From 51c9b49e18686750421d6c49b11b2ebdd7984b3a Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Sat, 29 Aug 2026 12:08:17 +0800 Subject: [PATCH] =?UTF-8?q?=E5=88=9D=E5=A7=8B=E5=8C=96=E9=A1=B9=E7=9B=AE?= =?UTF-8?q?=EF=BC=8C=E7=94=B1ModelHub=20XC=E7=A4=BE=E5=8C=BA=E6=8F=90?= =?UTF-8?q?=E4=BE=9B=E6=A8=A1=E5=9E=8B?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Model: Gueule-d-ange/llama32-3b-redo-dpo_simple Source: Original Platform --- .gitattributes | 36 + README.md | 71 + all_results.json | 26 + chat_template.jinja | 7 + config.json | 36 + eval_results.json | 21 + generation_config.json | 13 + model-00001-of-00002.safetensors | 3 + model-00002-of-00002.safetensors | 3 + model.safetensors.index.json | 263 +++ qualitative_epoch_1.csv | 130 ++ qualitative_epoch_1.jsonl | 8 + ...tfevents.1785382176.scw-zen-knuth.183882.0 | 3 + ...tfevents.1785396884.scw-zen-knuth.183882.1 | 3 + special_tokens_map.json | 26 + stability_metrics.jsonl | 95 + tokenizer.json | 3 + tokenizer_config.json | 2068 +++++++++++++++++ train_results.json | 8 + trainer_log.jsonl | 96 + trainer_state.json | 2036 ++++++++++++++++ training_args.bin | 3 + training_eval_loss.png | Bin 0 -> 34822 bytes training_loss.png | Bin 0 -> 43572 bytes training_rewards_accuracies.png | Bin 0 -> 48034 bytes training_rewards_chosen.png | Bin 0 -> 42787 bytes training_rewards_margins.png | Bin 0 -> 45376 bytes training_rewards_rejected.png | Bin 0 -> 57183 bytes 28 files changed, 4958 insertions(+) create mode 100644 .gitattributes create mode 100644 README.md create mode 100644 all_results.json create mode 100644 chat_template.jinja create mode 100644 config.json create mode 100644 eval_results.json create mode 100644 generation_config.json create mode 100644 model-00001-of-00002.safetensors create mode 100644 model-00002-of-00002.safetensors create mode 100644 model.safetensors.index.json create mode 100644 qualitative_epoch_1.csv create mode 100644 qualitative_epoch_1.jsonl create mode 100644 runs/Jul30_03-28-29_scw-zen-knuth/events.out.tfevents.1785382176.scw-zen-knuth.183882.0 create mode 100644 runs/Jul30_03-28-29_scw-zen-knuth/events.out.tfevents.1785396884.scw-zen-knuth.183882.1 create mode 100644 special_tokens_map.json create mode 100644 stability_metrics.jsonl create mode 100644 tokenizer.json create mode 100644 tokenizer_config.json create mode 100644 train_results.json create mode 100644 trainer_log.jsonl create mode 100644 trainer_state.json create mode 100644 training_args.bin create mode 100644 training_eval_loss.png create mode 100644 training_loss.png create mode 100644 training_rewards_accuracies.png create mode 100644 training_rewards_chosen.png create mode 100644 training_rewards_margins.png create mode 100644 training_rewards_rejected.png diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..52373fe --- /dev/null +++ b/.gitattributes @@ -0,0 +1,36 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs -text +*.onnx filter=lfs diff=lfs merge=lfs -text +*.ot filter=lfs diff=lfs merge=lfs -text +*.parquet filter=lfs diff=lfs merge=lfs -text +*.pb filter=lfs diff=lfs merge=lfs -text +*.pickle filter=lfs diff=lfs merge=lfs -text +*.pkl filter=lfs diff=lfs merge=lfs -text +*.pt filter=lfs diff=lfs merge=lfs -text +*.pth filter=lfs diff=lfs merge=lfs -text +*.rar filter=lfs diff=lfs merge=lfs -text +*.safetensors filter=lfs diff=lfs merge=lfs -text +saved_model/**/* filter=lfs diff=lfs merge=lfs -text +*.tar.* filter=lfs diff=lfs merge=lfs -text +*.tar filter=lfs diff=lfs merge=lfs -text +*.tflite filter=lfs diff=lfs merge=lfs -text +*.tgz filter=lfs diff=lfs merge=lfs -text +*.wasm filter=lfs diff=lfs merge=lfs -text +*.xz filter=lfs diff=lfs merge=lfs -text +*.zip filter=lfs diff=lfs merge=lfs -text +*.zst filter=lfs diff=lfs merge=lfs -text +*tfevents* filter=lfs diff=lfs merge=lfs -text +tokenizer.json filter=lfs diff=lfs merge=lfs -text diff --git a/README.md b/README.md new file mode 100644 index 0000000..d41e80a --- /dev/null +++ b/README.md @@ -0,0 +1,71 @@ +--- +base_model: meta-llama/Llama-3.2-3B +library_name: transformers +model_name: llama32-3b-redo-dpo_simple +tags: +- generated_from_trainer +- dpo +- llama-factory +- full +- trl +licence: license +--- + +# Model Card for llama32-3b-redo-dpo_simple + +This model is a fine-tuned version of [meta-llama/Llama-3.2-3B](https://huggingface.co/meta-llama/Llama-3.2-3B). +It has been trained using [TRL](https://github.com/huggingface/trl). + +## Quick start + +```python +from transformers import pipeline + +question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?" +generator = pipeline("text-generation", model="Gueule-d-ange/llama32-3b-redo-dpo_simple", device="cuda") +output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0] +print(output["generated_text"]) +``` + +## Training procedure + + + + +This model was trained with DPO, a method introduced in [Direct Preference Optimization: Your Language Model is Secretly a Reward Model](https://huggingface.co/papers/2305.18290). + +### Framework versions + +- TRL: 0.24.0 +- Transformers: 4.57.1 +- Pytorch: 2.12.1 +- Datasets: 4.0.0 +- Tokenizers: 0.22.2 + +## Citations + +Cite DPO as: + +```bibtex +@inproceedings{rafailov2023direct, + title = {{Direct Preference Optimization: Your Language Model is Secretly a Reward Model}}, + author = {Rafael Rafailov and Archit Sharma and Eric Mitchell and Christopher D. Manning and Stefano Ermon and Chelsea Finn}, + year = 2023, + booktitle = {Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023}, + url = {http://papers.nips.cc/paper_files/paper/2023/hash/a85b405ed65c6477a4fe8302b5e06ce7-Abstract-Conference.html}, + editor = {Alice Oh and Tristan Naumann and Amir Globerson and Kate Saenko and Moritz Hardt and Sergey Levine}, +} +``` + +Cite TRL as: + +```bibtex +@misc{vonwerra2022trl, + title = {{TRL: Transformer Reinforcement Learning}}, + author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallou{\'e}dec}, + year = 2020, + journal = {GitHub repository}, + publisher = {GitHub}, + howpublished = {\url{https://github.com/huggingface/trl}} +} +``` \ No newline at end of file diff --git a/all_results.json b/all_results.json new file mode 100644 index 0000000..7bdc459 --- /dev/null +++ b/all_results.json @@ -0,0 +1,26 @@ +{ + "epoch": 1.0, + "eval_logits/chosen": -1.3287253379821777, + "eval_logits/rejected": -1.3337767124176025, + "eval_logps/chosen": -316.3905944824219, + "eval_logps/rejected": -254.8103485107422, + "eval_loss": 0.4671759009361267, + "eval_metrics/advantage_var": 125.51482391357422, + "eval_rewards/accuracies": 0.7835859060287476, + "eval_rewards/chosen": 1.0432024002075195, + "eval_rewards/margins": 1.0373461246490479, + "eval_rewards/rejected": 0.005856274161487818, + "eval_runtime": 273.8577, + "eval_samples_per_second": 14.438, + "eval_stability/repetition_rate_mean": 0.8705078363418579, + "eval_stability/response_length_mean": 512.0, + "eval_stability/response_length_std": 0.0, + "eval_stability/response_length_var": 0.0, + "eval_stability/token_entropy_mean": 1.601953148841858, + "eval_steps_per_second": 1.808, + "total_flos": 1.761935585720664e+18, + "train_loss": 0.5203882457111775, + "train_runtime": 14354.8151, + "train_samples_per_second": 4.13, + "train_steps_per_second": 0.065 +} \ No newline at end of file diff --git a/chat_template.jinja b/chat_template.jinja new file mode 100644 index 0000000..c3af804 --- /dev/null +++ b/chat_template.jinja @@ -0,0 +1,7 @@ +{{ '<|begin_of_text|>' }}{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% else %}{% set loop_messages = messages %}{% endif %}{% if system_message is defined %}{{ '<|start_header_id|>system<|end_header_id|> + +' + system_message + '<|eot_id|>' }}{% endif %}{% for message in loop_messages %}{% set content = message['content'] %}{% if message['role'] == 'user' %}{{ '<|start_header_id|>user<|end_header_id|> + +' + content + '<|eot_id|><|start_header_id|>assistant<|end_header_id|> + +' }}{% elif message['role'] == 'assistant' %}{{ content + '<|eot_id|>' }}{% endif %}{% endfor %} \ No newline at end of file diff --git a/config.json b/config.json new file mode 100644 index 0000000..badb0f3 --- /dev/null +++ b/config.json @@ -0,0 +1,36 @@ +{ + "architectures": [ + "LlamaForCausalLM" + ], + "attention_bias": false, + "attention_dropout": 0.0, + "bos_token_id": 128000, + "dtype": "bfloat16", + "eos_token_id": 128009, + "head_dim": 128, + "hidden_act": "silu", + "hidden_size": 3072, + "initializer_range": 0.02, + "intermediate_size": 8192, + "max_position_embeddings": 131072, + "mlp_bias": false, + "model_type": "llama", + "num_attention_heads": 24, + "num_hidden_layers": 28, + "num_key_value_heads": 8, + "pad_token_id": 128009, + "pretraining_tp": 1, + "rms_norm_eps": 1e-05, + "rope_scaling": { + "factor": 32.0, + "high_freq_factor": 4.0, + "low_freq_factor": 1.0, + "original_max_position_embeddings": 8192, + "rope_type": "llama3" + }, + "rope_theta": 500000.0, + "tie_word_embeddings": true, + "transformers_version": "4.57.1", + "use_cache": false, + "vocab_size": 128256 +} diff --git a/eval_results.json b/eval_results.json new file mode 100644 index 0000000..2ca249c --- /dev/null +++ b/eval_results.json @@ -0,0 +1,21 @@ +{ + "epoch": 1.0, + "eval_logits/chosen": -1.3287253379821777, + "eval_logits/rejected": -1.3337767124176025, + "eval_logps/chosen": -316.3905944824219, + "eval_logps/rejected": -254.8103485107422, + "eval_loss": 0.4671759009361267, + "eval_metrics/advantage_var": 125.51482391357422, + "eval_rewards/accuracies": 0.7835859060287476, + "eval_rewards/chosen": 1.0432024002075195, + "eval_rewards/margins": 1.0373461246490479, + "eval_rewards/rejected": 0.005856274161487818, + "eval_runtime": 273.8577, + "eval_samples_per_second": 14.438, + "eval_stability/repetition_rate_mean": 0.8705078363418579, + "eval_stability/response_length_mean": 512.0, + "eval_stability/response_length_std": 0.0, + "eval_stability/response_length_var": 0.0, + "eval_stability/token_entropy_mean": 1.601953148841858, + "eval_steps_per_second": 1.808 +} \ No newline at end of file diff --git a/generation_config.json b/generation_config.json new file mode 100644 index 0000000..4228343 --- /dev/null +++ b/generation_config.json @@ -0,0 +1,13 @@ +{ + "_from_model_config": true, + "bos_token_id": 128000, + "do_sample": true, + "eos_token_id": [ + 128009, + 128001 + ], + "pad_token_id": 128009, + "temperature": 0.6, + "top_p": 0.9, + "transformers_version": "4.57.1" +} diff --git a/model-00001-of-00002.safetensors b/model-00001-of-00002.safetensors new file mode 100644 index 0000000..38d86e4 --- /dev/null +++ b/model-00001-of-00002.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:809afab775d6ee88e70155e4d52717e3778221670b4900475dc68d799c45a715 +size 4965799096 diff --git a/model-00002-of-00002.safetensors b/model-00002-of-00002.safetensors new file mode 100644 index 0000000..329f359 --- /dev/null +++ b/model-00002-of-00002.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:b91f90461124b47191505b2837b9f271a0e66cf76322082a631a393d797989f9 +size 2247734992 diff --git a/model.safetensors.index.json b/model.safetensors.index.json new file mode 100644 index 0000000..887d493 --- /dev/null +++ b/model.safetensors.index.json @@ -0,0 +1,263 @@ +{ + "metadata": { + "total_parameters": 3212749824, + "total_size": 7213504512 + }, + "weight_map": { + "lm_head.weight": "model-00002-of-00002.safetensors", + "model.embed_tokens.weight": "model-00001-of-00002.safetensors", + "model.layers.0.input_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.0.mlp.down_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.0.mlp.gate_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.0.mlp.up_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.0.post_attention_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.0.self_attn.k_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.0.self_attn.o_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.0.self_attn.q_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.0.self_attn.v_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.1.input_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.1.mlp.down_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.1.mlp.gate_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.1.mlp.up_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.1.post_attention_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.1.self_attn.k_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.1.self_attn.o_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.1.self_attn.q_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.1.self_attn.v_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.10.input_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.10.mlp.down_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.10.mlp.gate_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.10.mlp.up_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.10.post_attention_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.10.self_attn.k_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.10.self_attn.o_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.10.self_attn.q_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.10.self_attn.v_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.11.input_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.11.mlp.down_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.11.mlp.gate_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.11.mlp.up_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.11.post_attention_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.11.self_attn.k_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.11.self_attn.o_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.11.self_attn.q_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.11.self_attn.v_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.12.input_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.12.mlp.down_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.12.mlp.gate_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.12.mlp.up_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.12.post_attention_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.12.self_attn.k_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.12.self_attn.o_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.12.self_attn.q_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.12.self_attn.v_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.13.input_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.13.mlp.down_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.13.mlp.gate_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.13.mlp.up_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.13.post_attention_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.13.self_attn.k_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.13.self_attn.o_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.13.self_attn.q_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.13.self_attn.v_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.14.input_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.14.mlp.down_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.14.mlp.gate_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.14.mlp.up_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.14.post_attention_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.14.self_attn.k_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.14.self_attn.o_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.14.self_attn.q_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.14.self_attn.v_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.15.input_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.15.mlp.down_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.15.mlp.gate_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.15.mlp.up_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.15.post_attention_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.15.self_attn.k_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.15.self_attn.o_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.15.self_attn.q_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.15.self_attn.v_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.16.input_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.16.mlp.down_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.16.mlp.gate_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.16.mlp.up_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.16.post_attention_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.16.self_attn.k_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.16.self_attn.o_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.16.self_attn.q_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.16.self_attn.v_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.17.input_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.17.mlp.down_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.17.mlp.gate_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.17.mlp.up_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.17.post_attention_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.17.self_attn.k_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.17.self_attn.o_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.17.self_attn.q_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.17.self_attn.v_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.18.input_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.18.mlp.down_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.18.mlp.gate_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.18.mlp.up_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.18.post_attention_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.18.self_attn.k_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.18.self_attn.o_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.18.self_attn.q_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.18.self_attn.v_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.19.input_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.19.mlp.down_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.19.mlp.gate_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.19.mlp.up_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.19.post_attention_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.19.self_attn.k_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.19.self_attn.o_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.19.self_attn.q_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.19.self_attn.v_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.2.input_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.2.mlp.down_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.2.mlp.gate_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.2.mlp.up_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.2.post_attention_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.2.self_attn.k_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.2.self_attn.o_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.2.self_attn.q_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.2.self_attn.v_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.20.input_layernorm.weight": "model-00002-of-00002.safetensors", + "model.layers.20.mlp.down_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.20.mlp.gate_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.20.mlp.up_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.20.post_attention_layernorm.weight": "model-00002-of-00002.safetensors", + "model.layers.20.self_attn.k_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.20.self_attn.o_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.20.self_attn.q_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.20.self_attn.v_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.21.input_layernorm.weight": "model-00002-of-00002.safetensors", + "model.layers.21.mlp.down_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.21.mlp.gate_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.21.mlp.up_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.21.post_attention_layernorm.weight": "model-00002-of-00002.safetensors", + "model.layers.21.self_attn.k_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.21.self_attn.o_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.21.self_attn.q_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.21.self_attn.v_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.22.input_layernorm.weight": "model-00002-of-00002.safetensors", + "model.layers.22.mlp.down_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.22.mlp.gate_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.22.mlp.up_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.22.post_attention_layernorm.weight": "model-00002-of-00002.safetensors", + "model.layers.22.self_attn.k_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.22.self_attn.o_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.22.self_attn.q_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.22.self_attn.v_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.23.input_layernorm.weight": "model-00002-of-00002.safetensors", + "model.layers.23.mlp.down_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.23.mlp.gate_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.23.mlp.up_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.23.post_attention_layernorm.weight": "model-00002-of-00002.safetensors", + "model.layers.23.self_attn.k_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.23.self_attn.o_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.23.self_attn.q_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.23.self_attn.v_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.24.input_layernorm.weight": "model-00002-of-00002.safetensors", + "model.layers.24.mlp.down_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.24.mlp.gate_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.24.mlp.up_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.24.post_attention_layernorm.weight": "model-00002-of-00002.safetensors", + "model.layers.24.self_attn.k_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.24.self_attn.o_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.24.self_attn.q_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.24.self_attn.v_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.25.input_layernorm.weight": "model-00002-of-00002.safetensors", + "model.layers.25.mlp.down_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.25.mlp.gate_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.25.mlp.up_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.25.post_attention_layernorm.weight": "model-00002-of-00002.safetensors", + "model.layers.25.self_attn.k_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.25.self_attn.o_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.25.self_attn.q_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.25.self_attn.v_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.26.input_layernorm.weight": "model-00002-of-00002.safetensors", + "model.layers.26.mlp.down_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.26.mlp.gate_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.26.mlp.up_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.26.post_attention_layernorm.weight": "model-00002-of-00002.safetensors", + "model.layers.26.self_attn.k_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.26.self_attn.o_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.26.self_attn.q_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.26.self_attn.v_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.27.input_layernorm.weight": "model-00002-of-00002.safetensors", + "model.layers.27.mlp.down_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.27.mlp.gate_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.27.mlp.up_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.27.post_attention_layernorm.weight": "model-00002-of-00002.safetensors", + "model.layers.27.self_attn.k_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.27.self_attn.o_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.27.self_attn.q_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.27.self_attn.v_proj.weight": "model-00002-of-00002.safetensors", + "model.layers.3.input_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.3.mlp.down_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.3.mlp.gate_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.3.mlp.up_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.3.post_attention_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.3.self_attn.k_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.3.self_attn.o_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.3.self_attn.q_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.3.self_attn.v_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.4.input_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.4.mlp.down_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.4.mlp.gate_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.4.mlp.up_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.4.post_attention_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.4.self_attn.k_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.4.self_attn.o_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.4.self_attn.q_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.4.self_attn.v_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.5.input_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.5.mlp.down_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.5.mlp.gate_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.5.mlp.up_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.5.post_attention_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.5.self_attn.k_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.5.self_attn.o_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.5.self_attn.q_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.5.self_attn.v_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.6.input_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.6.mlp.down_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.6.mlp.gate_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.6.mlp.up_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.6.post_attention_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.6.self_attn.k_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.6.self_attn.o_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.6.self_attn.q_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.6.self_attn.v_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.7.input_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.7.mlp.down_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.7.mlp.gate_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.7.mlp.up_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.7.post_attention_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.7.self_attn.k_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.7.self_attn.o_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.7.self_attn.q_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.7.self_attn.v_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.8.input_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.8.mlp.down_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.8.mlp.gate_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.8.mlp.up_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.8.post_attention_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.8.self_attn.k_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.8.self_attn.o_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.8.self_attn.q_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.8.self_attn.v_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.9.input_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.9.mlp.down_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.9.mlp.gate_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.9.mlp.up_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.9.post_attention_layernorm.weight": "model-00001-of-00002.safetensors", + "model.layers.9.self_attn.k_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.9.self_attn.o_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.9.self_attn.q_proj.weight": "model-00001-of-00002.safetensors", + "model.layers.9.self_attn.v_proj.weight": "model-00001-of-00002.safetensors", + "model.norm.weight": "model-00002-of-00002.safetensors" + } +} diff --git a/qualitative_epoch_1.csv b/qualitative_epoch_1.csv new file mode 100644 index 0000000..413b650 --- /dev/null +++ b/qualitative_epoch_1.csv @@ -0,0 +1,130 @@ +epoch,global_step,prompt_id,prompt,response +1,927,0,"If someone naively says they will ""pick a random natural number uniformly,"" the probability of any fixed number seems to be zero, yet something gets picked. Walk a reader through what breaks in the usual probability story here, and mention at least two different ways mathematicians repair the intuition (measure theory, finitely additive approaches, ""don't ask that question,"" etc.).","Try to give the flavor of the measure theory approach.2013-10-12_03-47-21 +Let's say we have a sequence of natural numbers, $(a_n)_{n=1}^\infty$. A sequence of natural numbers is just a function $a: \mathbb{N} \to \mathbb{N}$. +If $n \in \mathbb{N}$, $a(n)$ is the $n$th natural number. +For example, if $a(n) = n^2$, then $a(1) = 1^2 = 1$, $a(2) = 2^2 = 4$, $a(3) = 3^2 = 9$, etc. +We will define a probability measure on the set of natural numbers by saying that the probability of $a(n)$ being chosen is $\frac{1}{n}$. +What's the probability of $a(n)$ being chosen if $n$ is odd? The probability of $a(n)$ being chosen if $n$ is even? +The probability of $a(n)$ being chosen is $\frac{1}{n}$, regardless of whether $n$ is odd or even. To see this, consider the probability of $a(n)$ being chosen if $n$ is even. +Let $E$ be the event that $n$ is even. Then $E$ is an event and has probability $\frac{1}{2}$. Let $A$ be the set of natural numbers that are even. Then +\begin{align*} P(a(n) = a(2k)) &= P(a(n) \in A)\\ &= P(a(n) \in A | E) P(E) + P(a(n) \in A | \overline{E}) P(\overline{E})\\ &= \frac{1}{2} \cdot \frac{1}{2} + 0 \cdot \frac{1}{2}\\ &= \frac{1}{4}. \end{align*} +The probability of $a(n)$ being chosen if $n$ is odd is exactly the same, so the probability of $a(n)$ being chosen is $\frac{1}{4}$ if $n$ is even and $\frac{3}{4}$ if $n$ is odd. +The probability of $a(n)$ being chosen is $\frac{1}{n}$. The probability of $" +1,927,1,"Explain why GPUs are not just ""faster CPUs"" for training neural networks—discuss memory bandwidth, batching, kernel fusion, and communication, at a level where someone could draw a wrong cartoon and a better cartoon of what is happening.","500 words, no citations, no references, no notes, no quotes, no diagrams, no images, no code. I want a coherent, simple, and readable explanation.What is a GPU? GPUs are graphics processing units, which are a type of coprocessor used for performing calculations in parallel, rather than sequentially, as a CPU does. They are typically used for rendering graphics and video, and more recently, they have been used for machine learning and deep learning. GPUs are optimized for parallel processing, making them particularly well-suited for tasks that require many computations, such as neural network training, image processing, and data analysis. GPUs typically have many cores, which can work in parallel, and are designed to perform mathematical operations like matrix multiplication, which are essential for neural network training. GPUs have a high bandwidth and fast memory access, which enables them to handle large datasets efficiently. GPUs also have a specialized architecture that makes them well-suited for parallel processing, allowing them to perform multiple computations at once. GPUs are not just ""faster CPUs"" for training neural networks, but they are a specialized hardware designed for parallel processing and have advantages over CPUs in terms of memory bandwidth, batching, kernel fusion, and communication. GPU vs. CPU for Neural Network Training: Memory Bandwidth: GPUs have a much higher bandwidth compared to CPUs, which means they can process data faster and handle large datasets more efficiently. CPUs, on the other hand, have a limited bandwidth, which can become a bottleneck when working with large datasets. Batching: GPUs can work with larger batches of data, which can significantly speed up the training process. CPUs, on the other hand, have a limit on the size of batches they can work with, making GPUs more efficient in terms of training time. Kernel Fusion: GPUs have a specialized architecture that allows for kernel fusion, which means that multiple instructions can be fused into a single operation, resulting in faster execution. CPUs, on the other hand, are not as efficient in terms of kernel fusion, making GPUs more efficient in terms of performance. Communication: GPUs have a specialized architecture that makes them more efficient in terms of communication, allowing them to communicate with each other more efficiently. CPUs, on the other hand, have a limited communication capacity, which can become a bottleneck when working with large datasets. GPUs are not just ""faster CPUs"" for training neural networks, but they have specialized hardware and architecture that make them more efficient in terms of memory bandwidth, batching, kernel fusion, and communication, which allows them" +1,927,2,"Some philosophers defend views that feel almost like performance art. Explain—as if to a curious undergrad—three different interpretations of what serious philosophers might be doing when they advocate bizarre-sounding positions (truth-seeking, steelmanning, career incentives, dialectical usefulness, etc.).","How would you respond to someone who thinks that these views are either uninteresting or incoherent? +What is a serious philosopher? +A serious philosopher is one who is not afraid to express a bold, controversial, or radical view. A serious philosopher is one who is not afraid to be wrong. A serious philosopher is one who is not afraid to be thought of as foolish, or eccentric, or even crazy. A serious philosopher is one who is not afraid to be ridiculed, or reviled, or reviled and ridiculed. +What is a serious philosopher’s job? +The job of a serious philosopher is to find the truth. The job of a serious philosopher is to find the truth about reality. The job of a serious philosopher is to find the truth about the universe. The job of a serious philosopher is to find the truth about the world. +What is a serious philosopher’s work? +The work of a serious philosopher is to find the truth. The work of a serious philosopher is to find the truth about reality. The work of a serious philosopher is to find the truth about the universe. The work of a serious philosopher is to find the truth about the world. +What is a serious philosopher’s aim? +The aim of a serious philosopher is to find the truth. The aim of a serious philosopher is to find the truth about reality. The aim of a serious philosopher is to find the truth about the universe. The aim of a serious philosopher is to find the truth about the world. +What is a serious philosopher’s goal? +The goal of a serious philosopher is to find the truth. The goal of a serious philosopher is to find the truth about reality. The goal of a serious philosopher is to find the truth about the universe. The goal of a serious philosopher is to find the truth about the world. +What is a serious philosopher’s task? +The task of a serious philosopher is to find the truth. The task of a serious philosopher is to find the truth about reality. The task of a serious philosopher is to find the truth about the universe. The task of a serious philosopher is to find the truth about the world. +What is a serious philosopher’s mission? +The mission of a serious philosopher is to find the truth. The mission of a serious philosopher is to find the truth about reality. The mission of a serious philosopher is to find the truth about the universe. The mission of a serious philosopher is to find the truth about the world. +What is a serious philosopher’s role? +The role of a serious philosopher is to find the truth. The" +1,927,3,"You are first author on a messy multi-lab paper; deadlines slip and people ghost you until the last minute but rarely say ""no."" Outline a delegation and communication system that is kind, repeatability-based, and escalates without humiliating juniors.","This is a very common issue. When I was a postdoc, I was the first author on a 10-author paper. It was a mess. People were ghosting me and I was ghosting people. It was not a great experience. +I'm the PI of a grant that is funded by a lot of agencies. I have 4 co-PIs on my grant, but I'm the only one who is responsible for reporting progress to the agencies. My co-PIs don't understand this and are frustrated. What's a good way to manage this? I'm the PI of a grant that is funded by a lot of agencies. I have 4 co-PIs on my grant, but I'm the only one who is responsible for reporting progress to the agencies. My co-PIs don't understand this and are frustrated. What's a good way to manage this? +As a postdoc, I'm the first author on a 20+ author paper, and it's taking longer than I expected. What's the best way to manage my expectations for this paper? As a postdoc, I'm the first author on a 20+ author paper, and it's taking longer than I expected. What's the best way to manage my expectations for this paper? +How can I be more assertive with my PI without it seeming like I'm being a jerk? I've been a postdoc for almost a year, and I'm still a little shy about telling my PI that I want to do a certain project or that I'm not happy with the way something is going. I feel like I'm not being as assertive as I should be. How can I be more assertive with my PI without it seeming like I'm being a jerk? I've been a postdoc for almost a year, and I'm still a little shy about telling my PI that I want to do a certain project or that I'm not happy with the way something is going. I feel like I'm not being as assertive as I should be. +I've been a postdoc for 2 years, and I'm still in the dark about how I'll be evaluated for promotion. Is there a way to get information about this? I've been a postdoc for 2 years, and I'm still in the dark about how I'll be evaluated for promotion. Is there a way to get information about this? +I have a new postdoc, and I need to write a new lab manual. How do I" +1,927,4,"You suddenly need to teach a semester of project-first high school ""engineering"" to beginners, with a shoestring budget. Propose a progression of hands-on milestones (weeks 1–16 mindset, not a shopping list) that could end in something ambitious without setting everyone up for only frustration.","What would you do, and what would you keep in mind? And how would you scale the same approach to teaching a full semester of ""engineering"" at a high school? +We're in a situation where we have a few weeks to put together a semester-long project-first class at a high school, and I'm asking for a bit of guidance. The project will be a high-altitude weather balloon launch, with a payload that could include a GPS, a temperature sensor, a barometer, a camera, and a small LED (or perhaps a few LEDs). The students will build and launch the balloon, and then analyze the data they collect. We're not building a rocket, but we're also not doing a simple balloon launch with a sensor attached. +What we have: +A school with a few dozen high school students (ages 14–18) who have had little to no engineering education, but who are interested in engineering and are motivated by the prospect of building something, launching it, and analyzing the data. +A few hundred dollars for supplies (some of which will come from the school, but not all). +A 3D printer that's not particularly fast, but will be adequate for the first version of the balloon. +A few hundred feet of PVC pipe (and associated fittings) that will be used to build the balloon. +A 6V battery (perhaps 1000 mAh) that will be used to power the payload. +A few hundred feet of 1/4"" copper wire that will be used for the payload's antenna. +The students will be doing this on their own time, in their free time, and in their spare time. +A few weeks to build and launch the balloon. +A semester-long class (or a semester of classes, depending on how we structure the class). +A few hundred feet of 1/4"" copper wire that will be used for the payload's antenna. +A 6V battery (perhaps 1000 mAh) that will be used to power the payload. +A few hundred feet of 1/4"" copper wire that will be used for the payload's antenna. +A 6V battery (perhaps 1000 mAh) that will be used to power the payload. +A few hundred feet of 1/4"" copper wire that will be used for the payload's antenna. +A 6V battery (perhaps 1000 mAh) that will be used to power the payload. +A few hundred feet of 1/4"" copper wire that will be used" +1,927,5,Write a 250-word story where the twist hinges on a misunderstanding of conditional probability.,"You may use a standard conditional probability formula, but you must show the reader how to understand the relationship. +Example: Two brothers, Jack and Jill, are trying to decide which of them will marry the woman they both like. If Jill marries the woman, then Jack will not, and vice versa. If Jack marries the woman, then Jill will not. The brothers know that the probability that Jill will marry the woman is 0.7, and that the probability that Jack will marry the woman is 0.4. Which brother will marry the woman? +Solution: We can represent this scenario using the following Venn diagram: +The probability that Jill will marry the woman is 0.7, so the shaded region is 0.7. The probability that Jack will marry the woman is 0.4, so the shaded region is 0.4. The probability that Jill will marry the woman is 0.7, and the probability that Jack will marry the woman is 0.4, so the probability that neither brother will marry the woman is 1 - 0.7 - 0.4 = 0.9. This means that the probability that one brother will marry the woman is 0.1, so the probability that Jack will marry the woman is 0.1. Therefore, Jack will marry the woman. +In your story, you should describe a scenario where the twist hinges on a misunderstanding of conditional probability. You should show the reader how to understand the relationship between the conditional probability and the probability of the event in question. +The story should be written in 250 words or less, and it should be in the form of a short story or a poem. You should include a title and a brief description of the story. You should also include a reference to the conditional probability formula and how it was used to solve the problem. +For example, here's a story that uses a misunderstanding of conditional probability as the twist: +A man named John was trying to decide whether to take a job in a new city. He had two options: Option 1: Take the job and move to the new city, or Option 2: Stay in his current city and continue working there. He knew that the probability of getting a job in the new city was 0.8, and the probability of getting a job in his current city was 0.2. He also knew that if he took the job in the new city, then he would have to move to the new city, and if" +1,927,6,"Engineering students debate whether chasing all-A grades is worth it versus projects and sleep. Analyze what grades do and do not proxy for, first-job signaling, learning depth, and opportunity cost—end with conditional advice for different student goals.","(10 minutes) +Grading is an important, but often misunderstood, part of your education. In this episode, we discuss the differences between high school, college, and grad school grading systems, the importance of grading feedback, and how to optimize your grades in each system. (20 minutes) +In this episode, we explore the different types of grades that universities use, including cumulative GPA, class grades, and pass/fail. We discuss the importance of understanding the grading system at your university and how to navigate it effectively. (20 minutes) +In this episode, we discuss the different types of grades that high schools use, including letter grades, GPA, and weighted GPA. We also explore the importance of understanding the grading system at your high school and how to navigate it effectively. (20 minutes) +In this episode, we discuss the importance of understanding the grading system at your university, including the difference between cumulative GPA and class grades, the impact of weighted and unweighted GPAs, and how to manage your grade point average. (20 minutes) +In this episode, we explore the different types of grades that high schools use, including letter grades, GPA, weighted GPA, and honors classes. We also discuss the importance of understanding the grading system at your high school and how to navigate it effectively. (20 minutes) +In this episode, we discuss the different types of grades that high schools use, including letter grades, GPA, weighted GPA, and honors classes. We also explore the importance of understanding the grading system at your high school and how to navigate it effectively. (20 minutes) +In this episode, we discuss the different types of grades that high schools use, including letter grades, GPA, weighted GPA, and honors classes. We also explore the importance of understanding the grading system at your high school and how to navigate it effectively. (20 minutes) +In this episode, we discuss the different types of grades that high schools use, including letter grades, GPA, weighted GPA, and honors classes. We also explore the importance of understanding the grading system at your high school and how to navigate it effectively. (20 minutes) +In this episode, we discuss the different types of grades that high schools use, including letter grades, GPA, weighted GPA, and honors classes. We also explore the importance of understanding the grading system at your high school and how to navigate it effectively. (20 minutes) +In this episode, we discuss the different types of grades that high schools use, including letter grades, GPA, weighted GPA, and honors classes. We also explore" +1,927,7,"You are a 10x engineer in a startup with a legacy monolith. You want to build a new system, but the existing code is a spaghetti monster. How do you start? Outline a plan to refactor the codebase without rewriting everything.","You will need to think about the following: + +- How do you extract a single class out of the codebase? +- How do you test your code? +- How do you keep the existing functionality intact while you refactor? +- How do you refactor the code in the most maintainable way possible? +- How do you communicate with your team about the refactor process? + +In this kata, you will write a function that refactors a given JavaScript code snippet to make it more maintainable and testable. You will need to use the following techniques: + +- Refactoring +- Extracting classes +- Extracting methods +- Extracting functions +- Refactoring with tests +- Communicating with your team +- Working in a team + +This kata is a practical application of the principles of test-driven development and code refactoring. You will need to apply these principles to a real-world scenario, which will help you to understand how to apply them in practice. + +You will also need to use the following tools: + +- A code editor (such as VS Code, Sublime Text, or Atom) +- A version control system (such as Git or Bitbucket) +- A testing framework (such as Mocha, Jest, or Jest) + +This kata will take you about 2-3 hours to complete, depending on your experience and the complexity of the code snippet you start with. You can use the following resources to help you: + +- [Refactoring](https://en.wikipedia.org/wiki/Code_refactoring) +- [Test-Driven Development](https://en.wikipedia.org/wiki/Test-driven_development) +- [Extracting classes](https://en.wikipedia.org/wiki/Extract_class) +- [Extracting methods](https://en.wikipedia.org/wiki/Extract_method) +- [Extracting functions](https://en.wikipedia.org/wiki/Extract_function) +- [Refactoring with tests](https://en.wikipedia.org/wiki/Test-driven_development#Refactoring) +- [Communicating with your team](https://en.wikipedia.org/wiki/Communication) +- [Working in a team](https://en.wikipedia.org/wiki/Teamwork) + +Good luck and have fun! +Isolate the classes in the given code snippet: + +```javascript +const app = { + state: { + user: { + name: 'John', + age: 30 + }, + posts: [ + { + id: 1, + title: 'My first post', + content: 'This is my first post.' + }, + { + id: 2, + title: '" diff --git a/qualitative_epoch_1.jsonl b/qualitative_epoch_1.jsonl new file mode 100644 index 0000000..94e78b6 --- /dev/null +++ b/qualitative_epoch_1.jsonl @@ -0,0 +1,8 @@ +{"epoch": 1, "global_step": 927, "prompt_id": 0, "prompt": "If someone naively says they will \"pick a random natural number uniformly,\" the probability of any fixed number seems to be zero, yet something gets picked. Walk a reader through what breaks in the usual probability story here, and mention at least two different ways mathematicians repair the intuition (measure theory, finitely additive approaches, \"don't ask that question,\" etc.).", "response": "Try to give the flavor of the measure theory approach.2013-10-12_03-47-21\nLet's say we have a sequence of natural numbers, $(a_n)_{n=1}^\\infty$. A sequence of natural numbers is just a function $a: \\mathbb{N} \\to \\mathbb{N}$.\nIf $n \\in \\mathbb{N}$, $a(n)$ is the $n$th natural number.\nFor example, if $a(n) = n^2$, then $a(1) = 1^2 = 1$, $a(2) = 2^2 = 4$, $a(3) = 3^2 = 9$, etc.\nWe will define a probability measure on the set of natural numbers by saying that the probability of $a(n)$ being chosen is $\\frac{1}{n}$.\nWhat's the probability of $a(n)$ being chosen if $n$ is odd? The probability of $a(n)$ being chosen if $n$ is even?\nThe probability of $a(n)$ being chosen is $\\frac{1}{n}$, regardless of whether $n$ is odd or even. To see this, consider the probability of $a(n)$ being chosen if $n$ is even.\nLet $E$ be the event that $n$ is even. Then $E$ is an event and has probability $\\frac{1}{2}$. Let $A$ be the set of natural numbers that are even. Then\n\\begin{align*} P(a(n) = a(2k)) &= P(a(n) \\in A)\\\\ &= P(a(n) \\in A | E) P(E) + P(a(n) \\in A | \\overline{E}) P(\\overline{E})\\\\ &= \\frac{1}{2} \\cdot \\frac{1}{2} + 0 \\cdot \\frac{1}{2}\\\\ &= \\frac{1}{4}. \\end{align*}\nThe probability of $a(n)$ being chosen if $n$ is odd is exactly the same, so the probability of $a(n)$ being chosen is $\\frac{1}{4}$ if $n$ is even and $\\frac{3}{4}$ if $n$ is odd.\nThe probability of $a(n)$ being chosen is $\\frac{1}{n}$. The probability of $"} +{"epoch": 1, "global_step": 927, "prompt_id": 1, "prompt": "Explain why GPUs are not just \"faster CPUs\" for training neural networks—discuss memory bandwidth, batching, kernel fusion, and communication, at a level where someone could draw a wrong cartoon and a better cartoon of what is happening.", "response": "500 words, no citations, no references, no notes, no quotes, no diagrams, no images, no code. I want a coherent, simple, and readable explanation.What is a GPU? GPUs are graphics processing units, which are a type of coprocessor used for performing calculations in parallel, rather than sequentially, as a CPU does. They are typically used for rendering graphics and video, and more recently, they have been used for machine learning and deep learning. GPUs are optimized for parallel processing, making them particularly well-suited for tasks that require many computations, such as neural network training, image processing, and data analysis. GPUs typically have many cores, which can work in parallel, and are designed to perform mathematical operations like matrix multiplication, which are essential for neural network training. GPUs have a high bandwidth and fast memory access, which enables them to handle large datasets efficiently. GPUs also have a specialized architecture that makes them well-suited for parallel processing, allowing them to perform multiple computations at once. GPUs are not just \"faster CPUs\" for training neural networks, but they are a specialized hardware designed for parallel processing and have advantages over CPUs in terms of memory bandwidth, batching, kernel fusion, and communication. GPU vs. CPU for Neural Network Training: Memory Bandwidth: GPUs have a much higher bandwidth compared to CPUs, which means they can process data faster and handle large datasets more efficiently. CPUs, on the other hand, have a limited bandwidth, which can become a bottleneck when working with large datasets. Batching: GPUs can work with larger batches of data, which can significantly speed up the training process. CPUs, on the other hand, have a limit on the size of batches they can work with, making GPUs more efficient in terms of training time. Kernel Fusion: GPUs have a specialized architecture that allows for kernel fusion, which means that multiple instructions can be fused into a single operation, resulting in faster execution. CPUs, on the other hand, are not as efficient in terms of kernel fusion, making GPUs more efficient in terms of performance. Communication: GPUs have a specialized architecture that makes them more efficient in terms of communication, allowing them to communicate with each other more efficiently. CPUs, on the other hand, have a limited communication capacity, which can become a bottleneck when working with large datasets. GPUs are not just \"faster CPUs\" for training neural networks, but they have specialized hardware and architecture that make them more efficient in terms of memory bandwidth, batching, kernel fusion, and communication, which allows them"} +{"epoch": 1, "global_step": 927, "prompt_id": 2, "prompt": "Some philosophers defend views that feel almost like performance art. Explain—as if to a curious undergrad—three different interpretations of what serious philosophers might be doing when they advocate bizarre-sounding positions (truth-seeking, steelmanning, career incentives, dialectical usefulness, etc.).", "response": "How would you respond to someone who thinks that these views are either uninteresting or incoherent?\nWhat is a serious philosopher?\nA serious philosopher is one who is not afraid to express a bold, controversial, or radical view. A serious philosopher is one who is not afraid to be wrong. A serious philosopher is one who is not afraid to be thought of as foolish, or eccentric, or even crazy. A serious philosopher is one who is not afraid to be ridiculed, or reviled, or reviled and ridiculed.\nWhat is a serious philosopher’s job?\nThe job of a serious philosopher is to find the truth. The job of a serious philosopher is to find the truth about reality. The job of a serious philosopher is to find the truth about the universe. The job of a serious philosopher is to find the truth about the world.\nWhat is a serious philosopher’s work?\nThe work of a serious philosopher is to find the truth. The work of a serious philosopher is to find the truth about reality. The work of a serious philosopher is to find the truth about the universe. The work of a serious philosopher is to find the truth about the world.\nWhat is a serious philosopher’s aim?\nThe aim of a serious philosopher is to find the truth. The aim of a serious philosopher is to find the truth about reality. The aim of a serious philosopher is to find the truth about the universe. The aim of a serious philosopher is to find the truth about the world.\nWhat is a serious philosopher’s goal?\nThe goal of a serious philosopher is to find the truth. The goal of a serious philosopher is to find the truth about reality. The goal of a serious philosopher is to find the truth about the universe. The goal of a serious philosopher is to find the truth about the world.\nWhat is a serious philosopher’s task?\nThe task of a serious philosopher is to find the truth. The task of a serious philosopher is to find the truth about reality. The task of a serious philosopher is to find the truth about the universe. The task of a serious philosopher is to find the truth about the world.\nWhat is a serious philosopher’s mission?\nThe mission of a serious philosopher is to find the truth. The mission of a serious philosopher is to find the truth about reality. The mission of a serious philosopher is to find the truth about the universe. The mission of a serious philosopher is to find the truth about the world.\nWhat is a serious philosopher’s role?\nThe role of a serious philosopher is to find the truth. The"} +{"epoch": 1, "global_step": 927, "prompt_id": 3, "prompt": "You are first author on a messy multi-lab paper; deadlines slip and people ghost you until the last minute but rarely say \"no.\" Outline a delegation and communication system that is kind, repeatability-based, and escalates without humiliating juniors.", "response": "This is a very common issue. When I was a postdoc, I was the first author on a 10-author paper. It was a mess. People were ghosting me and I was ghosting people. It was not a great experience.\nI'm the PI of a grant that is funded by a lot of agencies. I have 4 co-PIs on my grant, but I'm the only one who is responsible for reporting progress to the agencies. My co-PIs don't understand this and are frustrated. What's a good way to manage this? I'm the PI of a grant that is funded by a lot of agencies. I have 4 co-PIs on my grant, but I'm the only one who is responsible for reporting progress to the agencies. My co-PIs don't understand this and are frustrated. What's a good way to manage this?\nAs a postdoc, I'm the first author on a 20+ author paper, and it's taking longer than I expected. What's the best way to manage my expectations for this paper? As a postdoc, I'm the first author on a 20+ author paper, and it's taking longer than I expected. What's the best way to manage my expectations for this paper?\nHow can I be more assertive with my PI without it seeming like I'm being a jerk? I've been a postdoc for almost a year, and I'm still a little shy about telling my PI that I want to do a certain project or that I'm not happy with the way something is going. I feel like I'm not being as assertive as I should be. How can I be more assertive with my PI without it seeming like I'm being a jerk? I've been a postdoc for almost a year, and I'm still a little shy about telling my PI that I want to do a certain project or that I'm not happy with the way something is going. I feel like I'm not being as assertive as I should be.\nI've been a postdoc for 2 years, and I'm still in the dark about how I'll be evaluated for promotion. Is there a way to get information about this? I've been a postdoc for 2 years, and I'm still in the dark about how I'll be evaluated for promotion. Is there a way to get information about this?\nI have a new postdoc, and I need to write a new lab manual. How do I"} +{"epoch": 1, "global_step": 927, "prompt_id": 4, "prompt": "You suddenly need to teach a semester of project-first high school \"engineering\" to beginners, with a shoestring budget. Propose a progression of hands-on milestones (weeks 1–16 mindset, not a shopping list) that could end in something ambitious without setting everyone up for only frustration.", "response": "What would you do, and what would you keep in mind? And how would you scale the same approach to teaching a full semester of \"engineering\" at a high school?\nWe're in a situation where we have a few weeks to put together a semester-long project-first class at a high school, and I'm asking for a bit of guidance. The project will be a high-altitude weather balloon launch, with a payload that could include a GPS, a temperature sensor, a barometer, a camera, and a small LED (or perhaps a few LEDs). The students will build and launch the balloon, and then analyze the data they collect. We're not building a rocket, but we're also not doing a simple balloon launch with a sensor attached.\nWhat we have:\nA school with a few dozen high school students (ages 14–18) who have had little to no engineering education, but who are interested in engineering and are motivated by the prospect of building something, launching it, and analyzing the data.\nA few hundred dollars for supplies (some of which will come from the school, but not all).\nA 3D printer that's not particularly fast, but will be adequate for the first version of the balloon.\nA few hundred feet of PVC pipe (and associated fittings) that will be used to build the balloon.\nA 6V battery (perhaps 1000 mAh) that will be used to power the payload.\nA few hundred feet of 1/4\" copper wire that will be used for the payload's antenna.\nThe students will be doing this on their own time, in their free time, and in their spare time.\nA few weeks to build and launch the balloon.\nA semester-long class (or a semester of classes, depending on how we structure the class).\nA few hundred feet of 1/4\" copper wire that will be used for the payload's antenna.\nA 6V battery (perhaps 1000 mAh) that will be used to power the payload.\nA few hundred feet of 1/4\" copper wire that will be used for the payload's antenna.\nA 6V battery (perhaps 1000 mAh) that will be used to power the payload.\nA few hundred feet of 1/4\" copper wire that will be used for the payload's antenna.\nA 6V battery (perhaps 1000 mAh) that will be used to power the payload.\nA few hundred feet of 1/4\" copper wire that will be used"} +{"epoch": 1, "global_step": 927, "prompt_id": 5, "prompt": "Write a 250-word story where the twist hinges on a misunderstanding of conditional probability.", "response": "You may use a standard conditional probability formula, but you must show the reader how to understand the relationship.\nExample: Two brothers, Jack and Jill, are trying to decide which of them will marry the woman they both like. If Jill marries the woman, then Jack will not, and vice versa. If Jack marries the woman, then Jill will not. The brothers know that the probability that Jill will marry the woman is 0.7, and that the probability that Jack will marry the woman is 0.4. Which brother will marry the woman?\nSolution: We can represent this scenario using the following Venn diagram:\nThe probability that Jill will marry the woman is 0.7, so the shaded region is 0.7. The probability that Jack will marry the woman is 0.4, so the shaded region is 0.4. The probability that Jill will marry the woman is 0.7, and the probability that Jack will marry the woman is 0.4, so the probability that neither brother will marry the woman is 1 - 0.7 - 0.4 = 0.9. This means that the probability that one brother will marry the woman is 0.1, so the probability that Jack will marry the woman is 0.1. Therefore, Jack will marry the woman.\nIn your story, you should describe a scenario where the twist hinges on a misunderstanding of conditional probability. You should show the reader how to understand the relationship between the conditional probability and the probability of the event in question.\nThe story should be written in 250 words or less, and it should be in the form of a short story or a poem. You should include a title and a brief description of the story. You should also include a reference to the conditional probability formula and how it was used to solve the problem.\nFor example, here's a story that uses a misunderstanding of conditional probability as the twist:\nA man named John was trying to decide whether to take a job in a new city. He had two options: Option 1: Take the job and move to the new city, or Option 2: Stay in his current city and continue working there. He knew that the probability of getting a job in the new city was 0.8, and the probability of getting a job in his current city was 0.2. He also knew that if he took the job in the new city, then he would have to move to the new city, and if"} +{"epoch": 1, "global_step": 927, "prompt_id": 6, "prompt": "Engineering students debate whether chasing all-A grades is worth it versus projects and sleep. Analyze what grades do and do not proxy for, first-job signaling, learning depth, and opportunity cost—end with conditional advice for different student goals.", "response": "(10 minutes)\nGrading is an important, but often misunderstood, part of your education. In this episode, we discuss the differences between high school, college, and grad school grading systems, the importance of grading feedback, and how to optimize your grades in each system. (20 minutes)\nIn this episode, we explore the different types of grades that universities use, including cumulative GPA, class grades, and pass/fail. We discuss the importance of understanding the grading system at your university and how to navigate it effectively. (20 minutes)\nIn this episode, we discuss the different types of grades that high schools use, including letter grades, GPA, and weighted GPA. We also explore the importance of understanding the grading system at your high school and how to navigate it effectively. (20 minutes)\nIn this episode, we discuss the importance of understanding the grading system at your university, including the difference between cumulative GPA and class grades, the impact of weighted and unweighted GPAs, and how to manage your grade point average. (20 minutes)\nIn this episode, we explore the different types of grades that high schools use, including letter grades, GPA, weighted GPA, and honors classes. We also discuss the importance of understanding the grading system at your high school and how to navigate it effectively. (20 minutes)\nIn this episode, we discuss the different types of grades that high schools use, including letter grades, GPA, weighted GPA, and honors classes. We also explore the importance of understanding the grading system at your high school and how to navigate it effectively. (20 minutes)\nIn this episode, we discuss the different types of grades that high schools use, including letter grades, GPA, weighted GPA, and honors classes. We also explore the importance of understanding the grading system at your high school and how to navigate it effectively. (20 minutes)\nIn this episode, we discuss the different types of grades that high schools use, including letter grades, GPA, weighted GPA, and honors classes. We also explore the importance of understanding the grading system at your high school and how to navigate it effectively. (20 minutes)\nIn this episode, we discuss the different types of grades that high schools use, including letter grades, GPA, weighted GPA, and honors classes. We also explore the importance of understanding the grading system at your high school and how to navigate it effectively. (20 minutes)\nIn this episode, we discuss the different types of grades that high schools use, including letter grades, GPA, weighted GPA, and honors classes. We also explore"} +{"epoch": 1, "global_step": 927, "prompt_id": 7, "prompt": "You are a 10x engineer in a startup with a legacy monolith. You want to build a new system, but the existing code is a spaghetti monster. How do you start? Outline a plan to refactor the codebase without rewriting everything.", "response": "You will need to think about the following:\n\n- How do you extract a single class out of the codebase?\n- How do you test your code?\n- How do you keep the existing functionality intact while you refactor?\n- How do you refactor the code in the most maintainable way possible?\n- How do you communicate with your team about the refactor process?\n\nIn this kata, you will write a function that refactors a given JavaScript code snippet to make it more maintainable and testable. You will need to use the following techniques:\n\n- Refactoring\n- Extracting classes\n- Extracting methods\n- Extracting functions\n- Refactoring with tests\n- Communicating with your team\n- Working in a team\n\nThis kata is a practical application of the principles of test-driven development and code refactoring. You will need to apply these principles to a real-world scenario, which will help you to understand how to apply them in practice.\n\nYou will also need to use the following tools:\n\n- A code editor (such as VS Code, Sublime Text, or Atom)\n- A version control system (such as Git or Bitbucket)\n- A testing framework (such as Mocha, Jest, or Jest)\n\nThis kata will take you about 2-3 hours to complete, depending on your experience and the complexity of the code snippet you start with. You can use the following resources to help you:\n\n- [Refactoring](https://en.wikipedia.org/wiki/Code_refactoring)\n- [Test-Driven Development](https://en.wikipedia.org/wiki/Test-driven_development)\n- [Extracting classes](https://en.wikipedia.org/wiki/Extract_class)\n- [Extracting methods](https://en.wikipedia.org/wiki/Extract_method)\n- [Extracting functions](https://en.wikipedia.org/wiki/Extract_function)\n- [Refactoring with tests](https://en.wikipedia.org/wiki/Test-driven_development#Refactoring)\n- [Communicating with your team](https://en.wikipedia.org/wiki/Communication)\n- [Working in a team](https://en.wikipedia.org/wiki/Teamwork)\n\nGood luck and have fun!\nIsolate the classes in the given code snippet:\n\n```javascript\nconst app = {\n state: {\n user: {\n name: 'John',\n age: 30\n },\n posts: [\n {\n id: 1,\n title: 'My first post',\n content: 'This is my first post.'\n },\n {\n id: 2,\n title: '"} diff --git a/runs/Jul30_03-28-29_scw-zen-knuth/events.out.tfevents.1785382176.scw-zen-knuth.183882.0 b/runs/Jul30_03-28-29_scw-zen-knuth/events.out.tfevents.1785382176.scw-zen-knuth.183882.0 new file mode 100644 index 0000000..f858c35 --- /dev/null +++ b/runs/Jul30_03-28-29_scw-zen-knuth/events.out.tfevents.1785382176.scw-zen-knuth.183882.0 @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:33fb528865fdcdc98cbc60ff2937edf02d796964cb44fd40e9373969272d0b24 +size 112608 diff --git a/runs/Jul30_03-28-29_scw-zen-knuth/events.out.tfevents.1785396884.scw-zen-knuth.183882.1 b/runs/Jul30_03-28-29_scw-zen-knuth/events.out.tfevents.1785396884.scw-zen-knuth.183882.1 new file mode 100644 index 0000000..cb5f6f9 --- /dev/null +++ b/runs/Jul30_03-28-29_scw-zen-knuth/events.out.tfevents.1785396884.scw-zen-knuth.183882.1 @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:29494368a59122aee4d79f3d624cf37e087dd8b76cb23c2bc55bed8ee3d16792 +size 1259 diff --git a/special_tokens_map.json b/special_tokens_map.json new file mode 100644 index 0000000..14daf45 --- /dev/null +++ b/special_tokens_map.json @@ -0,0 +1,26 @@ +{ + "additional_special_tokens": [ + { + "content": "<|eom_id|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + } + ], + "bos_token": { + "content": "<|begin_of_text|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + }, + "eos_token": { + "content": "<|eot_id|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + }, + "pad_token": "<|eot_id|>" +} diff --git a/stability_metrics.jsonl b/stability_metrics.jsonl new file mode 100644 index 0000000..663386f --- /dev/null +++ b/stability_metrics.jsonl @@ -0,0 +1,95 @@ +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.434472680091858, "stability/repetition_rate_mean": 0.8257812261581421, "step": 20} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.364843726158142, "stability/repetition_rate_mean": 0.8824218511581421, "step": 30} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.0068359375, "stability/repetition_rate_mean": 0.8031250238418579, "step": 40} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.07568359375, "stability/repetition_rate_mean": 0.8675781488418579, "step": 50} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.2527344226837158, "stability/repetition_rate_mean": 0.7318359613418579, "step": 60} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.3330078125, "stability/repetition_rate_mean": 0.8822265863418579, "step": 70} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.825048804283142, "stability/repetition_rate_mean": 0.8583984375, "step": 80} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.663671851158142, "stability/repetition_rate_mean": 0.8740234375, "step": 90} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.4281249046325684, "stability/repetition_rate_mean": 0.9400390386581421, "step": 100} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.246875047683716, "stability/repetition_rate_mean": 0.809374988079071, "step": 110} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.070214867591858, "stability/repetition_rate_mean": 0.7470703125, "step": 120} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.4833984375, "stability/repetition_rate_mean": 0.773242175579071, "step": 130} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.019140601158142, "stability/repetition_rate_mean": 0.8072265386581421, "step": 140} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.5673828125, "stability/repetition_rate_mean": 0.807421863079071, "step": 150} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.4421875476837158, "stability/repetition_rate_mean": 0.789257824420929, "step": 160} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.5763671398162842, "stability/repetition_rate_mean": 0.7845703363418579, "step": 170} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.5693359375, "stability/repetition_rate_mean": 0.7490234375, "step": 180} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.1296875476837158, "stability/repetition_rate_mean": 0.850781261920929, "step": 190} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.4445312023162842, "stability/repetition_rate_mean": 0.796679675579071, "step": 200} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.3254883289337158, "stability/repetition_rate_mean": 0.81640625, "step": 210} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.763671875, "stability/repetition_rate_mean": 0.7367187738418579, "step": 220} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.4400391578674316, "stability/repetition_rate_mean": 0.8841797113418579, "step": 230} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.0635743141174316, "stability/repetition_rate_mean": 0.802539050579071, "step": 240} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.45166015625, "stability/repetition_rate_mean": 0.811718761920929, "step": 250} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.894628882408142, "stability/repetition_rate_mean": 0.813281238079071, "step": 260} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.030859351158142, "stability/repetition_rate_mean": 0.828906238079071, "step": 270} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.202734351158142, "stability/repetition_rate_mean": 0.8851562738418579, "step": 280} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.6193358898162842, "stability/repetition_rate_mean": 0.8099609613418579, "step": 290} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.1236329078674316, "stability/repetition_rate_mean": 0.7289062738418579, "step": 300} +{"eval_stability/response_length_mean": 512.0, "eval_stability/response_length_std": 0.0, "eval_stability/response_length_var": 0.0, "eval_stability/token_entropy_mean": 1.9105956554412842, "eval_stability/repetition_rate_mean": 0.9048827886581421, "step": 300} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 0.908203125, "stability/repetition_rate_mean": 0.799023449420929, "step": 310} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.083886742591858, "stability/repetition_rate_mean": 0.9072265625, "step": 320} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.7205078601837158, "stability/repetition_rate_mean": 0.955273449420929, "step": 330} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.8572266101837158, "stability/repetition_rate_mean": 0.7232421636581421, "step": 340} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.2517578601837158, "stability/repetition_rate_mean": 0.76953125, "step": 350} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.2664062976837158, "stability/repetition_rate_mean": 0.889843761920929, "step": 360} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.752539038658142, "stability/repetition_rate_mean": 0.777148425579071, "step": 370} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.844921827316284, "stability/repetition_rate_mean": 0.7945312261581421, "step": 380} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.869531273841858, "stability/repetition_rate_mean": 0.74609375, "step": 390} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.6525390148162842, "stability/repetition_rate_mean": 0.7679687738418579, "step": 400} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.6925780773162842, "stability/repetition_rate_mean": 0.854296863079071, "step": 410} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.1460938453674316, "stability/repetition_rate_mean": 0.822460949420929, "step": 420} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.808789014816284, "stability/repetition_rate_mean": 0.78125, "step": 430} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.164990186691284, "stability/repetition_rate_mean": 0.8707031011581421, "step": 440} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.7429687976837158, "stability/repetition_rate_mean": 0.8236328363418579, "step": 450} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.7371094226837158, "stability/repetition_rate_mean": 0.8646484613418579, "step": 460} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.244531273841858, "stability/repetition_rate_mean": 0.8687499761581421, "step": 470} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.1624999046325684, "stability/repetition_rate_mean": 0.8519531488418579, "step": 480} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.9038817882537842, "stability/repetition_rate_mean": 0.8125, "step": 490} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.1546874046325684, "stability/repetition_rate_mean": 0.7855468988418579, "step": 500} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.330175757408142, "stability/repetition_rate_mean": 0.8619140386581421, "step": 510} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.715429663658142, "stability/repetition_rate_mean": 0.856640636920929, "step": 520} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.365820288658142, "stability/repetition_rate_mean": 0.7701171636581421, "step": 530} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.7644531726837158, "stability/repetition_rate_mean": 0.8062499761581421, "step": 540} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.9962890148162842, "stability/repetition_rate_mean": 0.8472656011581421, "step": 550} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.4849610328674316, "stability/repetition_rate_mean": 0.784960925579071, "step": 560} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 0.817578136920929, "stability/repetition_rate_mean": 0.828906238079071, "step": 570} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.6736328601837158, "stability/repetition_rate_mean": 0.7662109136581421, "step": 580} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.351171851158142, "stability/repetition_rate_mean": 0.8466796875, "step": 590} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.7417969703674316, "stability/repetition_rate_mean": 0.8042968511581421, "step": 600} +{"eval_stability/response_length_mean": 512.0, "eval_stability/response_length_std": 0.0, "eval_stability/response_length_var": 0.0, "eval_stability/token_entropy_mean": 2.07421875, "eval_stability/repetition_rate_mean": 0.8873046636581421, "step": 600} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.9982421398162842, "stability/repetition_rate_mean": 0.744921863079071, "step": 610} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.2964844703674316, "stability/repetition_rate_mean": 0.8783203363418579, "step": 620} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.377539038658142, "stability/repetition_rate_mean": 0.8720703125, "step": 630} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.7732422351837158, "stability/repetition_rate_mean": 0.7818359136581421, "step": 640} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.5888671875, "stability/repetition_rate_mean": 0.850390613079071, "step": 650} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.3021483421325684, "stability/repetition_rate_mean": 0.775585949420929, "step": 660} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.6103515625, "stability/repetition_rate_mean": 0.785937488079071, "step": 670} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.3708984851837158, "stability/repetition_rate_mean": 0.7417968511581421, "step": 680} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.596289038658142, "stability/repetition_rate_mean": 0.8603515625, "step": 690} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.692675828933716, "stability/repetition_rate_mean": 0.8111327886581421, "step": 700} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.209765672683716, "stability/repetition_rate_mean": 0.840039074420929, "step": 710} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 0.8656250238418579, "stability/repetition_rate_mean": 0.8203125, "step": 720} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.055468797683716, "stability/repetition_rate_mean": 0.7437499761581421, "step": 730} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.513671875, "stability/repetition_rate_mean": 0.775195300579071, "step": 740} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.7333984375, "stability/repetition_rate_mean": 0.825390636920929, "step": 750} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.017578125, "stability/repetition_rate_mean": 0.779101550579071, "step": 760} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.833984375, "stability/repetition_rate_mean": 0.8814452886581421, "step": 770} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.575585961341858, "stability/repetition_rate_mean": 0.795703113079071, "step": 780} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.439843773841858, "stability/repetition_rate_mean": 0.8095703125, "step": 790} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.61376953125, "stability/repetition_rate_mean": 0.9134765863418579, "step": 800} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.4040038585662842, "stability/repetition_rate_mean": 0.8667968511581421, "step": 810} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.8826172351837158, "stability/repetition_rate_mean": 0.9224609136581421, "step": 820} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.1563477516174316, "stability/repetition_rate_mean": 0.8330078125, "step": 830} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.4929687976837158, "stability/repetition_rate_mean": 0.8158203363418579, "step": 840} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.3533203601837158, "stability/repetition_rate_mean": 0.7544921636581421, "step": 850} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.556640625, "stability/repetition_rate_mean": 0.805468738079071, "step": 860} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.4718749523162842, "stability/repetition_rate_mean": 0.864453136920929, "step": 870} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.583984375, "stability/repetition_rate_mean": 0.8818359375, "step": 880} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.6566405296325684, "stability/repetition_rate_mean": 0.8443359136581421, "step": 890} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.3954589366912842, "stability/repetition_rate_mean": 0.7369140386581421, "step": 900} +{"eval_stability/response_length_mean": 512.0, "eval_stability/response_length_std": 0.0, "eval_stability/response_length_var": 0.0, "eval_stability/token_entropy_mean": 1.127832055091858, "eval_stability/repetition_rate_mean": 0.811718761920929, "step": 900} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.468652367591858, "stability/repetition_rate_mean": 0.875195324420929, "step": 910} +{"stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.8033204078674316, "stability/repetition_rate_mean": 0.861328125, "step": 920} +{"eval_stability/response_length_mean": 512.0, "eval_stability/response_length_std": 0.0, "eval_stability/response_length_var": 0.0, "eval_stability/token_entropy_mean": 1.601953148841858, "eval_stability/repetition_rate_mean": 0.8705078363418579, "step": 927} diff --git a/tokenizer.json b/tokenizer.json new file mode 100644 index 0000000..a6552db --- /dev/null +++ b/tokenizer.json @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:76cfe2f054560aae896b2b75e273dc97a39e304d4ad19c44a9727a1d6b33c4cc +size 17210021 diff --git a/tokenizer_config.json b/tokenizer_config.json new file mode 100644 index 0000000..d1e1ea9 --- /dev/null +++ b/tokenizer_config.json @@ -0,0 +1,2068 @@ +{ + "added_tokens_decoder": { + "128000": { + "content": "<|begin_of_text|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128001": { + "content": "<|end_of_text|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128002": { + "content": "<|reserved_special_token_0|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128003": { + "content": "<|reserved_special_token_1|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128004": { + "content": "<|finetune_right_pad_id|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128005": { + "content": "<|reserved_special_token_2|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128006": { + "content": "<|start_header_id|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128007": { + "content": "<|end_header_id|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128008": { + "content": "<|eom_id|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128009": { + "content": "<|eot_id|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128010": { + "content": "<|python_tag|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128011": { + "content": "<|reserved_special_token_3|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128012": { + "content": "<|reserved_special_token_4|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128013": { + "content": "<|reserved_special_token_5|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128014": { + "content": "<|reserved_special_token_6|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128015": { + "content": "<|reserved_special_token_7|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128016": { + "content": "<|reserved_special_token_8|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128017": { + "content": "<|reserved_special_token_9|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128018": { + "content": "<|reserved_special_token_10|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128019": { + "content": "<|reserved_special_token_11|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128020": { + "content": "<|reserved_special_token_12|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128021": { + "content": "<|reserved_special_token_13|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128022": { + "content": "<|reserved_special_token_14|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128023": { + "content": "<|reserved_special_token_15|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128024": { + "content": "<|reserved_special_token_16|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128025": { + "content": "<|reserved_special_token_17|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128026": { + "content": "<|reserved_special_token_18|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128027": { + "content": "<|reserved_special_token_19|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128028": { + "content": "<|reserved_special_token_20|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128029": { + "content": "<|reserved_special_token_21|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128030": { + "content": "<|reserved_special_token_22|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128031": { + "content": "<|reserved_special_token_23|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128032": { + "content": "<|reserved_special_token_24|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128033": { + "content": "<|reserved_special_token_25|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128034": { + "content": "<|reserved_special_token_26|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128035": { + "content": "<|reserved_special_token_27|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128036": { + "content": "<|reserved_special_token_28|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128037": { + "content": "<|reserved_special_token_29|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128038": { + "content": "<|reserved_special_token_30|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128039": { + "content": "<|reserved_special_token_31|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128040": { + "content": "<|reserved_special_token_32|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128041": { + "content": "<|reserved_special_token_33|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128042": { + "content": "<|reserved_special_token_34|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128043": { + "content": "<|reserved_special_token_35|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128044": { + "content": "<|reserved_special_token_36|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128045": { + "content": "<|reserved_special_token_37|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128046": { + "content": "<|reserved_special_token_38|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128047": { + "content": "<|reserved_special_token_39|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128048": { + "content": "<|reserved_special_token_40|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128049": { + "content": "<|reserved_special_token_41|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128050": { + "content": "<|reserved_special_token_42|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128051": { + "content": "<|reserved_special_token_43|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128052": { + "content": "<|reserved_special_token_44|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128053": { + "content": "<|reserved_special_token_45|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128054": { + "content": "<|reserved_special_token_46|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128055": { + "content": "<|reserved_special_token_47|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128056": { + "content": "<|reserved_special_token_48|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128057": { + "content": "<|reserved_special_token_49|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128058": { + "content": "<|reserved_special_token_50|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128059": { + "content": "<|reserved_special_token_51|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128060": { + "content": "<|reserved_special_token_52|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128061": { + "content": "<|reserved_special_token_53|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128062": { + "content": "<|reserved_special_token_54|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128063": { + "content": "<|reserved_special_token_55|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128064": { + "content": "<|reserved_special_token_56|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128065": { + "content": "<|reserved_special_token_57|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128066": { + "content": "<|reserved_special_token_58|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128067": { + "content": "<|reserved_special_token_59|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128068": { + "content": "<|reserved_special_token_60|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128069": { + "content": "<|reserved_special_token_61|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128070": { + "content": "<|reserved_special_token_62|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128071": { + "content": "<|reserved_special_token_63|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128072": { + "content": "<|reserved_special_token_64|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128073": { + "content": "<|reserved_special_token_65|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128074": { + "content": "<|reserved_special_token_66|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128075": { + "content": "<|reserved_special_token_67|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128076": { + "content": "<|reserved_special_token_68|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128077": { + "content": "<|reserved_special_token_69|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128078": { + "content": "<|reserved_special_token_70|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128079": { + "content": "<|reserved_special_token_71|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128080": { + "content": "<|reserved_special_token_72|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128081": { + "content": "<|reserved_special_token_73|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128082": { + "content": "<|reserved_special_token_74|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128083": { + "content": "<|reserved_special_token_75|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128084": { + "content": "<|reserved_special_token_76|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128085": { + "content": "<|reserved_special_token_77|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128086": { + "content": "<|reserved_special_token_78|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128087": { + "content": "<|reserved_special_token_79|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128088": { + "content": "<|reserved_special_token_80|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128089": { + "content": "<|reserved_special_token_81|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128090": { + "content": "<|reserved_special_token_82|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128091": { + "content": "<|reserved_special_token_83|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128092": { + "content": "<|reserved_special_token_84|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128093": { + "content": "<|reserved_special_token_85|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128094": { + "content": "<|reserved_special_token_86|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128095": { + "content": "<|reserved_special_token_87|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128096": { + "content": "<|reserved_special_token_88|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128097": { + "content": "<|reserved_special_token_89|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128098": { + "content": "<|reserved_special_token_90|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128099": { + "content": "<|reserved_special_token_91|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128100": { + "content": "<|reserved_special_token_92|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128101": { + "content": "<|reserved_special_token_93|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128102": { + "content": "<|reserved_special_token_94|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128103": { + "content": "<|reserved_special_token_95|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128104": { + "content": "<|reserved_special_token_96|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128105": { + "content": "<|reserved_special_token_97|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128106": { + "content": "<|reserved_special_token_98|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128107": { + "content": "<|reserved_special_token_99|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128108": { + "content": "<|reserved_special_token_100|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128109": { + "content": "<|reserved_special_token_101|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128110": { + "content": "<|reserved_special_token_102|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128111": { + "content": "<|reserved_special_token_103|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128112": { + "content": "<|reserved_special_token_104|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128113": { + "content": "<|reserved_special_token_105|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128114": { + "content": "<|reserved_special_token_106|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128115": { + "content": "<|reserved_special_token_107|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128116": { + "content": "<|reserved_special_token_108|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128117": { + "content": "<|reserved_special_token_109|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128118": { + "content": "<|reserved_special_token_110|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128119": { + "content": "<|reserved_special_token_111|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128120": { + "content": "<|reserved_special_token_112|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128121": { + "content": "<|reserved_special_token_113|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128122": { + "content": "<|reserved_special_token_114|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128123": { + "content": "<|reserved_special_token_115|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128124": { + "content": "<|reserved_special_token_116|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128125": { + "content": "<|reserved_special_token_117|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128126": { + "content": "<|reserved_special_token_118|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128127": { + "content": "<|reserved_special_token_119|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128128": { + "content": "<|reserved_special_token_120|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128129": { + "content": "<|reserved_special_token_121|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128130": { + "content": "<|reserved_special_token_122|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128131": { + "content": "<|reserved_special_token_123|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128132": { + "content": "<|reserved_special_token_124|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128133": { + "content": "<|reserved_special_token_125|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128134": { + "content": "<|reserved_special_token_126|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128135": { + "content": "<|reserved_special_token_127|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128136": { + "content": "<|reserved_special_token_128|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128137": { + "content": "<|reserved_special_token_129|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128138": { + "content": "<|reserved_special_token_130|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128139": { + "content": "<|reserved_special_token_131|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128140": { + "content": "<|reserved_special_token_132|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128141": { + "content": "<|reserved_special_token_133|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128142": { + "content": "<|reserved_special_token_134|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128143": { + "content": "<|reserved_special_token_135|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128144": { + "content": "<|reserved_special_token_136|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128145": { + "content": "<|reserved_special_token_137|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128146": { + "content": "<|reserved_special_token_138|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128147": { + "content": "<|reserved_special_token_139|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128148": { + "content": "<|reserved_special_token_140|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128149": { + "content": "<|reserved_special_token_141|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128150": { + "content": "<|reserved_special_token_142|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128151": { + "content": "<|reserved_special_token_143|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128152": { + "content": "<|reserved_special_token_144|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128153": { + "content": "<|reserved_special_token_145|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128154": { + "content": "<|reserved_special_token_146|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128155": { + "content": "<|reserved_special_token_147|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128156": { + "content": "<|reserved_special_token_148|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128157": { + "content": "<|reserved_special_token_149|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128158": { + "content": "<|reserved_special_token_150|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128159": { + "content": "<|reserved_special_token_151|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128160": { + "content": "<|reserved_special_token_152|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128161": { + "content": "<|reserved_special_token_153|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128162": { + "content": "<|reserved_special_token_154|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128163": { + "content": "<|reserved_special_token_155|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128164": { + "content": "<|reserved_special_token_156|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128165": { + "content": "<|reserved_special_token_157|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128166": { + "content": "<|reserved_special_token_158|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128167": { + "content": "<|reserved_special_token_159|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128168": { + "content": "<|reserved_special_token_160|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128169": { + "content": "<|reserved_special_token_161|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128170": { + "content": "<|reserved_special_token_162|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128171": { + "content": "<|reserved_special_token_163|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128172": { + "content": "<|reserved_special_token_164|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128173": { + "content": "<|reserved_special_token_165|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128174": { + "content": "<|reserved_special_token_166|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128175": { + "content": "<|reserved_special_token_167|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128176": { + "content": "<|reserved_special_token_168|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128177": { + "content": "<|reserved_special_token_169|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128178": { + "content": "<|reserved_special_token_170|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128179": { + "content": "<|reserved_special_token_171|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128180": { + "content": "<|reserved_special_token_172|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128181": { + "content": "<|reserved_special_token_173|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128182": { + "content": "<|reserved_special_token_174|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128183": { + "content": "<|reserved_special_token_175|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128184": { + "content": "<|reserved_special_token_176|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128185": { + "content": "<|reserved_special_token_177|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128186": { + "content": "<|reserved_special_token_178|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128187": { + "content": "<|reserved_special_token_179|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128188": { + "content": "<|reserved_special_token_180|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128189": { + "content": "<|reserved_special_token_181|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128190": { + "content": "<|reserved_special_token_182|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128191": { + "content": "<|reserved_special_token_183|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128192": { + "content": "<|reserved_special_token_184|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128193": { + "content": "<|reserved_special_token_185|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128194": { + "content": "<|reserved_special_token_186|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128195": { + "content": "<|reserved_special_token_187|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128196": { + "content": "<|reserved_special_token_188|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128197": { + "content": "<|reserved_special_token_189|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128198": { + "content": "<|reserved_special_token_190|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128199": { + "content": "<|reserved_special_token_191|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128200": { + "content": "<|reserved_special_token_192|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128201": { + "content": "<|reserved_special_token_193|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128202": { + "content": "<|reserved_special_token_194|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128203": { + "content": "<|reserved_special_token_195|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128204": { + "content": "<|reserved_special_token_196|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128205": { + "content": "<|reserved_special_token_197|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128206": { + "content": "<|reserved_special_token_198|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128207": { + "content": "<|reserved_special_token_199|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128208": { + "content": "<|reserved_special_token_200|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128209": { + "content": "<|reserved_special_token_201|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128210": { + "content": "<|reserved_special_token_202|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128211": { + "content": "<|reserved_special_token_203|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128212": { + "content": "<|reserved_special_token_204|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128213": { + "content": "<|reserved_special_token_205|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128214": { + "content": "<|reserved_special_token_206|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128215": { + "content": "<|reserved_special_token_207|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128216": { + "content": "<|reserved_special_token_208|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128217": { + "content": "<|reserved_special_token_209|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128218": { + "content": "<|reserved_special_token_210|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128219": { + "content": "<|reserved_special_token_211|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128220": { + "content": "<|reserved_special_token_212|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128221": { + "content": "<|reserved_special_token_213|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128222": { + "content": "<|reserved_special_token_214|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128223": { + "content": "<|reserved_special_token_215|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128224": { + "content": "<|reserved_special_token_216|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128225": { + "content": "<|reserved_special_token_217|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128226": { + "content": "<|reserved_special_token_218|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128227": { + "content": "<|reserved_special_token_219|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128228": { + "content": "<|reserved_special_token_220|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128229": { + "content": "<|reserved_special_token_221|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128230": { + "content": "<|reserved_special_token_222|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128231": { + "content": "<|reserved_special_token_223|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128232": { + "content": "<|reserved_special_token_224|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128233": { + "content": "<|reserved_special_token_225|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128234": { + "content": "<|reserved_special_token_226|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128235": { + "content": "<|reserved_special_token_227|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128236": { + "content": "<|reserved_special_token_228|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128237": { + "content": "<|reserved_special_token_229|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128238": { + "content": "<|reserved_special_token_230|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128239": { + "content": "<|reserved_special_token_231|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128240": { + "content": "<|reserved_special_token_232|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128241": { + "content": "<|reserved_special_token_233|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128242": { + "content": "<|reserved_special_token_234|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128243": { + "content": "<|reserved_special_token_235|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128244": { + "content": "<|reserved_special_token_236|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128245": { + "content": "<|reserved_special_token_237|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128246": { + "content": "<|reserved_special_token_238|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128247": { + "content": "<|reserved_special_token_239|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128248": { + "content": "<|reserved_special_token_240|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128249": { + "content": "<|reserved_special_token_241|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128250": { + "content": "<|reserved_special_token_242|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128251": { + "content": "<|reserved_special_token_243|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128252": { + "content": "<|reserved_special_token_244|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128253": { + "content": "<|reserved_special_token_245|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128254": { + "content": "<|reserved_special_token_246|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128255": { + "content": "<|reserved_special_token_247|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + } + }, + "additional_special_tokens": [ + "<|eom_id|>" + ], + "bos_token": "<|begin_of_text|>", + "clean_up_tokenization_spaces": true, + "eos_token": "<|eot_id|>", + "extra_special_tokens": {}, + "model_input_names": [ + "input_ids", + "attention_mask" + ], + "model_max_length": 131072, + "pad_token": "<|eot_id|>", + "padding_side": "right", + "split_special_tokens": false, + "tokenizer_class": "PreTrainedTokenizerFast" +} diff --git a/train_results.json b/train_results.json new file mode 100644 index 0000000..cc1178b --- /dev/null +++ b/train_results.json @@ -0,0 +1,8 @@ +{ + "epoch": 1.0, + "total_flos": 1.761935585720664e+18, + "train_loss": 0.5203882457111775, + "train_runtime": 14354.8151, + "train_samples_per_second": 4.13, + "train_steps_per_second": 0.065 +} \ No newline at end of file diff --git a/trainer_log.jsonl b/trainer_log.jsonl new file mode 100644 index 0000000..d7c056e --- /dev/null +++ b/trainer_log.jsonl @@ -0,0 +1,96 @@ +{"current_steps": 10, "total_steps": 927, "loss": 0.6928, "accuracy": 0.40937501192092896, "lr": 4.8387096774193546e-08, "epoch": 0.010794764539198488, "percentage": 1.08, "elapsed_time": "0:02:19", "remaining_time": "3:33:40", "rewards/chosen": 0.0015822252025827765, "rewards/rejected": -0.0001372337428620085, "rewards/accuracies": 0.40937501192092896, "rewards/margins": 0.0017194593092426658, "logps/chosen": -328.8013610839844, "logps/rejected": -253.98362731933594, "logits/chosen": -1.4572813510894775, "logits/rejected": -1.5238107442855835} +{"current_steps": 20, "total_steps": 927, "loss": 0.6933, "accuracy": 0.5140625238418579, "lr": 1.0215053763440861e-07, "epoch": 0.021589529078396976, "percentage": 2.16, "elapsed_time": "0:05:11", "remaining_time": "3:55:06", "rewards/chosen": 0.0026884928811341524, "rewards/rejected": 0.0015687048435211182, "rewards/accuracies": 0.5140625238418579, "rewards/margins": 0.0011197883868589997, "logps/chosen": -329.26373291015625, "logps/rejected": -269.0686950683594, "logits/chosen": -1.4601737260818481, "logits/rejected": -1.495823860168457, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.434472680091858, "stability/repetition_rate_mean": 0.8257812261581421} +{"current_steps": 30, "total_steps": 927, "loss": 0.6925, "accuracy": 0.5140625238418579, "lr": 1.5591397849462365e-07, "epoch": 0.03238429361759547, "percentage": 3.24, "elapsed_time": "0:07:45", "remaining_time": "3:51:52", "rewards/chosen": 0.004414338618516922, "rewards/rejected": 0.0018770955502986908, "rewards/accuracies": 0.5140625238418579, "rewards/margins": 0.0025372428353875875, "logps/chosen": -316.17425537109375, "logps/rejected": -256.8540954589844, "logits/chosen": -1.4658056497573853, "logits/rejected": -1.5197511911392212, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.364843726158142, "stability/repetition_rate_mean": 0.8824218511581421} +{"current_steps": 40, "total_steps": 927, "loss": 0.6913, "accuracy": 0.550000011920929, "lr": 2.0967741935483871e-07, "epoch": 0.04317905815679395, "percentage": 4.31, "elapsed_time": "0:10:13", "remaining_time": "3:46:54", "rewards/chosen": 0.005997015163302422, "rewards/rejected": 0.0007881380734033883, "rewards/accuracies": 0.550000011920929, "rewards/margins": 0.005208877846598625, "logps/chosen": -329.3841247558594, "logps/rejected": -258.57672119140625, "logits/chosen": -1.4785693883895874, "logits/rejected": -1.5407034158706665, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.0068359375, "stability/repetition_rate_mean": 0.8031250238418579} +{"current_steps": 50, "total_steps": 927, "loss": 0.6885, "accuracy": 0.546875, "lr": 2.6344086021505376e-07, "epoch": 0.05397382269599244, "percentage": 5.39, "elapsed_time": "0:12:50", "remaining_time": "3:45:17", "rewards/chosen": 0.01573883555829525, "rewards/rejected": 0.005042524076998234, "rewards/accuracies": 0.546875, "rewards/margins": 0.010696313343942165, "logps/chosen": -313.481689453125, "logps/rejected": -258.3254089355469, "logits/chosen": -1.438301682472229, "logits/rejected": -1.503927230834961, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.07568359375, "stability/repetition_rate_mean": 0.8675781488418579} +{"current_steps": 60, "total_steps": 927, "loss": 0.6846, "accuracy": 0.604687511920929, "lr": 3.172043010752688e-07, "epoch": 0.06476858723519094, "percentage": 6.47, "elapsed_time": "0:15:12", "remaining_time": "3:39:41", "rewards/chosen": 0.02920054830610752, "rewards/rejected": 0.009999553672969341, "rewards/accuracies": 0.604687511920929, "rewards/margins": 0.019200993701815605, "logps/chosen": -318.685302734375, "logps/rejected": -265.6797180175781, "logits/chosen": -1.4596624374389648, "logits/rejected": -1.501914620399475, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.2527344226837158, "stability/repetition_rate_mean": 0.7318359613418579} +{"current_steps": 70, "total_steps": 927, "loss": 0.6787, "accuracy": 0.609375, "lr": 3.7096774193548384e-07, "epoch": 0.07556335177438941, "percentage": 7.55, "elapsed_time": "0:17:38", "remaining_time": "3:35:59", "rewards/chosen": 0.06427477300167084, "rewards/rejected": 0.03113069012761116, "rewards/accuracies": 0.609375, "rewards/margins": 0.03314407169818878, "logps/chosen": -339.0155334472656, "logps/rejected": -273.65655517578125, "logits/chosen": -1.5026830434799194, "logits/rejected": -1.5432065725326538, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.3330078125, "stability/repetition_rate_mean": 0.8822265863418579} +{"current_steps": 80, "total_steps": 927, "loss": 0.6616, "accuracy": 0.643750011920929, "lr": 4.247311827956989e-07, "epoch": 0.0863581163135879, "percentage": 8.63, "elapsed_time": "0:20:03", "remaining_time": "3:32:19", "rewards/chosen": 0.1002170592546463, "rewards/rejected": 0.028648091480135918, "rewards/accuracies": 0.643750011920929, "rewards/margins": 0.07156896591186523, "logps/chosen": -325.33526611328125, "logps/rejected": -254.3518524169922, "logits/chosen": -1.4859027862548828, "logits/rejected": -1.5006340742111206, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.825048804283142, "stability/repetition_rate_mean": 0.8583984375} +{"current_steps": 90, "total_steps": 927, "loss": 0.6497, "accuracy": 0.6953125, "lr": 4.78494623655914e-07, "epoch": 0.0971528808527864, "percentage": 9.71, "elapsed_time": "0:22:27", "remaining_time": "3:28:53", "rewards/chosen": 0.14759615063667297, "rewards/rejected": 0.04552074521780014, "rewards/accuracies": 0.6953125, "rewards/margins": 0.10207539796829224, "logps/chosen": -295.8207702636719, "logps/rejected": -248.85952758789062, "logits/chosen": -1.4689861536026, "logits/rejected": -1.4905648231506348, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.663671851158142, "stability/repetition_rate_mean": 0.8740234375} +{"current_steps": 100, "total_steps": 927, "loss": 0.6413, "accuracy": 0.6890625357627869, "lr": 4.999361498869529e-07, "epoch": 0.10794764539198488, "percentage": 10.79, "elapsed_time": "0:24:49", "remaining_time": "3:25:18", "rewards/chosen": 0.19397814571857452, "rewards/rejected": 0.06464159488677979, "rewards/accuracies": 0.6890625357627869, "rewards/margins": 0.12933655083179474, "logps/chosen": -314.435791015625, "logps/rejected": -249.51695251464844, "logits/chosen": -1.4919625520706177, "logits/rejected": -1.5506508350372314, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.4281249046325684, "stability/repetition_rate_mean": 0.9400390386581421} +{"current_steps": 110, "total_steps": 927, "loss": 0.6214, "accuracy": 0.714062511920929, "lr": 4.995460728562402e-07, "epoch": 0.11874240993118337, "percentage": 11.87, "elapsed_time": "0:27:12", "remaining_time": "3:22:04", "rewards/chosen": 0.24892178177833557, "rewards/rejected": 0.06499166041612625, "rewards/accuracies": 0.714062511920929, "rewards/margins": 0.18393009901046753, "logps/chosen": -319.29156494140625, "logps/rejected": -253.4399871826172, "logits/chosen": -1.4327154159545898, "logits/rejected": -1.5077978372573853, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.246875047683716, "stability/repetition_rate_mean": 0.809374988079071} +{"current_steps": 120, "total_steps": 927, "loss": 0.6032, "accuracy": 0.739062488079071, "lr": 4.988019438437758e-07, "epoch": 0.12953717447038188, "percentage": 12.94, "elapsed_time": "0:29:35", "remaining_time": "3:18:59", "rewards/chosen": 0.3554464876651764, "rewards/rejected": 0.1081392914056778, "rewards/accuracies": 0.739062488079071, "rewards/margins": 0.2473072111606598, "logps/chosen": -330.7845764160156, "logps/rejected": -248.1776885986328, "logits/chosen": -1.4564826488494873, "logits/rejected": -1.5484386682510376, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.070214867591858, "stability/repetition_rate_mean": 0.7470703125} +{"current_steps": 130, "total_steps": 927, "loss": 0.5951, "accuracy": 0.721875011920929, "lr": 4.977048186079155e-07, "epoch": 0.14033193900958035, "percentage": 14.02, "elapsed_time": "0:31:58", "remaining_time": "3:16:00", "rewards/chosen": 0.40177080035209656, "rewards/rejected": 0.11879038065671921, "rewards/accuracies": 0.721875011920929, "rewards/margins": 0.28298041224479675, "logps/chosen": -317.5703125, "logps/rejected": -253.7754364013672, "logits/chosen": -1.4577782154083252, "logits/rejected": -1.508943796157837, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.4833984375, "stability/repetition_rate_mean": 0.773242175579071} +{"current_steps": 140, "total_steps": 927, "loss": 0.6036, "accuracy": 0.6890625357627869, "lr": 4.962562537324176e-07, "epoch": 0.15112670354877883, "percentage": 15.1, "elapsed_time": "0:34:25", "remaining_time": "3:13:31", "rewards/chosen": 0.42533954977989197, "rewards/rejected": 0.1358480602502823, "rewards/accuracies": 0.6890625357627869, "rewards/margins": 0.2894915044307709, "logps/chosen": -343.68548583984375, "logps/rejected": -272.2403869628906, "logits/chosen": -1.4774430990219116, "logits/rejected": -1.512833833694458, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.019140601158142, "stability/repetition_rate_mean": 0.8072265386581421} +{"current_steps": 150, "total_steps": 927, "loss": 0.6074, "accuracy": 0.6968750357627869, "lr": 4.944583044179871e-07, "epoch": 0.16192146808797733, "percentage": 16.18, "elapsed_time": "0:36:48", "remaining_time": "3:10:40", "rewards/chosen": 0.412137508392334, "rewards/rejected": 0.13995173573493958, "rewards/accuracies": 0.6968750357627869, "rewards/margins": 0.2721858024597168, "logps/chosen": -320.7796936035156, "logps/rejected": -268.3492126464844, "logits/chosen": -1.4802706241607666, "logits/rejected": -1.5120983123779297, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.5673828125, "stability/repetition_rate_mean": 0.807421863079071} +{"current_steps": 160, "total_steps": 927, "loss": 0.5807, "accuracy": 0.7484375238418579, "lr": 4.923135215663896e-07, "epoch": 0.1727162326271758, "percentage": 17.26, "elapsed_time": "0:39:12", "remaining_time": "3:07:56", "rewards/chosen": 0.46426326036453247, "rewards/rejected": 0.09919857233762741, "rewards/accuracies": 0.7484375238418579, "rewards/margins": 0.3650646209716797, "logps/chosen": -317.5917663574219, "logps/rejected": -243.84231567382812, "logits/chosen": -1.479994773864746, "logits/rejected": -1.5399045944213867, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.4421875476837158, "stability/repetition_rate_mean": 0.789257824420929} +{"current_steps": 170, "total_steps": 927, "loss": 0.5752, "accuracy": 0.706250011920929, "lr": 4.89824948161273e-07, "epoch": 0.1835109971663743, "percentage": 18.34, "elapsed_time": "0:41:34", "remaining_time": "3:05:06", "rewards/chosen": 0.47893524169921875, "rewards/rejected": 0.08635219186544418, "rewards/accuracies": 0.706250011920929, "rewards/margins": 0.39258310198783875, "logps/chosen": -308.2352600097656, "logps/rejected": -256.36358642578125, "logits/chosen": -1.4407405853271484, "logits/rejected": -1.5115913152694702, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.5763671398162842, "stability/repetition_rate_mean": 0.7845703363418579} +{"current_steps": 180, "total_steps": 927, "loss": 0.5744, "accuracy": 0.7109375, "lr": 4.8699611495083e-07, "epoch": 0.1943057617055728, "percentage": 19.42, "elapsed_time": "0:43:58", "remaining_time": "3:02:31", "rewards/chosen": 0.5145285725593567, "rewards/rejected": 0.10545291751623154, "rewards/accuracies": 0.7109375, "rewards/margins": 0.40907564759254456, "logps/chosen": -317.1926574707031, "logps/rejected": -261.8941650390625, "logits/chosen": -1.504378318786621, "logits/rejected": -1.5372484922409058, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.5693359375, "stability/repetition_rate_mean": 0.7490234375} +{"current_steps": 190, "total_steps": 927, "loss": 0.5629, "accuracy": 0.707812488079071, "lr": 4.838310354384302e-07, "epoch": 0.2051005262447713, "percentage": 20.5, "elapsed_time": "0:46:25", "remaining_time": "3:00:05", "rewards/chosen": 0.5523476600646973, "rewards/rejected": 0.11809053272008896, "rewards/accuracies": 0.707812488079071, "rewards/margins": 0.4342571198940277, "logps/chosen": -307.32684326171875, "logps/rejected": -263.76373291015625, "logits/chosen": -1.4963879585266113, "logits/rejected": -1.5239351987838745, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.1296875476837158, "stability/repetition_rate_mean": 0.850781261920929} +{"current_steps": 200, "total_steps": 927, "loss": 0.5524, "accuracy": 0.745312511920929, "lr": 4.803342001883246e-07, "epoch": 0.21589529078396977, "percentage": 21.57, "elapsed_time": "0:48:54", "remaining_time": "2:57:45", "rewards/chosen": 0.556470513343811, "rewards/rejected": 0.09783537685871124, "rewards/accuracies": 0.745312511920929, "rewards/margins": 0.4586350917816162, "logps/chosen": -318.7608337402344, "logps/rejected": -267.5777282714844, "logits/chosen": -1.5078216791152954, "logits/rejected": -1.541197419166565, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.4445312023162842, "stability/repetition_rate_mean": 0.796679675579071} +{"current_steps": 210, "total_steps": 927, "loss": 0.5515, "accuracy": 0.7484375238418579, "lr": 4.7651057045450515e-07, "epoch": 0.22669005532316827, "percentage": 22.65, "elapsed_time": "0:51:13", "remaining_time": "2:54:54", "rewards/chosen": 0.5690556764602661, "rewards/rejected": 0.10906264930963516, "rewards/accuracies": 0.7484375238418579, "rewards/margins": 0.4599929749965668, "logps/chosen": -326.5751647949219, "logps/rejected": -245.41970825195312, "logits/chosen": -1.4529699087142944, "logits/rejected": -1.5274174213409424, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.3254883289337158, "stability/repetition_rate_mean": 0.81640625} +{"current_steps": 220, "total_steps": 927, "loss": 0.5548, "accuracy": 0.746874988079071, "lr": 4.72365571141757e-07, "epoch": 0.23748481986236675, "percentage": 23.73, "elapsed_time": "0:53:36", "remaining_time": "2:52:17", "rewards/chosen": 0.5794717669487, "rewards/rejected": 0.08195456117391586, "rewards/accuracies": 0.746874988079071, "rewards/margins": 0.4975171983242035, "logps/chosen": -331.7127380371094, "logps/rejected": -264.9964294433594, "logits/chosen": -1.4564087390899658, "logits/rejected": -1.4975181818008423, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.763671875, "stability/repetition_rate_mean": 0.7367187738418579} +{"current_steps": 230, "total_steps": 927, "loss": 0.5575, "accuracy": 0.7359375357627869, "lr": 4.6790508310889007e-07, "epoch": 0.24827958440156525, "percentage": 24.81, "elapsed_time": "0:55:53", "remaining_time": "2:49:23", "rewards/chosen": 0.5666539072990417, "rewards/rejected": 0.07812191545963287, "rewards/accuracies": 0.7359375357627869, "rewards/margins": 0.48853203654289246, "logps/chosen": -311.7873229980469, "logps/rejected": -257.8661193847656, "logits/chosen": -1.4929759502410889, "logits/rejected": -1.5188223123550415, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.4400391578674316, "stability/repetition_rate_mean": 0.8841797113418579} +{"current_steps": 240, "total_steps": 927, "loss": 0.5496, "accuracy": 0.7281250357627869, "lr": 4.6313543482507056e-07, "epoch": 0.25907434894076375, "percentage": 25.89, "elapsed_time": "0:58:12", "remaining_time": "2:46:38", "rewards/chosen": 0.5762147307395935, "rewards/rejected": 0.05319035053253174, "rewards/accuracies": 0.7281250357627869, "rewards/margins": 0.5230244398117065, "logps/chosen": -319.4496154785156, "logps/rejected": -261.7314453125, "logits/chosen": -1.4668247699737549, "logits/rejected": -1.50505530834198, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.0635743141174316, "stability/repetition_rate_mean": 0.802539050579071} +{"current_steps": 250, "total_steps": 927, "loss": 0.5612, "accuracy": 0.723437488079071, "lr": 4.580633933910901e-07, "epoch": 0.26986911347996223, "percentage": 26.97, "elapsed_time": "1:00:37", "remaining_time": "2:44:10", "rewards/chosen": 0.5559987425804138, "rewards/rejected": 0.0560583770275116, "rewards/accuracies": 0.723437488079071, "rewards/margins": 0.4999403655529022, "logps/chosen": -305.2557678222656, "logps/rejected": -253.59902954101562, "logits/chosen": -1.436219334602356, "logits/rejected": -1.46418035030365, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.45166015625, "stability/repetition_rate_mean": 0.811718761920929} +{"current_steps": 260, "total_steps": 927, "loss": 0.5574, "accuracy": 0.7203125357627869, "lr": 4.526961549383108e-07, "epoch": 0.2806638780191607, "percentage": 28.05, "elapsed_time": "1:03:04", "remaining_time": "2:41:47", "rewards/chosen": 0.6053926348686218, "rewards/rejected": 0.08161897957324982, "rewards/accuracies": 0.7203125357627869, "rewards/margins": 0.5237736105918884, "logps/chosen": -325.4045104980469, "logps/rejected": -272.9486389160156, "logits/chosen": -1.4230726957321167, "logits/rejected": -1.4305095672607422, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.894628882408142, "stability/repetition_rate_mean": 0.813281238079071} +{"current_steps": 270, "total_steps": 927, "loss": 0.5356, "accuracy": 0.7437500357627869, "lr": 4.470413344189098e-07, "epoch": 0.2914586425583592, "percentage": 29.13, "elapsed_time": "1:05:33", "remaining_time": "2:39:32", "rewards/chosen": 0.6630539894104004, "rewards/rejected": 0.06447024643421173, "rewards/accuracies": 0.7437500357627869, "rewards/margins": 0.5985837578773499, "logps/chosen": -323.3600158691406, "logps/rejected": -270.2887878417969, "logits/chosen": -1.4393119812011719, "logits/rejected": -1.467215895652771, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.030859351158142, "stability/repetition_rate_mean": 0.828906238079071} +{"current_steps": 280, "total_steps": 927, "loss": 0.5221, "accuracy": 0.7671875357627869, "lr": 4.4110695480190597e-07, "epoch": 0.30225340709755766, "percentage": 30.2, "elapsed_time": "1:07:58", "remaining_time": "2:37:03", "rewards/chosen": 0.7377834916114807, "rewards/rejected": 0.10894794762134552, "rewards/accuracies": 0.7671875357627869, "rewards/margins": 0.6288355588912964, "logps/chosen": -330.3580627441406, "logps/rejected": -267.19561767578125, "logits/chosen": -1.4905976057052612, "logits/rejected": -1.5187627077102661, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.202734351158142, "stability/repetition_rate_mean": 0.8851562738418579} +{"current_steps": 290, "total_steps": 927, "loss": 0.5299, "accuracy": 0.746874988079071, "lr": 4.3490143569030017e-07, "epoch": 0.3130481716367562, "percentage": 31.28, "elapsed_time": "1:10:21", "remaining_time": "2:34:33", "rewards/chosen": 0.6983198523521423, "rewards/rejected": 0.10521648079156876, "rewards/accuracies": 0.746874988079071, "rewards/margins": 0.5931033492088318, "logps/chosen": -320.11309814453125, "logps/rejected": -252.4005584716797, "logits/chosen": -1.4678796529769897, "logits/rejected": -1.5179208517074585, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.6193358898162842, "stability/repetition_rate_mean": 0.8099609613418579} +{"current_steps": 300, "total_steps": 927, "loss": 0.5031, "accuracy": 0.770312488079071, "lr": 4.284335813754769e-07, "epoch": 0.32384293617595467, "percentage": 32.36, "elapsed_time": "1:12:46", "remaining_time": "2:32:06", "rewards/chosen": 0.6781904101371765, "rewards/rejected": 9.752810001373291e-06, "rewards/accuracies": 0.770312488079071, "rewards/margins": 0.6781806349754333, "logps/chosen": -321.5018005371094, "logps/rejected": -276.88409423828125, "logits/chosen": -1.4394444227218628, "logits/rejected": -1.4822733402252197, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.1236329078674316, "stability/repetition_rate_mean": 0.7289062738418579} +{"current_steps": 300, "total_steps": 927, "eval_loss": 0.513998806476593, "epoch": 0.32384293617595467, "percentage": 32.36, "elapsed_time": "1:17:19", "remaining_time": "2:41:35"} +{"current_steps": 310, "total_steps": 927, "loss": 0.534, "accuracy": 0.75, "lr": 4.217125683458161e-07, "epoch": 0.33463770071515314, "percentage": 33.44, "elapsed_time": "1:19:45", "remaining_time": "2:38:45", "rewards/chosen": 0.6554938554763794, "rewards/rejected": 0.0268485676497221, "rewards/accuracies": 0.75, "rewards/margins": 0.6286452412605286, "logps/chosen": -315.331298828125, "logps/rejected": -258.9646911621094, "logits/chosen": -1.4233049154281616, "logits/rejected": -1.452370285987854, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 0.908203125, "stability/repetition_rate_mean": 0.799023449420929} +{"current_steps": 320, "total_steps": 927, "loss": 0.5117, "accuracy": 0.760937511920929, "lr": 4.1474793226723825e-07, "epoch": 0.3454324652543516, "percentage": 34.52, "elapsed_time": "1:22:15", "remaining_time": "2:36:02", "rewards/chosen": 0.7362013459205627, "rewards/rejected": 0.048347149044275284, "rewards/accuracies": 0.760937511920929, "rewards/margins": 0.6878542304039001, "logps/chosen": -327.7336120605469, "logps/rejected": -262.0153503417969, "logits/chosen": -1.448975682258606, "logits/rejected": -1.4607841968536377, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.083886742591858, "stability/repetition_rate_mean": 0.9072265625} +{"current_steps": 330, "total_steps": 927, "loss": 0.4903, "accuracy": 0.7562500238418579, "lr": 4.0754955445415396e-07, "epoch": 0.35622722979355015, "percentage": 35.6, "elapsed_time": "1:24:37", "remaining_time": "2:33:05", "rewards/chosen": 0.7997223734855652, "rewards/rejected": 0.012823845259845257, "rewards/accuracies": 0.7562500238418579, "rewards/margins": 0.7868985533714294, "logps/chosen": -330.9326477050781, "logps/rejected": -256.48638916015625, "logits/chosen": -1.447295069694519, "logits/rejected": -1.47311270236969, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.7205078601837158, "stability/repetition_rate_mean": 0.955273449420929} +{"current_steps": 340, "total_steps": 927, "loss": 0.4981, "accuracy": 0.770312488079071, "lr": 4.001276478500126e-07, "epoch": 0.3670219943327486, "percentage": 36.68, "elapsed_time": "1:27:04", "remaining_time": "2:30:19", "rewards/chosen": 0.7650503516197205, "rewards/rejected": 0.026440534740686417, "rewards/accuracies": 0.770312488079071, "rewards/margins": 0.738609790802002, "logps/chosen": -316.4836120605469, "logps/rejected": -258.7716064453125, "logits/chosen": -1.4461034536361694, "logits/rejected": -1.4699530601501465, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.8572266101837158, "stability/repetition_rate_mean": 0.7232421636581421} +{"current_steps": 350, "total_steps": 927, "loss": 0.5247, "accuracy": 0.7359375357627869, "lr": 3.9249274253734164e-07, "epoch": 0.3778167588719471, "percentage": 37.76, "elapsed_time": "1:29:29", "remaining_time": "2:27:32", "rewards/chosen": 0.7249447107315063, "rewards/rejected": 0.012191593647003174, "rewards/accuracies": 0.7359375357627869, "rewards/margins": 0.712753176689148, "logps/chosen": -314.6985778808594, "logps/rejected": -269.089599609375, "logits/chosen": -1.4219696521759033, "logits/rejected": -1.4259979724884033, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.2517578601837158, "stability/repetition_rate_mean": 0.76953125} +{"current_steps": 360, "total_steps": 927, "loss": 0.5044, "accuracy": 0.7515625357627869, "lr": 3.846556707978337e-07, "epoch": 0.3886115234111456, "percentage": 38.83, "elapsed_time": "1:31:53", "remaining_time": "2:24:43", "rewards/chosen": 0.8103561401367188, "rewards/rejected": 0.039548713713884354, "rewards/accuracies": 0.7515625357627869, "rewards/margins": 0.7708074450492859, "logps/chosen": -334.6982727050781, "logps/rejected": -252.6654815673828, "logits/chosen": -1.427175760269165, "logits/rejected": -1.461297869682312, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.2664062976837158, "stability/repetition_rate_mean": 0.889843761920929} +{"current_steps": 370, "total_steps": 927, "loss": 0.4983, "accuracy": 0.729687511920929, "lr": 3.766275517436779e-07, "epoch": 0.3994062879503441, "percentage": 39.91, "elapsed_time": "1:34:19", "remaining_time": "2:21:59", "rewards/chosen": 0.7894806861877441, "rewards/rejected": 0.03071962669491768, "rewards/accuracies": 0.729687511920929, "rewards/margins": 0.7587611079216003, "logps/chosen": -319.5567321777344, "logps/rejected": -254.91746520996094, "logits/chosen": -1.3873792886734009, "logits/rejected": -1.3985546827316284, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.752539038658142, "stability/repetition_rate_mean": 0.777148425579071} +{"current_steps": 380, "total_steps": 927, "loss": 0.5001, "accuracy": 0.7593750357627869, "lr": 3.684197755419419e-07, "epoch": 0.4102010524895426, "percentage": 40.99, "elapsed_time": "1:36:43", "remaining_time": "2:19:14", "rewards/chosen": 0.7916366457939148, "rewards/rejected": 0.01186272781342268, "rewards/accuracies": 0.7593750357627869, "rewards/margins": 0.7797738909721375, "logps/chosen": -306.7962341308594, "logps/rejected": -258.84234619140625, "logits/chosen": -1.4125322103500366, "logits/rejected": -1.417395830154419, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.844921827316284, "stability/repetition_rate_mean": 0.7945312261581421} +{"current_steps": 390, "total_steps": 927, "loss": 0.4952, "accuracy": 0.765625, "lr": 3.60043987254384e-07, "epoch": 0.42099581702874106, "percentage": 42.07, "elapsed_time": "1:39:06", "remaining_time": "2:16:27", "rewards/chosen": 0.8086903691291809, "rewards/rejected": -0.04293971136212349, "rewards/accuracies": 0.765625, "rewards/margins": 0.8516300320625305, "logps/chosen": -316.85101318359375, "logps/rejected": -264.2350769042969, "logits/chosen": -1.425724983215332, "logits/rejected": -1.4372109174728394, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.869531273841858, "stability/repetition_rate_mean": 0.74609375} +{"current_steps": 400, "total_steps": 927, "loss": 0.5137, "accuracy": 0.776562511920929, "lr": 3.5151207031562633e-07, "epoch": 0.43179058156793954, "percentage": 43.15, "elapsed_time": "1:41:29", "remaining_time": "2:13:43", "rewards/chosen": 0.7608602046966553, "rewards/rejected": -0.023676123470067978, "rewards/accuracies": 0.776562511920929, "rewards/margins": 0.7845363020896912, "logps/chosen": -310.2779235839844, "logps/rejected": -268.259033203125, "logits/chosen": -1.3795498609542847, "logits/rejected": -1.3812373876571655, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.6525390148162842, "stability/repetition_rate_mean": 0.7679687738418579} +{"current_steps": 410, "total_steps": 927, "loss": 0.5069, "accuracy": 0.760937511920929, "lr": 3.4283612967312687e-07, "epoch": 0.442585346107138, "percentage": 44.23, "elapsed_time": "1:43:55", "remaining_time": "2:11:03", "rewards/chosen": 0.7829875349998474, "rewards/rejected": -0.021388515830039978, "rewards/accuracies": 0.760937511920929, "rewards/margins": 0.8043760657310486, "logps/chosen": -313.1993103027344, "logps/rejected": -250.6515655517578, "logits/chosen": -1.3496493101119995, "logits/rejected": -1.3831802606582642, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.6925780773162842, "stability/repetition_rate_mean": 0.854296863079071} +{"current_steps": 420, "total_steps": 927, "loss": 0.5122, "accuracy": 0.737500011920929, "lr": 3.34028474612874e-07, "epoch": 0.45338011064633654, "percentage": 45.31, "elapsed_time": "1:46:17", "remaining_time": "2:08:18", "rewards/chosen": 0.7716613411903381, "rewards/rejected": -0.07191526889801025, "rewards/accuracies": 0.737500011920929, "rewards/margins": 0.8435766100883484, "logps/chosen": -299.86065673828125, "logps/rejected": -261.5897521972656, "logits/chosen": -1.3803904056549072, "logits/rejected": -1.394149661064148, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.1460938453674316, "stability/repetition_rate_mean": 0.822460949420929} +{"current_steps": 430, "total_steps": 927, "loss": 0.4937, "accuracy": 0.768750011920929, "lr": 3.2510160129516775e-07, "epoch": 0.464174875185535, "percentage": 46.39, "elapsed_time": "1:48:35", "remaining_time": "2:05:30", "rewards/chosen": 0.8203991055488586, "rewards/rejected": -0.07847942411899567, "rewards/accuracies": 0.768750011920929, "rewards/margins": 0.8988785147666931, "logps/chosen": -319.5307922363281, "logps/rejected": -265.67938232421875, "logits/chosen": -1.3800678253173828, "logits/rejected": -1.3930643796920776, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.808789014816284, "stability/repetition_rate_mean": 0.78125} +{"current_steps": 440, "total_steps": 927, "loss": 0.4891, "accuracy": 0.792187511920929, "lr": 3.1606817502526736e-07, "epoch": 0.4749696397247335, "percentage": 47.46, "elapsed_time": "1:50:53", "remaining_time": "2:02:44", "rewards/chosen": 0.8151880502700806, "rewards/rejected": -0.05617132410407066, "rewards/accuracies": 0.792187511920929, "rewards/margins": 0.8713592886924744, "logps/chosen": -326.2301330566406, "logps/rejected": -256.16412353515625, "logits/chosen": -1.3767389059066772, "logits/rejected": -1.4001781940460205, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.164990186691284, "stability/repetition_rate_mean": 0.8707031011581421} +{"current_steps": 450, "total_steps": 927, "loss": 0.4817, "accuracy": 0.7890625, "lr": 3.069410122840585e-07, "epoch": 0.48576440426393197, "percentage": 48.54, "elapsed_time": "1:53:16", "remaining_time": "2:00:04", "rewards/chosen": 0.8885055780410767, "rewards/rejected": -0.03621084615588188, "rewards/accuracies": 0.7890625, "rewards/margins": 0.924716591835022, "logps/chosen": -318.3290100097656, "logps/rejected": -268.3873596191406, "logits/chosen": -1.372667670249939, "logits/rejected": -1.4003467559814453, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.7429687976837158, "stability/repetition_rate_mean": 0.8236328363418579} +{"current_steps": 460, "total_steps": 927, "loss": 0.4832, "accuracy": 0.7718750238418579, "lr": 2.9773306254423513e-07, "epoch": 0.4965591688031305, "percentage": 49.62, "elapsed_time": "1:55:38", "remaining_time": "1:57:23", "rewards/chosen": 0.853641152381897, "rewards/rejected": -0.016610044986009598, "rewards/accuracies": 0.7718750238418579, "rewards/margins": 0.8702511191368103, "logps/chosen": -294.7362976074219, "logps/rejected": -240.1558074951172, "logits/chosen": -1.3681141138076782, "logits/rejected": -1.3875712156295776, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.7371094226837158, "stability/repetition_rate_mean": 0.8646484613418579} +{"current_steps": 470, "total_steps": 927, "loss": 0.4801, "accuracy": 0.7593750357627869, "lr": 2.884573898977941e-07, "epoch": 0.5073539333423289, "percentage": 50.7, "elapsed_time": "1:58:03", "remaining_time": "1:54:47", "rewards/chosen": 0.8505555391311646, "rewards/rejected": -0.04154070094227791, "rewards/accuracies": 0.7593750357627869, "rewards/margins": 0.8920961618423462, "logps/chosen": -308.7089538574219, "logps/rejected": -268.0931091308594, "logits/chosen": -1.388026237487793, "logits/rejected": -1.3998411893844604, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.244531273841858, "stability/repetition_rate_mean": 0.8687499761581421} +{"current_steps": 480, "total_steps": 927, "loss": 0.4827, "accuracy": 0.7890625, "lr": 2.791271545209101e-07, "epoch": 0.5181486978815275, "percentage": 51.78, "elapsed_time": "2:00:30", "remaining_time": "1:52:13", "rewards/chosen": 0.8823606371879578, "rewards/rejected": 0.021032243967056274, "rewards/accuracies": 0.7890625, "rewards/margins": 0.8613284230232239, "logps/chosen": -294.66412353515625, "logps/rejected": -248.6920928955078, "logits/chosen": -1.3824865818023682, "logits/rejected": -1.4162545204162598, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.1624999046325684, "stability/repetition_rate_mean": 0.8519531488418579} +{"current_steps": 490, "total_steps": 927, "loss": 0.4647, "accuracy": 0.792187511920929, "lr": 2.697555940024887e-07, "epoch": 0.528943462420726, "percentage": 52.86, "elapsed_time": "2:02:55", "remaining_time": "1:49:37", "rewards/chosen": 0.9351348280906677, "rewards/rejected": -0.035314515233039856, "rewards/accuracies": 0.792187511920929, "rewards/margins": 0.9704492688179016, "logps/chosen": -303.913330078125, "logps/rejected": -242.33706665039062, "logits/chosen": -1.3622970581054688, "logits/rejected": -1.3937467336654663, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.9038817882537842, "stability/repetition_rate_mean": 0.8125} +{"current_steps": 500, "total_steps": 927, "loss": 0.482, "accuracy": 0.7828125357627869, "lr": 2.603560045628857e-07, "epoch": 0.5397382269599245, "percentage": 53.94, "elapsed_time": "2:05:22", "remaining_time": "1:47:03", "rewards/chosen": 0.9495781064033508, "rewards/rejected": -0.016795417293906212, "rewards/accuracies": 0.7828125357627869, "rewards/margins": 0.9663735628128052, "logps/chosen": -314.1101989746094, "logps/rejected": -261.1115417480469, "logits/chosen": -1.3485071659088135, "logits/rejected": -1.3485997915267944, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.1546874046325684, "stability/repetition_rate_mean": 0.7855468988418579} +{"current_steps": 510, "total_steps": 927, "loss": 0.4861, "accuracy": 0.796875, "lr": 2.509417221894427e-07, "epoch": 0.5505329914991229, "percentage": 55.02, "elapsed_time": "2:07:46", "remaining_time": "1:44:28", "rewards/chosen": 0.9477736353874207, "rewards/rejected": 0.007596464361995459, "rewards/accuracies": 0.796875, "rewards/margins": 0.9401771426200867, "logps/chosen": -307.50494384765625, "logps/rejected": -269.51959228515625, "logits/chosen": -1.3849689960479736, "logits/rejected": -1.3808684349060059, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.330175757408142, "stability/repetition_rate_mean": 0.8619140386581421} +{"current_steps": 520, "total_steps": 927, "loss": 0.4896, "accuracy": 0.765625, "lr": 2.4152610371560093e-07, "epoch": 0.5613277560383214, "percentage": 56.09, "elapsed_time": "2:10:12", "remaining_time": "1:41:55", "rewards/chosen": 0.9386131167411804, "rewards/rejected": 0.06416996568441391, "rewards/accuracies": 0.765625, "rewards/margins": 0.8744432330131531, "logps/chosen": -308.14276123046875, "logps/rejected": -257.72283935546875, "logits/chosen": -1.4082396030426025, "logits/rejected": -1.4073408842086792, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.715429663658142, "stability/repetition_rate_mean": 0.856640636920929} +{"current_steps": 530, "total_steps": 927, "loss": 0.4874, "accuracy": 0.7562500238418579, "lr": 2.321225078704399e-07, "epoch": 0.5721225205775199, "percentage": 57.17, "elapsed_time": "2:12:36", "remaining_time": "1:39:19", "rewards/chosen": 1.0152686834335327, "rewards/rejected": 0.1395503580570221, "rewards/accuracies": 0.7562500238418579, "rewards/margins": 0.8757182955741882, "logps/chosen": -317.8136291503906, "logps/rejected": -260.39678955078125, "logits/chosen": -1.4284799098968506, "logits/rejected": -1.4444469213485718, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.365820288658142, "stability/repetition_rate_mean": 0.7701171636581421} +{"current_steps": 540, "total_steps": 927, "loss": 0.4931, "accuracy": 0.7734375, "lr": 2.2274427632552503e-07, "epoch": 0.5829172851167184, "percentage": 58.25, "elapsed_time": "2:14:57", "remaining_time": "1:36:43", "rewards/chosen": 0.9857921600341797, "rewards/rejected": 0.1031401976943016, "rewards/accuracies": 0.7734375, "rewards/margins": 0.8826519250869751, "logps/chosen": -302.94537353515625, "logps/rejected": -262.5538635253906, "logits/chosen": -1.4013619422912598, "logits/rejected": -1.405015468597412, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.7644531726837158, "stability/repetition_rate_mean": 0.8062499761581421} +{"current_steps": 550, "total_steps": 927, "loss": 0.4744, "accuracy": 0.7671875357627869, "lr": 2.134047147659583e-07, "epoch": 0.5937120496559168, "percentage": 59.33, "elapsed_time": "2:17:23", "remaining_time": "1:34:10", "rewards/chosen": 1.062072992324829, "rewards/rejected": 0.140531525015831, "rewards/accuracies": 0.7671875357627869, "rewards/margins": 0.9215413928031921, "logps/chosen": -309.70013427734375, "logps/rejected": -264.7682189941406, "logits/chosen": -1.3965346813201904, "logits/rejected": -1.3893383741378784, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.9962890148162842, "stability/repetition_rate_mean": 0.8472656011581421} +{"current_steps": 560, "total_steps": 927, "loss": 0.5088, "accuracy": 0.7328125238418579, "lr": 2.0411707401248403e-07, "epoch": 0.6045068141951153, "percentage": 60.41, "elapsed_time": "2:19:50", "remaining_time": "1:31:38", "rewards/chosen": 1.0473458766937256, "rewards/rejected": 0.2058195173740387, "rewards/accuracies": 0.7328125238418579, "rewards/margins": 0.841526210308075, "logps/chosen": -310.02789306640625, "logps/rejected": -263.0741882324219, "logits/chosen": -1.4111377000808716, "logits/rejected": -1.4183025360107422, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.4849610328674316, "stability/repetition_rate_mean": 0.784960925579071} +{"current_steps": 570, "total_steps": 927, "loss": 0.4437, "accuracy": 0.793749988079071, "lr": 1.9489453122143603e-07, "epoch": 0.6153015787343139, "percentage": 61.49, "elapsed_time": "2:22:14", "remaining_time": "1:29:05", "rewards/chosen": 1.1061866283416748, "rewards/rejected": 0.11313938349485397, "rewards/accuracies": 0.793749988079071, "rewards/margins": 0.9930472373962402, "logps/chosen": -312.1006164550781, "logps/rejected": -254.21788024902344, "logits/chosen": -1.4051156044006348, "logits/rejected": -1.4276247024536133, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 0.817578136920929, "stability/repetition_rate_mean": 0.828906238079071} +{"current_steps": 580, "total_steps": 927, "loss": 0.5064, "accuracy": 0.746874988079071, "lr": 1.8575017118919928e-07, "epoch": 0.6260963432735124, "percentage": 62.57, "elapsed_time": "2:24:44", "remaining_time": "1:26:35", "rewards/chosen": 0.9926168322563171, "rewards/rejected": 0.16463755071163177, "rewards/accuracies": 0.746874988079071, "rewards/margins": 0.8279793858528137, "logps/chosen": -319.3863830566406, "logps/rejected": -252.8662109375, "logits/chosen": -1.4090861082077026, "logits/rejected": -1.4279987812042236, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.6736328601837158, "stability/repetition_rate_mean": 0.7662109136581421} +{"current_steps": 590, "total_steps": 927, "loss": 0.4494, "accuracy": 0.800000011920929, "lr": 1.7669696778770938e-07, "epoch": 0.6368911078127109, "percentage": 63.65, "elapsed_time": "2:27:04", "remaining_time": "1:24:00", "rewards/chosen": 1.0922644138336182, "rewards/rejected": 0.08526992052793503, "rewards/accuracies": 0.800000011920929, "rewards/margins": 1.006994605064392, "logps/chosen": -316.9762268066406, "logps/rejected": -245.96548461914062, "logits/chosen": -1.4007326364517212, "logits/rejected": -1.4263814687728882, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.351171851158142, "stability/repetition_rate_mean": 0.8466796875} +{"current_steps": 600, "total_steps": 927, "loss": 0.479, "accuracy": 0.768750011920929, "lr": 1.6774776555733028e-07, "epoch": 0.6476858723519093, "percentage": 64.72, "elapsed_time": "2:29:29", "remaining_time": "1:21:28", "rewards/chosen": 1.0857884883880615, "rewards/rejected": 0.14797575771808624, "rewards/accuracies": 0.768750011920929, "rewards/margins": 0.9378126263618469, "logps/chosen": -317.29132080078125, "logps/rejected": -270.30157470703125, "logits/chosen": -1.382874846458435, "logits/rejected": -1.3788057565689087, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.7417969703674316, "stability/repetition_rate_mean": 0.8042968511581421} +{"current_steps": 600, "total_steps": 927, "eval_loss": 0.47359293699264526, "epoch": 0.6476858723519093, "percentage": 64.72, "elapsed_time": "2:34:01", "remaining_time": "1:23:56"} +{"current_steps": 610, "total_steps": 927, "loss": 0.4827, "accuracy": 0.785937488079071, "lr": 1.5891526148322593e-07, "epoch": 0.6584806368911078, "percentage": 65.8, "elapsed_time": "2:36:28", "remaining_time": "1:21:18", "rewards/chosen": 1.0058691501617432, "rewards/rejected": 0.11844401806592941, "rewards/accuracies": 0.785937488079071, "rewards/margins": 0.8874250650405884, "logps/chosen": -337.97906494140625, "logps/rejected": -273.7126159667969, "logits/chosen": -1.3868850469589233, "logits/rejected": -1.386324167251587, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.9982421398162842, "stability/repetition_rate_mean": 0.744921863079071} +{"current_steps": 620, "total_steps": 927, "loss": 0.494, "accuracy": 0.7734375, "lr": 1.5021198698108036e-07, "epoch": 0.6692754014303063, "percentage": 66.88, "elapsed_time": "2:38:51", "remaining_time": "1:18:39", "rewards/chosen": 1.0009812116622925, "rewards/rejected": 0.0862690731883049, "rewards/accuracies": 0.7734375, "rewards/margins": 0.914712131023407, "logps/chosen": -317.61688232421875, "logps/rejected": -255.9473114013672, "logits/chosen": -1.37397038936615, "logits/rejected": -1.378446102142334, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.2964844703674316, "stability/repetition_rate_mean": 0.8783203363418579} +{"current_steps": 630, "total_steps": 927, "loss": 0.4832, "accuracy": 0.7640625238418579, "lr": 1.416502901177251e-07, "epoch": 0.6800701659695048, "percentage": 67.96, "elapsed_time": "2:41:13", "remaining_time": "1:16:00", "rewards/chosen": 0.9517079591751099, "rewards/rejected": 0.09470874816179276, "rewards/accuracies": 0.7640625238418579, "rewards/margins": 0.8569992184638977, "logps/chosen": -311.6447448730469, "logps/rejected": -254.44578552246094, "logits/chosen": -1.3341145515441895, "logits/rejected": -1.3377490043640137, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.377539038658142, "stability/repetition_rate_mean": 0.8720703125} +{"current_steps": 640, "total_steps": 927, "loss": 0.4615, "accuracy": 0.800000011920929, "lr": 1.3324231809189983e-07, "epoch": 0.6908649305087032, "percentage": 69.04, "elapsed_time": "2:43:35", "remaining_time": "1:13:21", "rewards/chosen": 1.0257498025894165, "rewards/rejected": -0.0014841229422017932, "rewards/accuracies": 0.800000011920929, "rewards/margins": 1.0272339582443237, "logps/chosen": -319.6551818847656, "logps/rejected": -258.7291564941406, "logits/chosen": -1.3613817691802979, "logits/rejected": -1.3694230318069458, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.7732422351837158, "stability/repetition_rate_mean": 0.7818359136581421} +{"current_steps": 650, "total_steps": 927, "loss": 0.4443, "accuracy": 0.800000011920929, "lr": 1.2500000000000005e-07, "epoch": 0.7016596950479018, "percentage": 70.12, "elapsed_time": "2:45:50", "remaining_time": "1:10:40", "rewards/chosen": 0.9646196365356445, "rewards/rejected": -0.04443943500518799, "rewards/accuracies": 0.800000011920929, "rewards/margins": 1.0090590715408325, "logps/chosen": -292.4341735839844, "logps/rejected": -252.3300323486328, "logits/chosen": -1.322688341140747, "logits/rejected": -1.3375654220581055, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.5888671875, "stability/repetition_rate_mean": 0.850390613079071} +{"current_steps": 660, "total_steps": 927, "loss": 0.461, "accuracy": 0.7890625, "lr": 1.1693502991126608e-07, "epoch": 0.7124544595871003, "percentage": 71.2, "elapsed_time": "2:48:08", "remaining_time": "1:08:01", "rewards/chosen": 1.0033434629440308, "rewards/rejected": -0.03249470144510269, "rewards/accuracies": 0.7890625, "rewards/margins": 1.0358381271362305, "logps/chosen": -333.7082214355469, "logps/rejected": -250.5390625, "logits/chosen": -1.3551677465438843, "logits/rejected": -1.361363410949707, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.3021483421325684, "stability/repetition_rate_mean": 0.775585949420929} +{"current_steps": 670, "total_steps": 927, "loss": 0.477, "accuracy": 0.78125, "lr": 1.0905885027642483e-07, "epoch": 0.7232492241262988, "percentage": 72.28, "elapsed_time": "2:50:29", "remaining_time": "1:05:23", "rewards/chosen": 0.9816705584526062, "rewards/rejected": -0.0048652635887265205, "rewards/accuracies": 0.78125, "rewards/margins": 0.9865358471870422, "logps/chosen": -295.5746765136719, "logps/rejected": -237.2896728515625, "logits/chosen": -1.3491506576538086, "logits/rejected": -1.3566621541976929, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.6103515625, "stability/repetition_rate_mean": 0.785937488079071} +{"current_steps": 680, "total_steps": 927, "loss": 0.4736, "accuracy": 0.7796875238418579, "lr": 1.0138263569332267e-07, "epoch": 0.7340439886654972, "percentage": 73.35, "elapsed_time": "2:52:53", "remaining_time": "1:02:47", "rewards/chosen": 1.0467315912246704, "rewards/rejected": 0.059045251458883286, "rewards/accuracies": 0.7796875238418579, "rewards/margins": 0.9876863360404968, "logps/chosen": -314.92364501953125, "logps/rejected": -262.690673828125, "logits/chosen": -1.372681975364685, "logits/rejected": -1.3638715744018555, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.3708984851837158, "stability/repetition_rate_mean": 0.7417968511581421} +{"current_steps": 690, "total_steps": 927, "loss": 0.4613, "accuracy": 0.785937488079071, "lr": 9.391727705258502e-08, "epoch": 0.7448387532046957, "percentage": 74.43, "elapsed_time": "2:55:18", "remaining_time": "1:00:12", "rewards/chosen": 1.0267409086227417, "rewards/rejected": -0.01362178660929203, "rewards/accuracies": 0.785937488079071, "rewards/margins": 1.0403625965118408, "logps/chosen": -320.1853942871094, "logps/rejected": -271.3731384277344, "logits/chosen": -1.3565599918365479, "logits/rejected": -1.3600114583969116, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.596289038658142, "stability/repetition_rate_mean": 0.8603515625} +{"current_steps": 700, "total_steps": 927, "loss": 0.4775, "accuracy": 0.801562488079071, "lr": 8.667336608579487e-08, "epoch": 0.7556335177438942, "percentage": 75.51, "elapsed_time": "2:57:46", "remaining_time": "0:57:38", "rewards/chosen": 0.9467880129814148, "rewards/rejected": 0.011792674660682678, "rewards/accuracies": 0.801562488079071, "rewards/margins": 0.9349954724311829, "logps/chosen": -318.6557312011719, "logps/rejected": -261.914794921875, "logits/chosen": -1.3605684041976929, "logits/rejected": -1.3892539739608765, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.692675828933716, "stability/repetition_rate_mean": 0.8111327886581421} +{"current_steps": 710, "total_steps": 927, "loss": 0.4735, "accuracy": 0.796875, "lr": 7.96611803381127e-08, "epoch": 0.7664282822830927, "percentage": 76.59, "elapsed_time": "3:00:10", "remaining_time": "0:55:04", "rewards/chosen": 0.9548945426940918, "rewards/rejected": -0.02534562349319458, "rewards/accuracies": 0.796875, "rewards/margins": 0.9802401661872864, "logps/chosen": -303.3160095214844, "logps/rejected": -258.77264404296875, "logits/chosen": -1.3547624349594116, "logits/rejected": -1.3488959074020386, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.209765672683716, "stability/repetition_rate_mean": 0.840039074420929} +{"current_steps": 720, "total_steps": 927, "loss": 0.4632, "accuracy": 0.770312488079071, "lr": 7.28906685866599e-08, "epoch": 0.7772230468222912, "percentage": 77.67, "elapsed_time": "3:02:37", "remaining_time": "0:52:30", "rewards/chosen": 1.0151904821395874, "rewards/rejected": -0.02825441025197506, "rewards/accuracies": 0.770312488079071, "rewards/margins": 1.0434449911117554, "logps/chosen": -314.6918640136719, "logps/rejected": -246.10391235351562, "logits/chosen": -1.3702967166900635, "logits/rejected": -1.3795828819274902, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 0.8656250238418579, "stability/repetition_rate_mean": 0.8203125} +{"current_steps": 730, "total_steps": 927, "loss": 0.4905, "accuracy": 0.78125, "lr": 6.637143672535281e-08, "epoch": 0.7880178113614896, "percentage": 78.75, "elapsed_time": "3:05:00", "remaining_time": "0:49:55", "rewards/chosen": 1.0083658695220947, "rewards/rejected": 0.06377997249364853, "rewards/accuracies": 0.78125, "rewards/margins": 0.9445858001708984, "logps/chosen": -312.05279541015625, "logps/rejected": -256.790283203125, "logits/chosen": -1.3211309909820557, "logits/rejected": -1.3452644348144531, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.055468797683716, "stability/repetition_rate_mean": 0.7437499761581421} +{"current_steps": 740, "total_steps": 927, "loss": 0.4786, "accuracy": 0.7828125357627869, "lr": 6.01127341362138e-08, "epoch": 0.7988125759006882, "percentage": 79.83, "elapsed_time": "3:07:28", "remaining_time": "0:47:22", "rewards/chosen": 0.9195186495780945, "rewards/rejected": -0.05838441848754883, "rewards/accuracies": 0.7828125357627869, "rewards/margins": 0.9779030680656433, "logps/chosen": -314.6363220214844, "logps/rejected": -265.0621032714844, "logits/chosen": -1.339066505432129, "logits/rejected": -1.343850016593933, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.513671875, "stability/repetition_rate_mean": 0.775195300579071} +{"current_steps": 750, "total_steps": 927, "loss": 0.4702, "accuracy": 0.78125, "lr": 5.412344056649526e-08, "epoch": 0.8096073404398867, "percentage": 80.91, "elapsed_time": "3:09:52", "remaining_time": "0:44:48", "rewards/chosen": 1.004286766052246, "rewards/rejected": -0.05221066623926163, "rewards/accuracies": 0.78125, "rewards/margins": 1.0564974546432495, "logps/chosen": -323.9461364746094, "logps/rejected": -263.8832702636719, "logits/chosen": -1.3286861181259155, "logits/rejected": -1.3161166906356812, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.7333984375, "stability/repetition_rate_mean": 0.825390636920929} +{"current_steps": 760, "total_steps": 927, "loss": 0.4974, "accuracy": 0.7718750238418579, "lr": 4.841205353023714e-08, "epoch": 0.8204021049790852, "percentage": 81.98, "elapsed_time": "3:12:18", "remaining_time": "0:42:15", "rewards/chosen": 0.985223114490509, "rewards/rejected": 0.0688353106379509, "rewards/accuracies": 0.7718750238418579, "rewards/margins": 0.9163877367973328, "logps/chosen": -308.4322814941406, "logps/rejected": -251.6645965576172, "logits/chosen": -1.316092848777771, "logits/rejected": -1.3103103637695312, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.017578125, "stability/repetition_rate_mean": 0.779101550579071} +{"current_steps": 770, "total_steps": 927, "loss": 0.4839, "accuracy": 0.776562511920929, "lr": 4.298667625212904e-08, "epoch": 0.8311968695182836, "percentage": 83.06, "elapsed_time": "3:14:44", "remaining_time": "0:39:42", "rewards/chosen": 0.9914433360099792, "rewards/rejected": 0.01984873227775097, "rewards/accuracies": 0.776562511920929, "rewards/margins": 0.9715946316719055, "logps/chosen": -312.3675842285156, "logps/rejected": -260.13189697265625, "logits/chosen": -1.3329784870147705, "logits/rejected": -1.3454676866531372, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.833984375, "stability/repetition_rate_mean": 0.8814452886581421} +{"current_steps": 780, "total_steps": 927, "loss": 0.451, "accuracy": 0.8109375238418579, "lr": 3.785500617078424e-08, "epoch": 0.8419916340574821, "percentage": 84.14, "elapsed_time": "3:17:10", "remaining_time": "0:37:09", "rewards/chosen": 1.0986813306808472, "rewards/rejected": -0.03042042814195156, "rewards/accuracies": 0.8109375238418579, "rewards/margins": 1.1291017532348633, "logps/chosen": -339.4462585449219, "logps/rejected": -283.0810546875, "logits/chosen": -1.3594963550567627, "logits/rejected": -1.3589779138565063, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.575585961341858, "stability/repetition_rate_mean": 0.795703113079071} +{"current_steps": 790, "total_steps": 927, "loss": 0.4454, "accuracy": 0.809374988079071, "lr": 3.3024324017737554e-08, "epoch": 0.8527863985966806, "percentage": 85.22, "elapsed_time": "3:19:37", "remaining_time": "0:34:37", "rewards/chosen": 1.0409488677978516, "rewards/rejected": -0.016527360305190086, "rewards/accuracies": 0.809374988079071, "rewards/margins": 1.057476282119751, "logps/chosen": -314.4818115234375, "logps/rejected": -266.3319396972656, "logits/chosen": -1.341722846031189, "logits/rejected": -1.332808256149292, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.439843773841858, "stability/repetition_rate_mean": 0.8095703125} +{"current_steps": 800, "total_steps": 927, "loss": 0.4918, "accuracy": 0.770312488079071, "lr": 2.850148348765921e-08, "epoch": 0.8635811631358791, "percentage": 86.3, "elapsed_time": "3:22:00", "remaining_time": "0:32:04", "rewards/chosen": 0.9924200177192688, "rewards/rejected": 0.09035740047693253, "rewards/accuracies": 0.770312488079071, "rewards/margins": 0.9020625948905945, "logps/chosen": -304.0136413574219, "logps/rejected": -258.58209228515625, "logits/chosen": -1.3520551919937134, "logits/rejected": -1.355186939239502, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.61376953125, "stability/repetition_rate_mean": 0.9134765863418579} +{"current_steps": 810, "total_steps": 927, "loss": 0.4636, "accuracy": 0.7875000238418579, "lr": 2.4292901514442327e-08, "epoch": 0.8743759276750775, "percentage": 87.38, "elapsed_time": "3:24:24", "remaining_time": "0:29:31", "rewards/chosen": 1.0107624530792236, "rewards/rejected": 0.011880074627697468, "rewards/accuracies": 0.7875000238418579, "rewards/margins": 0.9988824725151062, "logps/chosen": -321.5726013183594, "logps/rejected": -258.95526123046875, "logits/chosen": -1.3454469442367554, "logits/rejected": -1.3386812210083008, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.4040038585662842, "stability/repetition_rate_mean": 0.8667968511581421} +{"current_steps": 820, "total_steps": 927, "loss": 0.4683, "accuracy": 0.7796875238418579, "lr": 2.0404549166959718e-08, "epoch": 0.885170692214276, "percentage": 88.46, "elapsed_time": "3:26:51", "remaining_time": "0:26:59", "rewards/chosen": 1.0170072317123413, "rewards/rejected": 0.03334783762693405, "rewards/accuracies": 0.7796875238418579, "rewards/margins": 0.9836593866348267, "logps/chosen": -308.5863037109375, "logps/rejected": -254.77041625976562, "logits/chosen": -1.300979495048523, "logits/rejected": -1.3161647319793701, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.8826172351837158, "stability/repetition_rate_mean": 0.9224609136581421} +{"current_steps": 830, "total_steps": 927, "loss": 0.4925, "accuracy": 0.7828125357627869, "lr": 1.6841943177406976e-08, "epoch": 0.8959654567534746, "percentage": 89.54, "elapsed_time": "3:29:17", "remaining_time": "0:24:27", "rewards/chosen": 0.9902805685997009, "rewards/rejected": -0.030288374051451683, "rewards/accuracies": 0.7828125357627869, "rewards/margins": 1.020569086074829, "logps/chosen": -319.1125793457031, "logps/rejected": -274.5699462890625, "logits/chosen": -1.3147996664047241, "logits/rejected": -1.3255729675292969, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.1563477516174316, "stability/repetition_rate_mean": 0.8330078125} +{"current_steps": 840, "total_steps": 927, "loss": 0.4735, "accuracy": 0.765625, "lr": 1.3610138114250519e-08, "epoch": 0.9067602212926731, "percentage": 90.61, "elapsed_time": "3:31:45", "remaining_time": "0:21:55", "rewards/chosen": 1.0660076141357422, "rewards/rejected": 0.06570061296224594, "rewards/accuracies": 0.765625, "rewards/margins": 1.0003070831298828, "logps/chosen": -327.689697265625, "logps/rejected": -261.86480712890625, "logits/chosen": -1.327235221862793, "logits/rejected": -1.343729853630066, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.4929687976837158, "stability/repetition_rate_mean": 0.8158203363418579} +{"current_steps": 850, "total_steps": 927, "loss": 0.4859, "accuracy": 0.776562511920929, "lr": 1.0713719210886928e-08, "epoch": 0.9175549858318716, "percentage": 91.69, "elapsed_time": "3:34:07", "remaining_time": "0:19:23", "rewards/chosen": 1.053748369216919, "rewards/rejected": 0.05971544608473778, "rewards/accuracies": 0.776562511920929, "rewards/margins": 0.9940328598022461, "logps/chosen": -324.7861328125, "logps/rejected": -261.70849609375, "logits/chosen": -1.3229340314865112, "logits/rejected": -1.3207443952560425, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.3533203601837158, "stability/repetition_rate_mean": 0.7544921636581421} +{"current_steps": 860, "total_steps": 927, "loss": 0.4306, "accuracy": 0.8109375238418579, "lr": 8.156795860187027e-09, "epoch": 0.92834975037107, "percentage": 92.77, "elapsed_time": "3:36:34", "remaining_time": "0:16:52", "rewards/chosen": 1.0677509307861328, "rewards/rejected": -0.06025683507323265, "rewards/accuracies": 0.8109375238418579, "rewards/margins": 1.1280078887939453, "logps/chosen": -336.0633850097656, "logps/rejected": -262.0978088378906, "logits/chosen": -1.348737359046936, "logits/rejected": -1.3422983884811401, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.556640625, "stability/repetition_rate_mean": 0.805468738079071} +{"current_steps": 870, "total_steps": 927, "loss": 0.4598, "accuracy": 0.7953125238418579, "lr": 5.942995784154692e-09, "epoch": 0.9391445149102685, "percentage": 93.85, "elapsed_time": "3:39:01", "remaining_time": "0:14:20", "rewards/chosen": 1.0478211641311646, "rewards/rejected": -0.0012408018810674548, "rewards/accuracies": 0.7953125238418579, "rewards/margins": 1.0490620136260986, "logps/chosen": -307.34771728515625, "logps/rejected": -260.82586669921875, "logits/chosen": -1.3338909149169922, "logits/rejected": -1.3578466176986694, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.4718749523162842, "stability/repetition_rate_mean": 0.864453136920929} +{"current_steps": 880, "total_steps": 927, "loss": 0.4837, "accuracy": 0.7750000357627869, "lr": 4.075459886973082e-09, "epoch": 0.949939279449467, "percentage": 94.93, "elapsed_time": "3:41:22", "remaining_time": "0:11:49", "rewards/chosen": 0.9852436184883118, "rewards/rejected": 0.012728266417980194, "rewards/accuracies": 0.7750000357627869, "rewards/margins": 0.9725152850151062, "logps/chosen": -288.3506774902344, "logps/rejected": -259.43109130859375, "logits/chosen": -1.322386622428894, "logits/rejected": -1.3134368658065796, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.583984375, "stability/repetition_rate_mean": 0.8818359375} +{"current_steps": 890, "total_steps": 927, "loss": 0.4647, "accuracy": 0.8109375238418579, "lr": 2.556837798739886e-09, "epoch": 0.9607340439886655, "percentage": 96.01, "elapsed_time": "3:43:40", "remaining_time": "0:09:17", "rewards/chosen": 0.9938045740127563, "rewards/rejected": -0.0041345953941345215, "rewards/accuracies": 0.8109375238418579, "rewards/margins": 0.9979391098022461, "logps/chosen": -314.2873229980469, "logps/rejected": -257.3379821777344, "logits/chosen": -1.3387622833251953, "logits/rejected": -1.34397554397583, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.6566405296325684, "stability/repetition_rate_mean": 0.8443359136581421} +{"current_steps": 900, "total_steps": 927, "loss": 0.455, "accuracy": 0.785937488079071, "lr": 1.3892841162143899e-09, "epoch": 0.9715288085278639, "percentage": 97.09, "elapsed_time": "3:46:00", "remaining_time": "0:06:46", "rewards/chosen": 0.9897605776786804, "rewards/rejected": -0.039306994527578354, "rewards/accuracies": 0.785937488079071, "rewards/margins": 1.0290673971176147, "logps/chosen": -304.279541015625, "logps/rejected": -257.1634216308594, "logits/chosen": -1.3134535551071167, "logits/rejected": -1.3294223546981812, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.3954589366912842, "stability/repetition_rate_mean": 0.7369140386581421} +{"current_steps": 900, "total_steps": 927, "eval_loss": 0.46732690930366516, "epoch": 0.9715288085278639, "percentage": 97.09, "elapsed_time": "3:50:30", "remaining_time": "0:06:54"} +{"current_steps": 910, "total_steps": 927, "loss": 0.4964, "accuracy": 0.7562500238418579, "lr": 5.744553459100243e-10, "epoch": 0.9823235730670625, "percentage": 98.17, "elapsed_time": "3:52:57", "remaining_time": "0:04:21", "rewards/chosen": 0.9547117352485657, "rewards/rejected": 0.03406943380832672, "rewards/accuracies": 0.7562500238418579, "rewards/margins": 0.9206423163414001, "logps/chosen": -324.1401062011719, "logps/rejected": -261.5168762207031, "logits/chosen": -1.3120925426483154, "logits/rejected": -1.3330440521240234, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 1.468652367591858, "stability/repetition_rate_mean": 0.875195324420929} +{"current_steps": 920, "total_steps": 927, "loss": 0.4515, "accuracy": 0.784375011920929, "lr": 1.1350755386951849e-10, "epoch": 0.993118337606261, "percentage": 99.24, "elapsed_time": "3:55:26", "remaining_time": "0:01:47", "rewards/chosen": 1.044679045677185, "rewards/rejected": 0.007530394475907087, "rewards/accuracies": 0.784375011920929, "rewards/margins": 1.0371487140655518, "logps/chosen": -329.8288879394531, "logps/rejected": -261.056640625, "logits/chosen": -1.3584011793136597, "logits/rejected": -1.3463481664657593, "stability/response_length_mean": 512.0, "stability/response_length_std": 0.0, "stability/response_length_var": 0.0, "stability/token_entropy_mean": 2.8033204078674316, "stability/repetition_rate_mean": 0.861328125} +{"current_steps": 927, "total_steps": 927, "epoch": 1.0, "percentage": 100.0, "elapsed_time": "3:59:14", "remaining_time": "0:00:00"} diff --git a/trainer_state.json b/trainer_state.json new file mode 100644 index 0000000..8b843e6 --- /dev/null +++ b/trainer_state.json @@ -0,0 +1,2036 @@ +{ + "best_global_step": null, + "best_metric": null, + "best_model_checkpoint": null, + "epoch": 1.0, + "eval_steps": 300, + "global_step": 927, + "is_hyper_param_search": false, + "is_local_process_zero": true, + "is_world_process_zero": true, + "log_history": [ + { + "epoch": 0.010794764539198488, + "grad_norm": 24.147397994995117, + "learning_rate": 4.8387096774193546e-08, + "logits/chosen": -1.4572813510894775, + "logits/rejected": -1.5238107442855835, + "logps/chosen": -328.8013610839844, + "logps/rejected": -253.98362731933594, + "loss": 0.6928, + "metrics/advantage_var": 0.2102208137512207, + "rewards/accuracies": 0.40937501192092896, + "rewards/chosen": 0.0015822252025827765, + "rewards/margins": 0.0017194593092426658, + "rewards/rejected": -0.0001372337428620085, + "step": 10 + }, + { + "epoch": 0.021589529078396976, + "grad_norm": 25.48040199279785, + "learning_rate": 1.0215053763440861e-07, + "logits/chosen": -1.4601737260818481, + "logits/rejected": -1.495823860168457, + "logps/chosen": -329.26373291015625, + "logps/rejected": -269.0686950683594, + "loss": 0.6933, + "metrics/advantage_var": 0.26926887035369873, + "rewards/accuracies": 0.5140625238418579, + "rewards/chosen": 0.0026884928811341524, + "rewards/margins": 0.0011197883868589997, + "rewards/rejected": 0.0015687048435211182, + "stability/repetition_rate_mean": 0.8257812261581421, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.434472680091858, + "step": 20 + }, + { + "epoch": 0.03238429361759547, + "grad_norm": 19.910463333129883, + "learning_rate": 1.5591397849462365e-07, + "logits/chosen": -1.4658056497573853, + "logits/rejected": -1.5197511911392212, + "logps/chosen": -316.17425537109375, + "logps/rejected": -256.8540954589844, + "loss": 0.6925, + "metrics/advantage_var": 0.24051065742969513, + "rewards/accuracies": 0.5140625238418579, + "rewards/chosen": 0.004414338618516922, + "rewards/margins": 0.0025372428353875875, + "rewards/rejected": 0.0018770955502986908, + "stability/repetition_rate_mean": 0.8824218511581421, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.364843726158142, + "step": 30 + }, + { + "epoch": 0.04317905815679395, + "grad_norm": 23.751585006713867, + "learning_rate": 2.0967741935483871e-07, + "logits/chosen": -1.4785693883895874, + "logits/rejected": -1.5407034158706665, + "logps/chosen": -329.3841247558594, + "logps/rejected": -258.57672119140625, + "loss": 0.6913, + "metrics/advantage_var": 0.2763865292072296, + "rewards/accuracies": 0.550000011920929, + "rewards/chosen": 0.005997015163302422, + "rewards/margins": 0.005208877846598625, + "rewards/rejected": 0.0007881380734033883, + "stability/repetition_rate_mean": 0.8031250238418579, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 2.0068359375, + "step": 40 + }, + { + "epoch": 0.05397382269599244, + "grad_norm": 20.962650299072266, + "learning_rate": 2.6344086021505376e-07, + "logits/chosen": -1.438301682472229, + "logits/rejected": -1.503927230834961, + "logps/chosen": -313.481689453125, + "logps/rejected": -258.3254089355469, + "loss": 0.6885, + "metrics/advantage_var": 0.281412810087204, + "rewards/accuracies": 0.546875, + "rewards/chosen": 0.01573883555829525, + "rewards/margins": 0.010696313343942165, + "rewards/rejected": 0.005042524076998234, + "stability/repetition_rate_mean": 0.8675781488418579, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 2.07568359375, + "step": 50 + }, + { + "epoch": 0.06476858723519094, + "grad_norm": 20.89899444580078, + "learning_rate": 3.172043010752688e-07, + "logits/chosen": -1.4596624374389648, + "logits/rejected": -1.501914620399475, + "logps/chosen": -318.685302734375, + "logps/rejected": -265.6797180175781, + "loss": 0.6846, + "metrics/advantage_var": 0.43760356307029724, + "rewards/accuracies": 0.604687511920929, + "rewards/chosen": 0.02920054830610752, + "rewards/margins": 0.019200993701815605, + "rewards/rejected": 0.009999553672969341, + "stability/repetition_rate_mean": 0.7318359613418579, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.2527344226837158, + "step": 60 + }, + { + "epoch": 0.07556335177438941, + "grad_norm": 22.085494995117188, + "learning_rate": 3.7096774193548384e-07, + "logits/chosen": -1.5026830434799194, + "logits/rejected": -1.5432065725326538, + "logps/chosen": -339.0155334472656, + "logps/rejected": -273.65655517578125, + "loss": 0.6787, + "metrics/advantage_var": 0.8573139309883118, + "rewards/accuracies": 0.609375, + "rewards/chosen": 0.06427477300167084, + "rewards/margins": 0.03314407169818878, + "rewards/rejected": 0.03113069012761116, + "stability/repetition_rate_mean": 0.8822265863418579, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.3330078125, + "step": 70 + }, + { + "epoch": 0.0863581163135879, + "grad_norm": 19.948606491088867, + "learning_rate": 4.247311827956989e-07, + "logits/chosen": -1.4859027862548828, + "logits/rejected": -1.5006340742111206, + "logps/chosen": -325.33526611328125, + "logps/rejected": -254.3518524169922, + "loss": 0.6616, + "metrics/advantage_var": 1.5368133783340454, + "rewards/accuracies": 0.643750011920929, + "rewards/chosen": 0.1002170592546463, + "rewards/margins": 0.07156896591186523, + "rewards/rejected": 0.028648091480135918, + "stability/repetition_rate_mean": 0.8583984375, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.825048804283142, + "step": 80 + }, + { + "epoch": 0.0971528808527864, + "grad_norm": 16.032991409301758, + "learning_rate": 4.78494623655914e-07, + "logits/chosen": -1.4689861536026, + "logits/rejected": -1.4905648231506348, + "logps/chosen": -295.8207702636719, + "logps/rejected": -248.85952758789062, + "loss": 0.6497, + "metrics/advantage_var": 3.12138295173645, + "rewards/accuracies": 0.6953125, + "rewards/chosen": 0.14759615063667297, + "rewards/margins": 0.10207539796829224, + "rewards/rejected": 0.04552074521780014, + "stability/repetition_rate_mean": 0.8740234375, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.663671851158142, + "step": 90 + }, + { + "epoch": 0.10794764539198488, + "grad_norm": 19.689159393310547, + "learning_rate": 4.999361498869529e-07, + "logits/chosen": -1.4919625520706177, + "logits/rejected": -1.5506508350372314, + "logps/chosen": -314.435791015625, + "logps/rejected": -249.51695251464844, + "loss": 0.6413, + "metrics/advantage_var": 5.264100551605225, + "rewards/accuracies": 0.6890625357627869, + "rewards/chosen": 0.19397814571857452, + "rewards/margins": 0.12933655083179474, + "rewards/rejected": 0.06464159488677979, + "stability/repetition_rate_mean": 0.9400390386581421, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 2.4281249046325684, + "step": 100 + }, + { + "epoch": 0.11874240993118337, + "grad_norm": 17.759952545166016, + "learning_rate": 4.995460728562402e-07, + "logits/chosen": -1.4327154159545898, + "logits/rejected": -1.5077978372573853, + "logps/chosen": -319.29156494140625, + "logps/rejected": -253.4399871826172, + "loss": 0.6214, + "metrics/advantage_var": 8.01412582397461, + "rewards/accuracies": 0.714062511920929, + "rewards/chosen": 0.24892178177833557, + "rewards/margins": 0.18393009901046753, + "rewards/rejected": 0.06499166041612625, + "stability/repetition_rate_mean": 0.809374988079071, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 2.246875047683716, + "step": 110 + }, + { + "epoch": 0.12953717447038188, + "grad_norm": 20.968534469604492, + "learning_rate": 4.988019438437758e-07, + "logits/chosen": -1.4564826488494873, + "logits/rejected": -1.5484386682510376, + "logps/chosen": -330.7845764160156, + "logps/rejected": -248.1776885986328, + "loss": 0.6032, + "metrics/advantage_var": 14.087158203125, + "rewards/accuracies": 0.739062488079071, + "rewards/chosen": 0.3554464876651764, + "rewards/margins": 0.2473072111606598, + "rewards/rejected": 0.1081392914056778, + "stability/repetition_rate_mean": 0.7470703125, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.070214867591858, + "step": 120 + }, + { + "epoch": 0.14033193900958035, + "grad_norm": 19.773218154907227, + "learning_rate": 4.977048186079155e-07, + "logits/chosen": -1.4577782154083252, + "logits/rejected": -1.508943796157837, + "logps/chosen": -317.5703125, + "logps/rejected": -253.7754364013672, + "loss": 0.5951, + "metrics/advantage_var": 16.9871883392334, + "rewards/accuracies": 0.721875011920929, + "rewards/chosen": 0.40177080035209656, + "rewards/margins": 0.28298041224479675, + "rewards/rejected": 0.11879038065671921, + "stability/repetition_rate_mean": 0.773242175579071, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.4833984375, + "step": 130 + }, + { + "epoch": 0.15112670354877883, + "grad_norm": 13.235716819763184, + "learning_rate": 4.962562537324176e-07, + "logits/chosen": -1.4774430990219116, + "logits/rejected": -1.512833833694458, + "logps/chosen": -343.68548583984375, + "logps/rejected": -272.2403869628906, + "loss": 0.6036, + "metrics/advantage_var": 24.688919067382812, + "rewards/accuracies": 0.6890625357627869, + "rewards/chosen": 0.42533954977989197, + "rewards/margins": 0.2894915044307709, + "rewards/rejected": 0.1358480602502823, + "stability/repetition_rate_mean": 0.8072265386581421, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.019140601158142, + "step": 140 + }, + { + "epoch": 0.16192146808797733, + "grad_norm": 19.26375961303711, + "learning_rate": 4.944583044179871e-07, + "logits/chosen": -1.4802706241607666, + "logits/rejected": -1.5120983123779297, + "logps/chosen": -320.7796936035156, + "logps/rejected": -268.3492126464844, + "loss": 0.6074, + "metrics/advantage_var": 21.159940719604492, + "rewards/accuracies": 0.6968750357627869, + "rewards/chosen": 0.412137508392334, + "rewards/margins": 0.2721858024597168, + "rewards/rejected": 0.13995173573493958, + "stability/repetition_rate_mean": 0.807421863079071, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.5673828125, + "step": 150 + }, + { + "epoch": 0.1727162326271758, + "grad_norm": 24.66869354248047, + "learning_rate": 4.923135215663896e-07, + "logits/chosen": -1.479994773864746, + "logits/rejected": -1.5399045944213867, + "logps/chosen": -317.5917663574219, + "logps/rejected": -243.84231567382812, + "loss": 0.5807, + "metrics/advantage_var": 26.341684341430664, + "rewards/accuracies": 0.7484375238418579, + "rewards/chosen": 0.46426326036453247, + "rewards/margins": 0.3650646209716797, + "rewards/rejected": 0.09919857233762741, + "stability/repetition_rate_mean": 0.789257824420929, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.4421875476837158, + "step": 160 + }, + { + "epoch": 0.1835109971663743, + "grad_norm": 22.35947036743164, + "learning_rate": 4.89824948161273e-07, + "logits/chosen": -1.4407405853271484, + "logits/rejected": -1.5115913152694702, + "logps/chosen": -308.2352600097656, + "logps/rejected": -256.36358642578125, + "loss": 0.5752, + "metrics/advantage_var": 30.53228759765625, + "rewards/accuracies": 0.706250011920929, + "rewards/chosen": 0.47893524169921875, + "rewards/margins": 0.39258310198783875, + "rewards/rejected": 0.08635219186544418, + "stability/repetition_rate_mean": 0.7845703363418579, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.5763671398162842, + "step": 170 + }, + { + "epoch": 0.1943057617055728, + "grad_norm": 14.936376571655273, + "learning_rate": 4.8699611495083e-07, + "logits/chosen": -1.504378318786621, + "logits/rejected": -1.5372484922409058, + "logps/chosen": -317.1926574707031, + "logps/rejected": -261.8941650390625, + "loss": 0.5744, + "metrics/advantage_var": 36.89189910888672, + "rewards/accuracies": 0.7109375, + "rewards/chosen": 0.5145285725593567, + "rewards/margins": 0.40907564759254456, + "rewards/rejected": 0.10545291751623154, + "stability/repetition_rate_mean": 0.7490234375, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.5693359375, + "step": 180 + }, + { + "epoch": 0.2051005262447713, + "grad_norm": 20.977313995361328, + "learning_rate": 4.838310354384302e-07, + "logits/chosen": -1.4963879585266113, + "logits/rejected": -1.5239351987838745, + "logps/chosen": -307.32684326171875, + "logps/rejected": -263.76373291015625, + "loss": 0.5629, + "metrics/advantage_var": 36.270076751708984, + "rewards/accuracies": 0.707812488079071, + "rewards/chosen": 0.5523476600646973, + "rewards/margins": 0.4342571198940277, + "rewards/rejected": 0.11809053272008896, + "stability/repetition_rate_mean": 0.850781261920929, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.1296875476837158, + "step": 190 + }, + { + "epoch": 0.21589529078396977, + "grad_norm": 13.247014045715332, + "learning_rate": 4.803342001883246e-07, + "logits/chosen": -1.5078216791152954, + "logits/rejected": -1.541197419166565, + "logps/chosen": -318.7608337402344, + "logps/rejected": -267.5777282714844, + "loss": 0.5524, + "metrics/advantage_var": 35.416255950927734, + "rewards/accuracies": 0.745312511920929, + "rewards/chosen": 0.556470513343811, + "rewards/margins": 0.4586350917816162, + "rewards/rejected": 0.09783537685871124, + "stability/repetition_rate_mean": 0.796679675579071, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.4445312023162842, + "step": 200 + }, + { + "epoch": 0.22669005532316827, + "grad_norm": 16.3123722076416, + "learning_rate": 4.7651057045450515e-07, + "logits/chosen": -1.4529699087142944, + "logits/rejected": -1.5274174213409424, + "logps/chosen": -326.5751647949219, + "logps/rejected": -245.41970825195312, + "loss": 0.5515, + "metrics/advantage_var": 36.527748107910156, + "rewards/accuracies": 0.7484375238418579, + "rewards/chosen": 0.5690556764602661, + "rewards/margins": 0.4599929749965668, + "rewards/rejected": 0.10906264930963516, + "stability/repetition_rate_mean": 0.81640625, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.3254883289337158, + "step": 210 + }, + { + "epoch": 0.23748481986236675, + "grad_norm": 21.77730369567871, + "learning_rate": 4.72365571141757e-07, + "logits/chosen": -1.4564087390899658, + "logits/rejected": -1.4975181818008423, + "logps/chosen": -331.7127380371094, + "logps/rejected": -264.9964294433594, + "loss": 0.5548, + "metrics/advantage_var": 43.936622619628906, + "rewards/accuracies": 0.746874988079071, + "rewards/chosen": 0.5794717669487, + "rewards/margins": 0.4975171983242035, + "rewards/rejected": 0.08195456117391586, + "stability/repetition_rate_mean": 0.7367187738418579, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.763671875, + "step": 220 + }, + { + "epoch": 0.24827958440156525, + "grad_norm": 18.723806381225586, + "learning_rate": 4.6790508310889007e-07, + "logits/chosen": -1.4929759502410889, + "logits/rejected": -1.5188223123550415, + "logps/chosen": -311.7873229980469, + "logps/rejected": -257.8661193847656, + "loss": 0.5575, + "metrics/advantage_var": 45.32672882080078, + "rewards/accuracies": 0.7359375357627869, + "rewards/chosen": 0.5666539072990417, + "rewards/margins": 0.48853203654289246, + "rewards/rejected": 0.07812191545963287, + "stability/repetition_rate_mean": 0.8841797113418579, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 2.4400391578674316, + "step": 230 + }, + { + "epoch": 0.25907434894076375, + "grad_norm": 12.753899574279785, + "learning_rate": 4.6313543482507056e-07, + "logits/chosen": -1.4668247699737549, + "logits/rejected": -1.50505530834198, + "logps/chosen": -319.4496154785156, + "logps/rejected": -261.7314453125, + "loss": 0.5496, + "metrics/advantage_var": 46.35799789428711, + "rewards/accuracies": 0.7281250357627869, + "rewards/chosen": 0.5762147307395935, + "rewards/margins": 0.5230244398117065, + "rewards/rejected": 0.05319035053253174, + "stability/repetition_rate_mean": 0.802539050579071, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 2.0635743141174316, + "step": 240 + }, + { + "epoch": 0.26986911347996223, + "grad_norm": 17.50574493408203, + "learning_rate": 4.580633933910901e-07, + "logits/chosen": -1.436219334602356, + "logits/rejected": -1.46418035030365, + "logps/chosen": -305.2557678222656, + "logps/rejected": -253.59902954101562, + "loss": 0.5612, + "metrics/advantage_var": 47.63227081298828, + "rewards/accuracies": 0.723437488079071, + "rewards/chosen": 0.5559987425804138, + "rewards/margins": 0.4999403655529022, + "rewards/rejected": 0.0560583770275116, + "stability/repetition_rate_mean": 0.811718761920929, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.45166015625, + "step": 250 + }, + { + "epoch": 0.2806638780191607, + "grad_norm": 15.86179256439209, + "learning_rate": 4.526961549383108e-07, + "logits/chosen": -1.4230726957321167, + "logits/rejected": -1.4305095672607422, + "logps/chosen": -325.4045104980469, + "logps/rejected": -272.9486389160156, + "loss": 0.5574, + "metrics/advantage_var": 50.00086212158203, + "rewards/accuracies": 0.7203125357627869, + "rewards/chosen": 0.6053926348686218, + "rewards/margins": 0.5237736105918884, + "rewards/rejected": 0.08161897957324982, + "stability/repetition_rate_mean": 0.813281238079071, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.894628882408142, + "step": 260 + }, + { + "epoch": 0.2914586425583592, + "grad_norm": 15.887772560119629, + "learning_rate": 4.470413344189098e-07, + "logits/chosen": -1.4393119812011719, + "logits/rejected": -1.467215895652771, + "logps/chosen": -323.3600158691406, + "logps/rejected": -270.2887878417969, + "loss": 0.5356, + "metrics/advantage_var": 55.44666290283203, + "rewards/accuracies": 0.7437500357627869, + "rewards/chosen": 0.6630539894104004, + "rewards/margins": 0.5985837578773499, + "rewards/rejected": 0.06447024643421173, + "stability/repetition_rate_mean": 0.828906238079071, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.030859351158142, + "step": 270 + }, + { + "epoch": 0.30225340709755766, + "grad_norm": 15.110116958618164, + "learning_rate": 4.4110695480190597e-07, + "logits/chosen": -1.4905976057052612, + "logits/rejected": -1.5187627077102661, + "logps/chosen": -330.3580627441406, + "logps/rejected": -267.19561767578125, + "loss": 0.5221, + "metrics/advantage_var": 60.70363235473633, + "rewards/accuracies": 0.7671875357627869, + "rewards/chosen": 0.7377834916114807, + "rewards/margins": 0.6288355588912964, + "rewards/rejected": 0.10894794762134552, + "stability/repetition_rate_mean": 0.8851562738418579, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.202734351158142, + "step": 280 + }, + { + "epoch": 0.3130481716367562, + "grad_norm": 15.053842544555664, + "learning_rate": 4.3490143569030017e-07, + "logits/chosen": -1.4678796529769897, + "logits/rejected": -1.5179208517074585, + "logps/chosen": -320.11309814453125, + "logps/rejected": -252.4005584716797, + "loss": 0.5299, + "metrics/advantage_var": 55.2855110168457, + "rewards/accuracies": 0.746874988079071, + "rewards/chosen": 0.6983198523521423, + "rewards/margins": 0.5931033492088318, + "rewards/rejected": 0.10521648079156876, + "stability/repetition_rate_mean": 0.8099609613418579, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.6193358898162842, + "step": 290 + }, + { + "epoch": 0.32384293617595467, + "grad_norm": 21.189123153686523, + "learning_rate": 4.284335813754769e-07, + "logits/chosen": -1.4394444227218628, + "logits/rejected": -1.4822733402252197, + "logps/chosen": -321.5018005371094, + "logps/rejected": -276.88409423828125, + "loss": 0.5031, + "metrics/advantage_var": 60.6578483581543, + "rewards/accuracies": 0.770312488079071, + "rewards/chosen": 0.6781904101371765, + "rewards/margins": 0.6781806349754333, + "rewards/rejected": 9.752810001373291e-06, + "stability/repetition_rate_mean": 0.7289062738418579, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 2.1236329078674316, + "step": 300 + }, + { + "epoch": 0.32384293617595467, + "eval_logits/chosen": -1.4329925775527954, + "eval_logits/rejected": -1.4661825895309448, + "eval_logps/chosen": -319.7928161621094, + "eval_logps/rejected": -254.64100646972656, + "eval_loss": 0.513998806476593, + "eval_metrics/advantage_var": 65.03108215332031, + "eval_rewards/accuracies": 0.7623737454414368, + "eval_rewards/chosen": 0.7029823660850525, + "eval_rewards/margins": 0.680192232131958, + "eval_rewards/rejected": 0.022790152579545975, + "eval_runtime": 272.245, + "eval_samples_per_second": 14.524, + "eval_stability/repetition_rate_mean": 0.9048827886581421, + "eval_stability/response_length_mean": 512.0, + "eval_stability/response_length_std": 0.0, + "eval_stability/response_length_var": 0.0, + "eval_stability/token_entropy_mean": 1.9105956554412842, + "eval_steps_per_second": 1.818, + "step": 300 + }, + { + "epoch": 0.33463770071515314, + "grad_norm": 20.66907501220703, + "learning_rate": 4.217125683458161e-07, + "logits/chosen": -1.4233049154281616, + "logits/rejected": -1.452370285987854, + "logps/chosen": -315.331298828125, + "logps/rejected": -258.9646911621094, + "loss": 0.534, + "metrics/advantage_var": 62.50199508666992, + "rewards/accuracies": 0.75, + "rewards/chosen": 0.6554938554763794, + "rewards/margins": 0.6286452412605286, + "rewards/rejected": 0.0268485676497221, + "stability/repetition_rate_mean": 0.799023449420929, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 0.908203125, + "step": 310 + }, + { + "epoch": 0.3454324652543516, + "grad_norm": 15.366827011108398, + "learning_rate": 4.1474793226723825e-07, + "logits/chosen": -1.448975682258606, + "logits/rejected": -1.4607841968536377, + "logps/chosen": -327.7336120605469, + "logps/rejected": -262.0153503417969, + "loss": 0.5117, + "metrics/advantage_var": 68.2557373046875, + "rewards/accuracies": 0.760937511920929, + "rewards/chosen": 0.7362013459205627, + "rewards/margins": 0.6878542304039001, + "rewards/rejected": 0.048347149044275284, + "stability/repetition_rate_mean": 0.9072265625, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.083886742591858, + "step": 320 + }, + { + "epoch": 0.35622722979355015, + "grad_norm": 19.474281311035156, + "learning_rate": 4.0754955445415396e-07, + "logits/chosen": -1.447295069694519, + "logits/rejected": -1.47311270236969, + "logps/chosen": -330.9326477050781, + "logps/rejected": -256.48638916015625, + "loss": 0.4903, + "metrics/advantage_var": 77.84224700927734, + "rewards/accuracies": 0.7562500238418579, + "rewards/chosen": 0.7997223734855652, + "rewards/margins": 0.7868985533714294, + "rewards/rejected": 0.012823845259845257, + "stability/repetition_rate_mean": 0.955273449420929, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.7205078601837158, + "step": 330 + }, + { + "epoch": 0.3670219943327486, + "grad_norm": 13.608744621276855, + "learning_rate": 4.001276478500126e-07, + "logits/chosen": -1.4461034536361694, + "logits/rejected": -1.4699530601501465, + "logps/chosen": -316.4836120605469, + "logps/rejected": -258.7716064453125, + "loss": 0.4981, + "metrics/advantage_var": 72.29796600341797, + "rewards/accuracies": 0.770312488079071, + "rewards/chosen": 0.7650503516197205, + "rewards/margins": 0.738609790802002, + "rewards/rejected": 0.026440534740686417, + "stability/repetition_rate_mean": 0.7232421636581421, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.8572266101837158, + "step": 340 + }, + { + "epoch": 0.3778167588719471, + "grad_norm": 13.565873146057129, + "learning_rate": 3.9249274253734164e-07, + "logits/chosen": -1.4219696521759033, + "logits/rejected": -1.4259979724884033, + "logps/chosen": -314.6985778808594, + "logps/rejected": -269.089599609375, + "loss": 0.5247, + "metrics/advantage_var": 80.2893295288086, + "rewards/accuracies": 0.7359375357627869, + "rewards/chosen": 0.7249447107315063, + "rewards/margins": 0.712753176689148, + "rewards/rejected": 0.012191593647003174, + "stability/repetition_rate_mean": 0.76953125, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.2517578601837158, + "step": 350 + }, + { + "epoch": 0.3886115234111456, + "grad_norm": 13.095726013183594, + "learning_rate": 3.846556707978337e-07, + "logits/chosen": -1.427175760269165, + "logits/rejected": -1.461297869682312, + "logps/chosen": -334.6982727050781, + "logps/rejected": -252.6654815673828, + "loss": 0.5044, + "metrics/advantage_var": 77.54660034179688, + "rewards/accuracies": 0.7515625357627869, + "rewards/chosen": 0.8103561401367188, + "rewards/margins": 0.7708074450492859, + "rewards/rejected": 0.039548713713884354, + "stability/repetition_rate_mean": 0.889843761920929, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.2664062976837158, + "step": 360 + }, + { + "epoch": 0.3994062879503441, + "grad_norm": 14.872525215148926, + "learning_rate": 3.766275517436779e-07, + "logits/chosen": -1.3873792886734009, + "logits/rejected": -1.3985546827316284, + "logps/chosen": -319.5567321777344, + "logps/rejected": -254.91746520996094, + "loss": 0.4983, + "metrics/advantage_var": 75.8227767944336, + "rewards/accuracies": 0.729687511920929, + "rewards/chosen": 0.7894806861877441, + "rewards/margins": 0.7587611079216003, + "rewards/rejected": 0.03071962669491768, + "stability/repetition_rate_mean": 0.777148425579071, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.752539038658142, + "step": 370 + }, + { + "epoch": 0.4102010524895426, + "grad_norm": 14.203469276428223, + "learning_rate": 3.684197755419419e-07, + "logits/chosen": -1.4125322103500366, + "logits/rejected": -1.417395830154419, + "logps/chosen": -306.7962341308594, + "logps/rejected": -258.84234619140625, + "loss": 0.5001, + "metrics/advantage_var": 81.72932434082031, + "rewards/accuracies": 0.7593750357627869, + "rewards/chosen": 0.7916366457939148, + "rewards/margins": 0.7797738909721375, + "rewards/rejected": 0.01186272781342268, + "stability/repetition_rate_mean": 0.7945312261581421, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 2.844921827316284, + "step": 380 + }, + { + "epoch": 0.42099581702874106, + "grad_norm": 14.88988971710205, + "learning_rate": 3.60043987254384e-07, + "logits/chosen": -1.425724983215332, + "logits/rejected": -1.4372109174728394, + "logps/chosen": -316.85101318359375, + "logps/rejected": -264.2350769042969, + "loss": 0.4952, + "metrics/advantage_var": 92.4764404296875, + "rewards/accuracies": 0.765625, + "rewards/chosen": 0.8086903691291809, + "rewards/margins": 0.8516300320625305, + "rewards/rejected": -0.04293971136212349, + "stability/repetition_rate_mean": 0.74609375, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.869531273841858, + "step": 390 + }, + { + "epoch": 0.43179058156793954, + "grad_norm": 13.483888626098633, + "learning_rate": 3.5151207031562633e-07, + "logits/chosen": -1.3795498609542847, + "logits/rejected": -1.3812373876571655, + "logps/chosen": -310.2779235839844, + "logps/rejected": -268.259033203125, + "loss": 0.5137, + "metrics/advantage_var": 87.57612609863281, + "rewards/accuracies": 0.776562511920929, + "rewards/chosen": 0.7608602046966553, + "rewards/margins": 0.7845363020896912, + "rewards/rejected": -0.023676123470067978, + "stability/repetition_rate_mean": 0.7679687738418579, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.6525390148162842, + "step": 400 + }, + { + "epoch": 0.442585346107138, + "grad_norm": 15.127874374389648, + "learning_rate": 3.4283612967312687e-07, + "logits/chosen": -1.3496493101119995, + "logits/rejected": -1.3831802606582642, + "logps/chosen": -313.1993103027344, + "logps/rejected": -250.6515655517578, + "loss": 0.5069, + "metrics/advantage_var": 93.4025650024414, + "rewards/accuracies": 0.760937511920929, + "rewards/chosen": 0.7829875349998474, + "rewards/margins": 0.8043760657310486, + "rewards/rejected": -0.021388515830039978, + "stability/repetition_rate_mean": 0.854296863079071, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.6925780773162842, + "step": 410 + }, + { + "epoch": 0.45338011064633654, + "grad_norm": 13.931750297546387, + "learning_rate": 3.34028474612874e-07, + "logits/chosen": -1.3803904056549072, + "logits/rejected": -1.394149661064148, + "logps/chosen": -299.86065673828125, + "logps/rejected": -261.5897521972656, + "loss": 0.5122, + "metrics/advantage_var": 100.02517700195312, + "rewards/accuracies": 0.737500011920929, + "rewards/chosen": 0.7716613411903381, + "rewards/margins": 0.8435766100883484, + "rewards/rejected": -0.07191526889801025, + "stability/repetition_rate_mean": 0.822460949420929, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 2.1460938453674316, + "step": 420 + }, + { + "epoch": 0.464174875185535, + "grad_norm": 15.035143852233887, + "learning_rate": 3.2510160129516775e-07, + "logits/chosen": -1.3800678253173828, + "logits/rejected": -1.3930643796920776, + "logps/chosen": -319.5307922363281, + "logps/rejected": -265.67938232421875, + "loss": 0.4937, + "metrics/advantage_var": 104.3858413696289, + "rewards/accuracies": 0.768750011920929, + "rewards/chosen": 0.8203991055488586, + "rewards/margins": 0.8988785147666931, + "rewards/rejected": -0.07847942411899567, + "stability/repetition_rate_mean": 0.78125, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 2.808789014816284, + "step": 430 + }, + { + "epoch": 0.4749696397247335, + "grad_norm": 14.138893127441406, + "learning_rate": 3.1606817502526736e-07, + "logits/chosen": -1.3767389059066772, + "logits/rejected": -1.4001781940460205, + "logps/chosen": -326.2301330566406, + "logps/rejected": -256.16412353515625, + "loss": 0.4891, + "metrics/advantage_var": 99.69866943359375, + "rewards/accuracies": 0.792187511920929, + "rewards/chosen": 0.8151880502700806, + "rewards/margins": 0.8713592886924744, + "rewards/rejected": -0.05617132410407066, + "stability/repetition_rate_mean": 0.8707031011581421, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 2.164990186691284, + "step": 440 + }, + { + "epoch": 0.48576440426393197, + "grad_norm": 11.794190406799316, + "learning_rate": 3.069410122840585e-07, + "logits/chosen": -1.372667670249939, + "logits/rejected": -1.4003467559814453, + "logps/chosen": -318.3290100097656, + "logps/rejected": -268.3873596191406, + "loss": 0.4817, + "metrics/advantage_var": 106.1712417602539, + "rewards/accuracies": 0.7890625, + "rewards/chosen": 0.8885055780410767, + "rewards/margins": 0.924716591835022, + "rewards/rejected": -0.03621084615588188, + "stability/repetition_rate_mean": 0.8236328363418579, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.7429687976837158, + "step": 450 + }, + { + "epoch": 0.4965591688031305, + "grad_norm": 12.17612361907959, + "learning_rate": 2.9773306254423513e-07, + "logits/chosen": -1.3681141138076782, + "logits/rejected": -1.3875712156295776, + "logps/chosen": -294.7362976074219, + "logps/rejected": -240.1558074951172, + "loss": 0.4832, + "metrics/advantage_var": 90.08233642578125, + "rewards/accuracies": 0.7718750238418579, + "rewards/chosen": 0.853641152381897, + "rewards/margins": 0.8702511191368103, + "rewards/rejected": -0.016610044986009598, + "stability/repetition_rate_mean": 0.8646484613418579, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.7371094226837158, + "step": 460 + }, + { + "epoch": 0.5073539333423289, + "grad_norm": 16.81270980834961, + "learning_rate": 2.884573898977941e-07, + "logits/chosen": -1.388026237487793, + "logits/rejected": -1.3998411893844604, + "logps/chosen": -308.7089538574219, + "logps/rejected": -268.0931091308594, + "loss": 0.4801, + "metrics/advantage_var": 102.28583526611328, + "rewards/accuracies": 0.7593750357627869, + "rewards/chosen": 0.8505555391311646, + "rewards/margins": 0.8920961618423462, + "rewards/rejected": -0.04154070094227791, + "stability/repetition_rate_mean": 0.8687499761581421, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.244531273841858, + "step": 470 + }, + { + "epoch": 0.5181486978815275, + "grad_norm": 17.988006591796875, + "learning_rate": 2.791271545209101e-07, + "logits/chosen": -1.3824865818023682, + "logits/rejected": -1.4162545204162598, + "logps/chosen": -294.66412353515625, + "logps/rejected": -248.6920928955078, + "loss": 0.4827, + "metrics/advantage_var": 95.26998138427734, + "rewards/accuracies": 0.7890625, + "rewards/chosen": 0.8823606371879578, + "rewards/margins": 0.8613284230232239, + "rewards/rejected": 0.021032243967056274, + "stability/repetition_rate_mean": 0.8519531488418579, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 2.1624999046325684, + "step": 480 + }, + { + "epoch": 0.528943462420726, + "grad_norm": 15.620615005493164, + "learning_rate": 2.697555940024887e-07, + "logits/chosen": -1.3622970581054688, + "logits/rejected": -1.3937467336654663, + "logps/chosen": -303.913330078125, + "logps/rejected": -242.33706665039062, + "loss": 0.4647, + "metrics/advantage_var": 105.72547912597656, + "rewards/accuracies": 0.792187511920929, + "rewards/chosen": 0.9351348280906677, + "rewards/margins": 0.9704492688179016, + "rewards/rejected": -0.035314515233039856, + "stability/repetition_rate_mean": 0.8125, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.9038817882537842, + "step": 490 + }, + { + "epoch": 0.5397382269599245, + "grad_norm": 28.97076416015625, + "learning_rate": 2.603560045628857e-07, + "logits/chosen": -1.3485071659088135, + "logits/rejected": -1.3485997915267944, + "logps/chosen": -314.1101989746094, + "logps/rejected": -261.1115417480469, + "loss": 0.482, + "metrics/advantage_var": 112.3708267211914, + "rewards/accuracies": 0.7828125357627869, + "rewards/chosen": 0.9495781064033508, + "rewards/margins": 0.9663735628128052, + "rewards/rejected": -0.016795417293906212, + "stability/repetition_rate_mean": 0.7855468988418579, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 2.1546874046325684, + "step": 500 + }, + { + "epoch": 0.5505329914991229, + "grad_norm": 16.771753311157227, + "learning_rate": 2.509417221894427e-07, + "logits/chosen": -1.3849689960479736, + "logits/rejected": -1.3808684349060059, + "logps/chosen": -307.50494384765625, + "logps/rejected": -269.51959228515625, + "loss": 0.4861, + "metrics/advantage_var": 120.5189208984375, + "rewards/accuracies": 0.796875, + "rewards/chosen": 0.9477736353874207, + "rewards/margins": 0.9401771426200867, + "rewards/rejected": 0.007596464361995459, + "stability/repetition_rate_mean": 0.8619140386581421, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.330175757408142, + "step": 510 + }, + { + "epoch": 0.5613277560383214, + "grad_norm": 16.037240982055664, + "learning_rate": 2.4152610371560093e-07, + "logits/chosen": -1.4082396030426025, + "logits/rejected": -1.4073408842086792, + "logps/chosen": -308.14276123046875, + "logps/rejected": -257.72283935546875, + "loss": 0.4896, + "metrics/advantage_var": 103.19306945800781, + "rewards/accuracies": 0.765625, + "rewards/chosen": 0.9386131167411804, + "rewards/margins": 0.8744432330131531, + "rewards/rejected": 0.06416996568441391, + "stability/repetition_rate_mean": 0.856640636920929, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.715429663658142, + "step": 520 + }, + { + "epoch": 0.5721225205775199, + "grad_norm": 20.248550415039062, + "learning_rate": 2.321225078704399e-07, + "logits/chosen": -1.4284799098968506, + "logits/rejected": -1.4444469213485718, + "logps/chosen": -317.8136291503906, + "logps/rejected": -260.39678955078125, + "loss": 0.4874, + "metrics/advantage_var": 103.1753921508789, + "rewards/accuracies": 0.7562500238418579, + "rewards/chosen": 1.0152686834335327, + "rewards/margins": 0.8757182955741882, + "rewards/rejected": 0.1395503580570221, + "stability/repetition_rate_mean": 0.7701171636581421, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.365820288658142, + "step": 530 + }, + { + "epoch": 0.5829172851167184, + "grad_norm": 17.81089210510254, + "learning_rate": 2.2274427632552503e-07, + "logits/chosen": -1.4013619422912598, + "logits/rejected": -1.405015468597412, + "logps/chosen": -302.94537353515625, + "logps/rejected": -262.5538635253906, + "loss": 0.4931, + "metrics/advantage_var": 99.6611557006836, + "rewards/accuracies": 0.7734375, + "rewards/chosen": 0.9857921600341797, + "rewards/margins": 0.8826519250869751, + "rewards/rejected": 0.1031401976943016, + "stability/repetition_rate_mean": 0.8062499761581421, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.7644531726837158, + "step": 540 + }, + { + "epoch": 0.5937120496559168, + "grad_norm": 15.281890869140625, + "learning_rate": 2.134047147659583e-07, + "logits/chosen": -1.3965346813201904, + "logits/rejected": -1.3893383741378784, + "logps/chosen": -309.70013427734375, + "logps/rejected": -264.7682189941406, + "loss": 0.4744, + "metrics/advantage_var": 104.08345794677734, + "rewards/accuracies": 0.7671875357627869, + "rewards/chosen": 1.062072992324829, + "rewards/margins": 0.9215413928031921, + "rewards/rejected": 0.140531525015831, + "stability/repetition_rate_mean": 0.8472656011581421, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.9962890148162842, + "step": 550 + }, + { + "epoch": 0.6045068141951153, + "grad_norm": 19.41432762145996, + "learning_rate": 2.0411707401248403e-07, + "logits/chosen": -1.4111377000808716, + "logits/rejected": -1.4183025360107422, + "logps/chosen": -310.02789306640625, + "logps/rejected": -263.0741882324219, + "loss": 0.5088, + "metrics/advantage_var": 106.92705535888672, + "rewards/accuracies": 0.7328125238418579, + "rewards/chosen": 1.0473458766937256, + "rewards/margins": 0.841526210308075, + "rewards/rejected": 0.2058195173740387, + "stability/repetition_rate_mean": 0.784960925579071, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 2.4849610328674316, + "step": 560 + }, + { + "epoch": 0.6153015787343139, + "grad_norm": 15.733675956726074, + "learning_rate": 1.9489453122143603e-07, + "logits/chosen": -1.4051156044006348, + "logits/rejected": -1.4276247024536133, + "logps/chosen": -312.1006164550781, + "logps/rejected": -254.21788024902344, + "loss": 0.4437, + "metrics/advantage_var": 103.9989013671875, + "rewards/accuracies": 0.793749988079071, + "rewards/chosen": 1.1061866283416748, + "rewards/margins": 0.9930472373962402, + "rewards/rejected": 0.11313938349485397, + "stability/repetition_rate_mean": 0.828906238079071, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 0.817578136920929, + "step": 570 + }, + { + "epoch": 0.6260963432735124, + "grad_norm": 17.128223419189453, + "learning_rate": 1.8575017118919928e-07, + "logits/chosen": -1.4090861082077026, + "logits/rejected": -1.4279987812042236, + "logps/chosen": -319.3863830566406, + "logps/rejected": -252.8662109375, + "loss": 0.5064, + "metrics/advantage_var": 100.0505142211914, + "rewards/accuracies": 0.746874988079071, + "rewards/chosen": 0.9926168322563171, + "rewards/margins": 0.8279793858528137, + "rewards/rejected": 0.16463755071163177, + "stability/repetition_rate_mean": 0.7662109136581421, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.6736328601837158, + "step": 580 + }, + { + "epoch": 0.6368911078127109, + "grad_norm": 10.917092323303223, + "learning_rate": 1.7669696778770938e-07, + "logits/chosen": -1.4007326364517212, + "logits/rejected": -1.4263814687728882, + "logps/chosen": -316.9762268066406, + "logps/rejected": -245.96548461914062, + "loss": 0.4494, + "metrics/advantage_var": 108.5511245727539, + "rewards/accuracies": 0.800000011920929, + "rewards/chosen": 1.0922644138336182, + "rewards/margins": 1.006994605064392, + "rewards/rejected": 0.08526992052793503, + "stability/repetition_rate_mean": 0.8466796875, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.351171851158142, + "step": 590 + }, + { + "epoch": 0.6476858723519093, + "grad_norm": 12.8851318359375, + "learning_rate": 1.6774776555733028e-07, + "logits/chosen": -1.382874846458435, + "logits/rejected": -1.3788057565689087, + "logps/chosen": -317.29132080078125, + "logps/rejected": -270.30157470703125, + "loss": 0.479, + "metrics/advantage_var": 106.93010711669922, + "rewards/accuracies": 0.768750011920929, + "rewards/chosen": 1.0857884883880615, + "rewards/margins": 0.9378126263618469, + "rewards/rejected": 0.14797575771808624, + "stability/repetition_rate_mean": 0.8042968511581421, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 2.7417969703674316, + "step": 600 + }, + { + "epoch": 0.6476858723519093, + "eval_logits/chosen": -1.3723105192184448, + "eval_logits/rejected": -1.3827242851257324, + "eval_logps/chosen": -316.3534240722656, + "eval_logps/rejected": -254.0533447265625, + "eval_loss": 0.47359293699264526, + "eval_metrics/advantage_var": 112.27565002441406, + "eval_rewards/accuracies": 0.7823232412338257, + "eval_rewards/chosen": 1.046919584274292, + "eval_rewards/margins": 0.9653631448745728, + "eval_rewards/rejected": 0.08155640214681625, + "eval_runtime": 271.831, + "eval_samples_per_second": 14.546, + "eval_stability/repetition_rate_mean": 0.8873046636581421, + "eval_stability/response_length_mean": 512.0, + "eval_stability/response_length_std": 0.0, + "eval_stability/response_length_var": 0.0, + "eval_stability/token_entropy_mean": 2.07421875, + "eval_steps_per_second": 1.821, + "step": 600 + }, + { + "epoch": 0.6584806368911078, + "grad_norm": 17.53192710876465, + "learning_rate": 1.5891526148322593e-07, + "logits/chosen": -1.3868850469589233, + "logits/rejected": -1.386324167251587, + "logps/chosen": -337.97906494140625, + "logps/rejected": -273.7126159667969, + "loss": 0.4827, + "metrics/advantage_var": 108.11744689941406, + "rewards/accuracies": 0.785937488079071, + "rewards/chosen": 1.0058691501617432, + "rewards/margins": 0.8874250650405884, + "rewards/rejected": 0.11844401806592941, + "stability/repetition_rate_mean": 0.744921863079071, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.9982421398162842, + "step": 610 + }, + { + "epoch": 0.6692754014303063, + "grad_norm": 12.167177200317383, + "learning_rate": 1.5021198698108036e-07, + "logits/chosen": -1.37397038936615, + "logits/rejected": -1.378446102142334, + "logps/chosen": -317.61688232421875, + "logps/rejected": -255.9473114013672, + "loss": 0.494, + "metrics/advantage_var": 114.5400390625, + "rewards/accuracies": 0.7734375, + "rewards/chosen": 1.0009812116622925, + "rewards/margins": 0.914712131023407, + "rewards/rejected": 0.0862690731883049, + "stability/repetition_rate_mean": 0.8783203363418579, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 2.2964844703674316, + "step": 620 + }, + { + "epoch": 0.6800701659695048, + "grad_norm": 17.123615264892578, + "learning_rate": 1.416502901177251e-07, + "logits/chosen": -1.3341145515441895, + "logits/rejected": -1.3377490043640137, + "logps/chosen": -311.6447448730469, + "logps/rejected": -254.44578552246094, + "loss": 0.4832, + "metrics/advantage_var": 98.87296295166016, + "rewards/accuracies": 0.7640625238418579, + "rewards/chosen": 0.9517079591751099, + "rewards/margins": 0.8569992184638977, + "rewards/rejected": 0.09470874816179276, + "stability/repetition_rate_mean": 0.8720703125, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.377539038658142, + "step": 630 + }, + { + "epoch": 0.6908649305087032, + "grad_norm": 12.504801750183105, + "learning_rate": 1.3324231809189983e-07, + "logits/chosen": -1.3613817691802979, + "logits/rejected": -1.3694230318069458, + "logps/chosen": -319.6551818847656, + "logps/rejected": -258.7291564941406, + "loss": 0.4615, + "metrics/advantage_var": 120.3536376953125, + "rewards/accuracies": 0.800000011920929, + "rewards/chosen": 1.0257498025894165, + "rewards/margins": 1.0272339582443237, + "rewards/rejected": -0.0014841229422017932, + "stability/repetition_rate_mean": 0.7818359136581421, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.7732422351837158, + "step": 640 + }, + { + "epoch": 0.7016596950479018, + "grad_norm": 14.149001121520996, + "learning_rate": 1.2500000000000005e-07, + "logits/chosen": -1.322688341140747, + "logits/rejected": -1.3375654220581055, + "logps/chosen": -292.4341735839844, + "logps/rejected": -252.3300323486328, + "loss": 0.4443, + "metrics/advantage_var": 113.12126922607422, + "rewards/accuracies": 0.800000011920929, + "rewards/chosen": 0.9646196365356445, + "rewards/margins": 1.0090590715408325, + "rewards/rejected": -0.04443943500518799, + "stability/repetition_rate_mean": 0.850390613079071, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.5888671875, + "step": 650 + }, + { + "epoch": 0.7124544595871003, + "grad_norm": 14.957926750183105, + "learning_rate": 1.1693502991126608e-07, + "logits/chosen": -1.3551677465438843, + "logits/rejected": -1.361363410949707, + "logps/chosen": -333.7082214355469, + "logps/rejected": -250.5390625, + "loss": 0.461, + "metrics/advantage_var": 120.99027252197266, + "rewards/accuracies": 0.7890625, + "rewards/chosen": 1.0033434629440308, + "rewards/margins": 1.0358381271362305, + "rewards/rejected": -0.03249470144510269, + "stability/repetition_rate_mean": 0.775585949420929, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 2.3021483421325684, + "step": 660 + }, + { + "epoch": 0.7232492241262988, + "grad_norm": 19.125764846801758, + "learning_rate": 1.0905885027642483e-07, + "logits/chosen": -1.3491506576538086, + "logits/rejected": -1.3566621541976929, + "logps/chosen": -295.5746765136719, + "logps/rejected": -237.2896728515625, + "loss": 0.477, + "metrics/advantage_var": 120.28877258300781, + "rewards/accuracies": 0.78125, + "rewards/chosen": 0.9816705584526062, + "rewards/margins": 0.9865358471870422, + "rewards/rejected": -0.0048652635887265205, + "stability/repetition_rate_mean": 0.785937488079071, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.6103515625, + "step": 670 + }, + { + "epoch": 0.7340439886654972, + "grad_norm": 15.960895538330078, + "learning_rate": 1.0138263569332267e-07, + "logits/chosen": -1.372681975364685, + "logits/rejected": -1.3638715744018555, + "logps/chosen": -314.92364501953125, + "logps/rejected": -262.690673828125, + "loss": 0.4736, + "metrics/advantage_var": 117.98992156982422, + "rewards/accuracies": 0.7796875238418579, + "rewards/chosen": 1.0467315912246704, + "rewards/margins": 0.9876863360404968, + "rewards/rejected": 0.059045251458883286, + "stability/repetition_rate_mean": 0.7417968511581421, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.3708984851837158, + "step": 680 + }, + { + "epoch": 0.7448387532046957, + "grad_norm": 13.511040687561035, + "learning_rate": 9.391727705258502e-08, + "logits/chosen": -1.3565599918365479, + "logits/rejected": -1.3600114583969116, + "logps/chosen": -320.1853942871094, + "logps/rejected": -271.3731384277344, + "loss": 0.4613, + "metrics/advantage_var": 122.61201477050781, + "rewards/accuracies": 0.785937488079071, + "rewards/chosen": 1.0267409086227417, + "rewards/margins": 1.0403625965118408, + "rewards/rejected": -0.01362178660929203, + "stability/repetition_rate_mean": 0.8603515625, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.596289038658142, + "step": 690 + }, + { + "epoch": 0.7556335177438942, + "grad_norm": 10.739056587219238, + "learning_rate": 8.667336608579487e-08, + "logits/chosen": -1.3605684041976929, + "logits/rejected": -1.3892539739608765, + "logps/chosen": -318.6557312011719, + "logps/rejected": -261.914794921875, + "loss": 0.4775, + "metrics/advantage_var": 106.7211685180664, + "rewards/accuracies": 0.801562488079071, + "rewards/chosen": 0.9467880129814148, + "rewards/margins": 0.9349954724311829, + "rewards/rejected": 0.011792674660682678, + "stability/repetition_rate_mean": 0.8111327886581421, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 2.692675828933716, + "step": 700 + }, + { + "epoch": 0.7664282822830927, + "grad_norm": 15.086265563964844, + "learning_rate": 7.96611803381127e-08, + "logits/chosen": -1.3547624349594116, + "logits/rejected": -1.3488959074020386, + "logps/chosen": -303.3160095214844, + "logps/rejected": -258.77264404296875, + "loss": 0.4735, + "metrics/advantage_var": 115.3608627319336, + "rewards/accuracies": 0.796875, + "rewards/chosen": 0.9548945426940918, + "rewards/margins": 0.9802401661872864, + "rewards/rejected": -0.02534562349319458, + "stability/repetition_rate_mean": 0.840039074420929, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 2.209765672683716, + "step": 710 + }, + { + "epoch": 0.7772230468222912, + "grad_norm": 16.009767532348633, + "learning_rate": 7.28906685866599e-08, + "logits/chosen": -1.3702967166900635, + "logits/rejected": -1.3795828819274902, + "logps/chosen": -314.6918640136719, + "logps/rejected": -246.10391235351562, + "loss": 0.4632, + "metrics/advantage_var": 128.08262634277344, + "rewards/accuracies": 0.770312488079071, + "rewards/chosen": 1.0151904821395874, + "rewards/margins": 1.0434449911117554, + "rewards/rejected": -0.02825441025197506, + "stability/repetition_rate_mean": 0.8203125, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 0.8656250238418579, + "step": 720 + }, + { + "epoch": 0.7880178113614896, + "grad_norm": 17.335712432861328, + "learning_rate": 6.637143672535281e-08, + "logits/chosen": -1.3211309909820557, + "logits/rejected": -1.3452644348144531, + "logps/chosen": -312.05279541015625, + "logps/rejected": -256.790283203125, + "loss": 0.4905, + "metrics/advantage_var": 118.5810317993164, + "rewards/accuracies": 0.78125, + "rewards/chosen": 1.0083658695220947, + "rewards/margins": 0.9445858001708984, + "rewards/rejected": 0.06377997249364853, + "stability/repetition_rate_mean": 0.7437499761581421, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 2.055468797683716, + "step": 730 + }, + { + "epoch": 0.7988125759006882, + "grad_norm": 10.28477668762207, + "learning_rate": 6.01127341362138e-08, + "logits/chosen": -1.339066505432129, + "logits/rejected": -1.343850016593933, + "logps/chosen": -314.6363220214844, + "logps/rejected": -265.0621032714844, + "loss": 0.4786, + "metrics/advantage_var": 117.64568328857422, + "rewards/accuracies": 0.7828125357627869, + "rewards/chosen": 0.9195186495780945, + "rewards/margins": 0.9779030680656433, + "rewards/rejected": -0.05838441848754883, + "stability/repetition_rate_mean": 0.775195300579071, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.513671875, + "step": 740 + }, + { + "epoch": 0.8096073404398867, + "grad_norm": 19.894166946411133, + "learning_rate": 5.412344056649526e-08, + "logits/chosen": -1.3286861181259155, + "logits/rejected": -1.3161166906356812, + "logps/chosen": -323.9461364746094, + "logps/rejected": -263.8832702636719, + "loss": 0.4702, + "metrics/advantage_var": 130.6468048095703, + "rewards/accuracies": 0.78125, + "rewards/chosen": 1.004286766052246, + "rewards/margins": 1.0564974546432495, + "rewards/rejected": -0.05221066623926163, + "stability/repetition_rate_mean": 0.825390636920929, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.7333984375, + "step": 750 + }, + { + "epoch": 0.8204021049790852, + "grad_norm": 17.493206024169922, + "learning_rate": 4.841205353023714e-08, + "logits/chosen": -1.316092848777771, + "logits/rejected": -1.3103103637695312, + "logps/chosen": -308.4322814941406, + "logps/rejected": -251.6645965576172, + "loss": 0.4974, + "metrics/advantage_var": 116.90795135498047, + "rewards/accuracies": 0.7718750238418579, + "rewards/chosen": 0.985223114490509, + "rewards/margins": 0.9163877367973328, + "rewards/rejected": 0.0688353106379509, + "stability/repetition_rate_mean": 0.779101550579071, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.017578125, + "step": 760 + }, + { + "epoch": 0.8311968695182836, + "grad_norm": 19.531171798706055, + "learning_rate": 4.298667625212904e-08, + "logits/chosen": -1.3329784870147705, + "logits/rejected": -1.3454676866531372, + "logps/chosen": -312.3675842285156, + "logps/rejected": -260.13189697265625, + "loss": 0.4839, + "metrics/advantage_var": 117.96380615234375, + "rewards/accuracies": 0.776562511920929, + "rewards/chosen": 0.9914433360099792, + "rewards/margins": 0.9715946316719055, + "rewards/rejected": 0.01984873227775097, + "stability/repetition_rate_mean": 0.8814452886581421, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.833984375, + "step": 770 + }, + { + "epoch": 0.8419916340574821, + "grad_norm": 13.06292724609375, + "learning_rate": 3.785500617078424e-08, + "logits/chosen": -1.3594963550567627, + "logits/rejected": -1.3589779138565063, + "logps/chosen": -339.4462585449219, + "logps/rejected": -283.0810546875, + "loss": 0.451, + "metrics/advantage_var": 135.08409118652344, + "rewards/accuracies": 0.8109375238418579, + "rewards/chosen": 1.0986813306808472, + "rewards/margins": 1.1291017532348633, + "rewards/rejected": -0.03042042814195156, + "stability/repetition_rate_mean": 0.795703113079071, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.575585961341858, + "step": 780 + }, + { + "epoch": 0.8527863985966806, + "grad_norm": 12.330864906311035, + "learning_rate": 3.3024324017737554e-08, + "logits/chosen": -1.341722846031189, + "logits/rejected": -1.332808256149292, + "logps/chosen": -314.4818115234375, + "logps/rejected": -266.3319396972656, + "loss": 0.4454, + "metrics/advantage_var": 123.73223876953125, + "rewards/accuracies": 0.809374988079071, + "rewards/chosen": 1.0409488677978516, + "rewards/margins": 1.057476282119751, + "rewards/rejected": -0.016527360305190086, + "stability/repetition_rate_mean": 0.8095703125, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.439843773841858, + "step": 790 + }, + { + "epoch": 0.8635811631358791, + "grad_norm": 15.701562881469727, + "learning_rate": 2.850148348765921e-08, + "logits/chosen": -1.3520551919937134, + "logits/rejected": -1.355186939239502, + "logps/chosen": -304.0136413574219, + "logps/rejected": -258.58209228515625, + "loss": 0.4918, + "metrics/advantage_var": 115.4345703125, + "rewards/accuracies": 0.770312488079071, + "rewards/chosen": 0.9924200177192688, + "rewards/margins": 0.9020625948905945, + "rewards/rejected": 0.09035740047693253, + "stability/repetition_rate_mean": 0.9134765863418579, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.61376953125, + "step": 800 + }, + { + "epoch": 0.8743759276750775, + "grad_norm": 9.2330322265625, + "learning_rate": 2.4292901514442327e-08, + "logits/chosen": -1.3454469442367554, + "logits/rejected": -1.3386812210083008, + "logps/chosen": -321.5726013183594, + "logps/rejected": -258.95526123046875, + "loss": 0.4636, + "metrics/advantage_var": 119.41340637207031, + "rewards/accuracies": 0.7875000238418579, + "rewards/chosen": 1.0107624530792236, + "rewards/margins": 0.9988824725151062, + "rewards/rejected": 0.011880074627697468, + "stability/repetition_rate_mean": 0.8667968511581421, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.4040038585662842, + "step": 810 + }, + { + "epoch": 0.885170692214276, + "grad_norm": 10.787253379821777, + "learning_rate": 2.0404549166959718e-08, + "logits/chosen": -1.300979495048523, + "logits/rejected": -1.3161647319793701, + "logps/chosen": -308.5863037109375, + "logps/rejected": -254.77041625976562, + "loss": 0.4683, + "metrics/advantage_var": 121.4715347290039, + "rewards/accuracies": 0.7796875238418579, + "rewards/chosen": 1.0170072317123413, + "rewards/margins": 0.9836593866348267, + "rewards/rejected": 0.03334783762693405, + "stability/repetition_rate_mean": 0.9224609136581421, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.8826172351837158, + "step": 820 + }, + { + "epoch": 0.8959654567534746, + "grad_norm": 13.196191787719727, + "learning_rate": 1.6841943177406976e-08, + "logits/chosen": -1.3147996664047241, + "logits/rejected": -1.3255729675292969, + "logps/chosen": -319.1125793457031, + "logps/rejected": -274.5699462890625, + "loss": 0.4925, + "metrics/advantage_var": 126.98355865478516, + "rewards/accuracies": 0.7828125357627869, + "rewards/chosen": 0.9902805685997009, + "rewards/margins": 1.020569086074829, + "rewards/rejected": -0.030288374051451683, + "stability/repetition_rate_mean": 0.8330078125, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 2.1563477516174316, + "step": 830 + }, + { + "epoch": 0.9067602212926731, + "grad_norm": 11.895269393920898, + "learning_rate": 1.3610138114250519e-08, + "logits/chosen": -1.327235221862793, + "logits/rejected": -1.343729853630066, + "logps/chosen": -327.689697265625, + "logps/rejected": -261.86480712890625, + "loss": 0.4735, + "metrics/advantage_var": 126.14949035644531, + "rewards/accuracies": 0.765625, + "rewards/chosen": 1.0660076141357422, + "rewards/margins": 1.0003070831298828, + "rewards/rejected": 0.06570061296224594, + "stability/repetition_rate_mean": 0.8158203363418579, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.4929687976837158, + "step": 840 + }, + { + "epoch": 0.9175549858318716, + "grad_norm": 15.15986156463623, + "learning_rate": 1.0713719210886928e-08, + "logits/chosen": -1.3229340314865112, + "logits/rejected": -1.3207443952560425, + "logps/chosen": -324.7861328125, + "logps/rejected": -261.70849609375, + "loss": 0.4859, + "metrics/advantage_var": 124.1085433959961, + "rewards/accuracies": 0.776562511920929, + "rewards/chosen": 1.053748369216919, + "rewards/margins": 0.9940328598022461, + "rewards/rejected": 0.05971544608473778, + "stability/repetition_rate_mean": 0.7544921636581421, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.3533203601837158, + "step": 850 + }, + { + "epoch": 0.92834975037107, + "grad_norm": 13.380340576171875, + "learning_rate": 8.156795860187027e-09, + "logits/chosen": -1.348737359046936, + "logits/rejected": -1.3422983884811401, + "logps/chosen": -336.0633850097656, + "logps/rejected": -262.0978088378906, + "loss": 0.4306, + "metrics/advantage_var": 125.40618133544922, + "rewards/accuracies": 0.8109375238418579, + "rewards/chosen": 1.0677509307861328, + "rewards/margins": 1.1280078887939453, + "rewards/rejected": -0.06025683507323265, + "stability/repetition_rate_mean": 0.805468738079071, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 2.556640625, + "step": 860 + }, + { + "epoch": 0.9391445149102685, + "grad_norm": 15.88653564453125, + "learning_rate": 5.942995784154692e-09, + "logits/chosen": -1.3338909149169922, + "logits/rejected": -1.3578466176986694, + "logps/chosen": -307.34771728515625, + "logps/rejected": -260.82586669921875, + "loss": 0.4598, + "metrics/advantage_var": 123.701904296875, + "rewards/accuracies": 0.7953125238418579, + "rewards/chosen": 1.0478211641311646, + "rewards/margins": 1.0490620136260986, + "rewards/rejected": -0.0012408018810674548, + "stability/repetition_rate_mean": 0.864453136920929, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.4718749523162842, + "step": 870 + }, + { + "epoch": 0.949939279449467, + "grad_norm": 14.681868553161621, + "learning_rate": 4.075459886973082e-09, + "logits/chosen": -1.322386622428894, + "logits/rejected": -1.3134368658065796, + "logps/chosen": -288.3506774902344, + "logps/rejected": -259.43109130859375, + "loss": 0.4837, + "metrics/advantage_var": 120.60890197753906, + "rewards/accuracies": 0.7750000357627869, + "rewards/chosen": 0.9852436184883118, + "rewards/margins": 0.9725152850151062, + "rewards/rejected": 0.012728266417980194, + "stability/repetition_rate_mean": 0.8818359375, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.583984375, + "step": 880 + }, + { + "epoch": 0.9607340439886655, + "grad_norm": 16.591888427734375, + "learning_rate": 2.556837798739886e-09, + "logits/chosen": -1.3387622833251953, + "logits/rejected": -1.34397554397583, + "logps/chosen": -314.2873229980469, + "logps/rejected": -257.3379821777344, + "loss": 0.4647, + "metrics/advantage_var": 120.80268859863281, + "rewards/accuracies": 0.8109375238418579, + "rewards/chosen": 0.9938045740127563, + "rewards/margins": 0.9979391098022461, + "rewards/rejected": -0.0041345953941345215, + "stability/repetition_rate_mean": 0.8443359136581421, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 2.6566405296325684, + "step": 890 + }, + { + "epoch": 0.9715288085278639, + "grad_norm": 13.192713737487793, + "learning_rate": 1.3892841162143899e-09, + "logits/chosen": -1.3134535551071167, + "logits/rejected": -1.3294223546981812, + "logps/chosen": -304.279541015625, + "logps/rejected": -257.1634216308594, + "loss": 0.455, + "metrics/advantage_var": 119.05987548828125, + "rewards/accuracies": 0.785937488079071, + "rewards/chosen": 0.9897605776786804, + "rewards/margins": 1.0290673971176147, + "rewards/rejected": -0.039306994527578354, + "stability/repetition_rate_mean": 0.7369140386581421, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.3954589366912842, + "step": 900 + }, + { + "epoch": 0.9715288085278639, + "eval_logits/chosen": -1.3294035196304321, + "eval_logits/rejected": -1.3341506719589233, + "eval_logps/chosen": -316.4003601074219, + "eval_logps/rejected": -254.81178283691406, + "eval_loss": 0.46732690930366516, + "eval_metrics/advantage_var": 125.62010955810547, + "eval_rewards/accuracies": 0.7828283309936523, + "eval_rewards/chosen": 1.0422265529632568, + "eval_rewards/margins": 1.036514401435852, + "eval_rewards/rejected": 0.005712195765227079, + "eval_runtime": 269.7729, + "eval_samples_per_second": 14.657, + "eval_stability/repetition_rate_mean": 0.811718761920929, + "eval_stability/response_length_mean": 512.0, + "eval_stability/response_length_std": 0.0, + "eval_stability/response_length_var": 0.0, + "eval_stability/token_entropy_mean": 1.127832055091858, + "eval_steps_per_second": 1.835, + "step": 900 + }, + { + "epoch": 0.9823235730670625, + "grad_norm": 11.817096710205078, + "learning_rate": 5.744553459100243e-10, + "logits/chosen": -1.3120925426483154, + "logits/rejected": -1.3330440521240234, + "logps/chosen": -324.1401062011719, + "logps/rejected": -261.5168762207031, + "loss": 0.4964, + "metrics/advantage_var": 119.01836395263672, + "rewards/accuracies": 0.7562500238418579, + "rewards/chosen": 0.9547117352485657, + "rewards/margins": 0.9206423163414001, + "rewards/rejected": 0.03406943380832672, + "stability/repetition_rate_mean": 0.875195324420929, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 1.468652367591858, + "step": 910 + }, + { + "epoch": 0.993118337606261, + "grad_norm": 19.269649505615234, + "learning_rate": 1.1350755386951849e-10, + "logits/chosen": -1.3584011793136597, + "logits/rejected": -1.3463481664657593, + "logps/chosen": -329.8288879394531, + "logps/rejected": -261.056640625, + "loss": 0.4515, + "metrics/advantage_var": 127.2206802368164, + "rewards/accuracies": 0.784375011920929, + "rewards/chosen": 1.044679045677185, + "rewards/margins": 1.0371487140655518, + "rewards/rejected": 0.007530394475907087, + "stability/repetition_rate_mean": 0.861328125, + "stability/response_length_mean": 512.0, + "stability/response_length_std": 0.0, + "stability/response_length_var": 0.0, + "stability/token_entropy_mean": 2.8033204078674316, + "step": 920 + }, + { + "epoch": 1.0, + "step": 927, + "total_flos": 1.761935585720664e+18, + "train_loss": 0.5203882457111775, + "train_runtime": 14354.8151, + "train_samples_per_second": 4.13, + "train_steps_per_second": 0.065 + } + ], + "logging_steps": 10, + "max_steps": 927, + "num_input_tokens_seen": 0, + "num_train_epochs": 1, + "save_steps": 500, + "stateful_callbacks": { + "TrainerControl": { + "args": { + "should_epoch_stop": false, + "should_evaluate": false, + "should_log": false, + "should_save": false, + "should_training_stop": false + }, + "attributes": {} + } + }, + "total_flos": 1.761935585720664e+18, + "train_batch_size": 8, + "trial_name": null, + "trial_params": null +} diff --git a/training_args.bin b/training_args.bin new file mode 100644 index 0000000..cfa2c50 --- /dev/null +++ b/training_args.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:b0393bae99a1b9894faa98e056a587dea8db45430d4deb4e7d04eba3f18e2913 +size 8145 diff --git a/training_eval_loss.png b/training_eval_loss.png new file mode 100644 index 0000000000000000000000000000000000000000..244d4ed4061cec1bdd46e10aa4d86780d2eed93d GIT binary patch literal 34822 zcmd?Rg>Grb7$uM376;j^g|Bs@0>UGUTf{O&qHlZRT4r5LIgobuB$2QA_!&}f?!PJ zP|)RnT_ND+X)pM!BhL*+A#hhS@1HGt$A4iOtKTex1{#Td)K=Z>6|{@lKo7ehj=ql`_BO_9f-NK$u! zGw~|r_rQtX^}c=8o~|cV>~ItW5&SO7sr@hW`qL1 zDh0U0l;KN1ihvEiO?qa9sRrNL+NC0t@VycJ|9^fw(q6mOb;B`x$SDjsTPF{TV1+igalK^6ujDc|s!xsy$ zLRs?i@(e2-Z^t^H4HVo`yLnT5?C|-re!|%IuLkDkEQh-*(G=%ZESth{5<6|@NekNS z?Cov7zrOCjQc^8s*%)RV8ufg~>vF&jkA&Og;~OagP5u3_dK9VRPBh~a6LHITD~+8e zK2ZnmueS{r8T4l>;Sn=R5R+Xw7E?{U!FUMvJ^m^2m>dx92EfEc$kO}eHeZ}lX zi_nwEz6{xP*>i<>RE-kzRb#HAD~Gm5-@kuH5cRz8JxL!j`Aw=UN6M_UdCsACWghZ( zj^WDZKeHVz!^5a+?Qx7GCAv24j}pT`R{H%YzxAWf}G)VUe zT{Cla6|lCp-dwAmV(5b5$;rtrhv-JJ(lqWoo6zASp=wk~l@FHD%#?fB)urCj=Hlj- zFcoq{f)JnBO$KgU4%+JEJ~-NF=+9LptKA!QI#|q2*o5z~kXCD9Q!_JR_vx!WFQtDh zCLdiYtqp(qk}2qL>21{e<+b{=(<9hT)O%}Vc&e(Z8tD=wepA8KI*)Ifu_D$sHh=yu zygGmRGILT=lK$@N<3OO^KGQdCl6yuF}rLnrCV1XtP|G-zyxg;tl-bgT(`J~5sp-F;(+Y;a$2D}Yh8_#U zR8Oz1#i55uK|z5>P_U!$c9HvZBgV&%A1!B^BNzK~JNVa%s#+%o2dPs#u{?V|krMi}>T1Rj}Uwzg&0(~BQh-hI{>wFnNS zx?kAQKNY;s{LZun6AusXF`Y1`=$#&+<*uyZl|QiD)?-yJNFn9a-5+lTYrdju+Hkx@ zBqAa*y|nZYkHsH>Js%nu09Qq*aW;QRI`8rO3q|emR=1kEy5gNXZ)P@*9#LP)>UY>& zt@!$@Zhuk!=%a%gwv7n=NEYMT3~g zdfmQxi;UKl6ER#8h6i)qDYJWHZmM>6c~*>XH8Ywa(8leV)J=4-1QJ7Fgj4d#Dji~n zSmD^fZs^gPBr%;3l9ra1D&xa@e0;q5O^FQsl#yyTi-?8Ao-|R&aE%F9PGgeJt6CrK zEPZsJ!TjX25=F(Wi6G6*&1H7o&l!$z3ti7K#I?KUitN^kzn%E(muph(D&@OM$940? zgTVC~yjQ_{^q>4T;-5Y}hunUsrl)sqsKf+~!_(y*ED`E?&G4BX>*LbND`FR-V7FQ? ze#?$J6Ev^=IP{=ixIERfo^g9ybS}W5=iVXgGi`nSC}ErSfitDz$bwA78(DWBnzOUHp(yV(!z#C!b62%RoV_G>m#eUwXXS}3eEOd8l_vEJOC+~~6 z#B^a0ID1lsvHZq8@Fs({Z;l6U)Tt~uK(b1e^%LOW;Mn|fK4BUj%75;ef#bx~c#YSe z=?F5#JYB1yVx!Hit>%M2v%+5UJq$k8&OgJmm7<&5+Hjhhn$YzgA0H<^vw;5z3JOYm z^(q18^E@~A+ja@xjmbEO?`hrwj$SszahE6GzZY4ZtYiG_x6w|eC3ipMAo}AD5jKaAy{W0Hay=qU^l79%XXZG}Hql5cZknZdY=T+h1_JNf?Ui<+b zzsY-Vzrl7kP9b3sQ-hS+j7D-hhPXF6m&3~QjQspbKp2_RXG4Ll@NLOkQCax` z97X|1fOPzfBDOK#;1Lzbu@y@6iFlu>(_IOv)yY^~bifEJgQOC$Z?k+)w5@mLt{4NH zT~!EK(b`5vcX_n5v}l=_nIj=~T!mjA`RrGUT$S=(Ozhv|y>uz^$rH-tm4WsFI&1~< z$>4o6jIhLv46_Z7Nk_hL?d_oS!)?*s00#}{gv)!WR&|b*C#yH>SR6k;FAPnnb{V_F z)7{xg;q2`EK)~!1K7{n5Y`H5}EXpb>sAvSugKiuZO5EGBor#xSCztVC=Yw#H4E}knnE*mAf4r%b z`w6`kp*tDx>h8vYl-3eb=(9d+1@mgS*`}_CrE{m5> zEo^ATd-rOxgW4WZha2+Itbd#(%`PtP(XJ2Jb;JmBhX7|HGe2rAwEL-o#u>x;j;5w2 zB(Ik;~-(bwz*kR>2iS{AwND^1ea=(Wf5T!To~L_vAZKQNK1wq~ zhW*l|Zih1g0Rem>B2l?V4bOrx8qpJsrd%|ZV`5@%9&djgcIa&Q=~P-51%Q_d5Txh_ zY^>Y4>d|DZt_OuBw?_s}I_ErF&eu9Zgq9Lxh?}9XQ#vYIbF=n&Rh^D!;=MdT5PY=P z_MG1YL0||`XBQVIIm`?|ve*hjykoWZL|d&r;+8_u#{`7Yn=Z-N1&1dRAeM>abytB( zbj3>~LXQ1&r>G(o?_W>mvI20(!_SZN?W5NZ@)}b#lc72K+sba#7Nd#qiYQ#%l5367 z30WdL0RW>Htp>U-TQ(v{d1Xa zv{t{rB)R+gMnN{O4?fb?)wTZa>oyOwHa>2;=q;nh`Gl*~V#3tIWFjmK0fhT$GMJN# z3lkZ7XBImZdd3{iMtAC9XJ?0zzihjj$|5Fv+eY%OPRZ>C3$xqc=|=DMi}5Tm5yJ@A3rlf5x?ivc`v{lIteA^}8oi6D!y zDcoE83mY32HjmPlSJsyYi@4TGs~R4{SE70zI&lcyI}!zQ2am zO-zU1nMJ&P`?i0I3@NLuj4UlJWjD`S?stM%?{p$v{e0Bgq34f&(b~pUOG`Fy8D?1Z zZw0sBs$`@`)$V-1A$4zybN%y%{KuLac3xh>{c$g{H(IaEog^dECxZHlLWg{wO&x!} z9UN5oY{I{%QW!nM8c4d43%@Mvkrvp-C>&u7-ulwj6|VVK^zP?MAI*}}2<>6+miBiR zC*3AvB!v(Hn}YR13mIj7`GA@kIAy@$MXo90`txVg|7l(r=*vOAvI+}%yo-`}sMq0tJbpv-T>T<&D&$HCOuY4pg*2rk~j#IdYiFl!;) z`&5bJ8zwIojk@(>9N%KaQ0I#2TH`VTz(|(G?WE%r;@wc<1rbqw@LsJH#IetA)y{+1hca? zV)iMf0v)NsHbQrL=ujfH`R7lQj58}MP6y=L>40WtA^f(${-R)Fa^|_>ziC*q;%r@`8~x^l?Jd?r=I zKx1P2-vb`5-Jc9pu>(B)AUPRD36EQ%$%g6T?!<4;13@RC;+h6HCwZ8A)XDv7dUK`) z}Ru&hsevz z11K$@*)Vf-z;H;GQ!B_Z=+Rq-89~-BNPC0B`*$< zGRtIXy^=SqxD%KC>>@Dhe*meZ$fw{^R6CPfVPe$Av-97bYpVS^GC5!1uiU%GEm0;N+*MJ)YK>%p%ZgRyuP7# zyb*dvl&AYpl{NSr5v{<3SFc##Su~J7RJIngBh?<14r+ctaIjodYU$);V)Lb;rf)38 zBIF@3LZ+4|5+#3sDfJsSk}@;nVQ-9Ws(t*4}ls_*4g$}!03)62_`nj-Kd4@cbQMqV@z1V2>ffCP!I4k;sn2{bd{i_)I~xHUkAsho81N*_ zt&*W39jFrvxJS&xssbrC5cJTQ0?tQHNr?%72j~TTUEqHElM6S9kEY(+5xvn!!(?S; zeGnCulb?^jGF)2v$8UISj1lN&D{!fqg@tGc?!eDle*B=4^<5PTO8xlk`S06B`c}ZD z@CgYOwYAB`7)T^s$74tsCC0!18KzdUiLV|#{=5AL4#DhPibWI~zM7g^W6rhM$ETAo z0$ep_=H?;+maq#7l0gsw)^`>35j2LoPJ9wSwH?R26<;Iq#@ug6ku&xC{l|~dC0_km z!NbcNuFTO?X4Qh|-OM7+>YLwzJ!x9&Pf=A>wK!UN34|fwO+@fKEwed5n{sna3#~bzL30h@uC9AaLODM;o;%1 zz5zFUmcMHg8m(dr(aa!$I=(o zcNVAdbE=3g-2tv`UsS^PK0SKQ|D3F9$Q_&s}P09?=N~z>TW6)6?&@WDb-Xl;v zl{k_t;iQ2cCaPg*4&$C2?W6M;rJ5v}B7QESpd%f4>bGy&|4u0cWtetA?vG#u`pfSn zcgMx_0ir)iPR`cjrJ$s=_9hwhWr3JOK}8h-{EM#6rY0u`6M(^0fB%m zFpX8a-6soZM#N-4eg4tRyzLhT!&%{K&OHpy^R$BIt(lhtiKm<@jpYCS$$mad7FFBC#@ZgnYjVgde48sJIBkDoV8;B4*9p zsX@saXmcII7NKTt8MGEb<$WE3162^F>J2krT(e=Zs9vCR6b(M~ew~*$SYyhO^r0s0 zQvTfo{8Yzh&z?oLwknT|jhz<}`JN+R!o|(a$i@EdhOO;yeyu!3Wm{LD-Ga}z@yJ+| zjf{*ky4$RU0pG@RZM?ns;wZI*nd&Nt7#x>cEZCD)qo->@tFv85tOQW>-CH#(Vn7 zp+Iu+(W6Jx3k&ui6HLx?h27LX88Hw@5yjx-;CL@IG#=b7!x}^dgBS__--Q!axV!hp z;cQon1{L4_NRvJ1s6zP=Teo1K@aRDN0a|@Ax)7%lv9q%iFm?aN^X{f5jLFGK(BFjp zcw8vaXL~ObP{)Fbcxs#=HDLi|A2A-##1BW{*H%}ZIWJsb7ZV$BJs|* zM3_KCqf=67x3;#7y_vmSQ#3lT6XC~%diwetaC`#l>aPt8FZgzPYanAh8SxG0V0MEz z&Yy=QK`JR(O=A|#hXpeGqMkZNR7e>a9+g)QGa*c|FuL_Vddz|-9tJ^g22@jt7het` z5}`U1#2#{LY8(p-3nn>#@;`t6EKb(RZf$SJEko&G4WE>>9rU2Gd)s&X@7-gEbc;9^ z->O?f`6j>sNjUSs?$sbJ_Lud-yud|G08L>U=tOMsL*TIJ%gEaDYGVDst*f5p(B1A9 z-Z-KYF6LEVQ-F2W!efZoG{)_;JV&yH3)p`tbHflZK>u<~F0 z;(}=a?98NJVvH6RT6%j)(3~Ey`XV_w0xjBX{q8gbNdD{BFQLFa=ik47(@}P%vkvOJ z9YxZbH*U>!&wwfnCxrq~Wy{~~1&{=%fjUCGqF-i($A{n&2>=$J_{E12PZl_uu;?iX$G!?*`;3w9!$ZlmDvi@lZI5W2Vsxn)=2;SRdKP-QZRX1 z-S^^rh#zJ+TdFJ{2Zu<7sC^&QtS}PQ&s@%-lRMxj{%dwNZg~%uf6@h_4k-jx$rpld zAnb9q!C|sGXo!x+3oE2)a|C3?5122ivGFQ=vK2g^nx>}2-LV0gk>UXrpN+*w)hscM z+v$ClXL-(iC+A6HH%KJ?43(AFp6hY6KbWk)^Ru)-jNxXSWQtzHihgcC-80FZJ)$@j ztiZq{U&jz53E8<`~H@asfuv@ zW6kEbN2OV@)l4>@j?hQU@huYWOqKRtAE$3P*-O{?3F-|Sr}R2gjT z>_C2W9x1~}mvnR8@-4V0jNv@XX-y#?@=;dt^2@BDW#N;R+%E$9>HpRW3silO^aw5) zyn9elA$ojrLUHcg11IgZH23 zvnhYEtS*)O#EXcDVbIsnxexdm5WB>P!MhS(9-gqey2~I6#dTe}bSWu4-ARm+7WrVz z@9F6Y^%bChwmid2-XQm&r)Iu4UD#z*3{bEFN78`d+bS2L@UWg94S>>34aQjC>)GVsRlOU^%GClu@pN=_ zKw(k=Ui_`p;tDW_=5Z^XOVd1-L>y2;aB?Sq;;CN#SD8V6gg!x=jC-6~XFHjNfI-1t3ZvoeF^Q+$Ac+3nkGm8}oqFQJH(;Dm(}E^n zqDJg*;S((L@!W1?Q6+khsfGzRw*(iYL{ee*GPJ@EuV1j18yF+Ib$FzNZTaJmUa@qd z?RpvfG(XM;(_!Z2nytULHlpIYi;M96J>l4Ew@Z`eg^?Y*Q;{mH`gf$Mm!-&qF-@~+ z!?=fEHRknLdqrP^kS)N@jsaD;t01FQxXE6+M1+0=F~7oXi~&w7x9hf7(`wUwd_CzL zz1$X?DJCWJg7$w;{R|>V`(t`h&^$m32M7dFEc=J}8Cx3&HpOP2X`lwxTkqo3h+UQe z;eqaZCzfa~X14bS1;-HS%!73)G2^-#rSpJ15+USQIt?r4TFpjWm`=YsN+Fwuy{{a= zUacIbwP)6z^jfaAewXRF+{m*H6HX3CZnQo;=GKs1Tg!xnN80*;fC}P7Vq#(#R4DLJ zr3fwO115rCY_&dK^QE`94JxRKz`!uDa4n&7qcWyfGu}uiraPB@GoC=GOzc}Czh%71L2h{%P zX#Mk7hqDV8E}+Q^@G1ojO%zJqj%q5oK=roQ)2#YfT_nl1_a_3skxcd0rjN#ZbPwd* z*+gj%h;UIFTuSf>Wj-tVJ+H2?HZ~-fxHX*kf-QgzHuR0>d`)PX*QzB-;q4C)Cdp%I z_?y9QK{7S~U=2X)pMF(V05sqjdMm@MQ}g1njmmiq?ehJLML6v z+#Cwr?r51=^6AoUK(?OQ&t;2%y2;-k-)f|B$o*-hQn9;x_ii{FzM{AH2juDjl-x2tE)T7`hq6M-(KXXIpy#kOW$;020B8AI=uE-76VxDj+$!2SgMHQH1hq z$wFb(E04;mpfgu~$k3X*BzhdBdJ)AO;_(*U9my+NzlQ%tkpF7hzf4In_@-7jTA*~z zdH2NJf7?}RB-K|I_*HAyvrED-cjK^fV2=P48ljT`8+c;#Yryv={(63#9RG|7nTR6TQfc{xZ1{)^es({ppT?I)mW4S_L7 z_OAzg%QO>TY;rF5R7X)k|Eab?Hm%CUmGN13pn zzp}D7QD)$}w3LjD_1~>I)SLl&;zNLxv{17V9wpambzu(9uK{x|?j5Si)MRP%H( z@?SW%4an>k@V{B6^YrpU?KMz7r!NtO(xCUoztG=XFtAw7Yf*M011_in;WmQvvZ9X z0~?8~BaTp-(8(E^Ne+If*2mvcyP;*dW)sYwTz14w(I2;JM`;QRSFt**2P^{;HfLtg z)^*UMe^m~f|MOP>fisy5?TBagI6c0X`~LOo!fN%uM@Q+V3;KABhlhv1pb`zLsY;zN z7Z(@9GqbvY-RFC%w?~6$HlgD43uSqLcmDwOw1z=YbV$Q*JTUzUJ;s1ZNGv2JlE+3z zf5D@)gGhs-pKw)6^AL5s9a8tU52qMqNsl}>Jq1oHcIBoZr+QN*sbS+W-Yp6h=kgeR zZx?GdDGSG991uUxrAtoV2QHCa-XTXtFD6-E;;VyMkICc@kjsI4%G%nAoj!#ozk#JN zRGvXK0KN4Ch(M3KP`AL-r%w?CwK;%THw*3n1S!#v1*kRki-O7$gFg%{GC|4bKJXBX z{6m}!VH;eQd%r1uFD$eS4p#R07?c>}D3GI`3ebM9g6i?SK#x~x+b3{%Vi@P%1qQkC zF|sM<`bQfHrb_mL_8N@jmh0ajpHb-Ey49a|gBH?eV_zR>;NEHzSg8o{@S;s7=f7nu zl{@rvpic)BRyOg;lW-95kAYM~{T_HK1G3QKU=i(l!&wMg)`8tox_x~jE{d2w9PZp^ zZ}le{mO+~J*jqIMSJv#i&+C}lgVFAg$YMZuX7(Gu|KP!cfY0GNEy{|FZiJuUL$Y)W z$~Dc$MrPx(ttb6Z#!ew1&Ua-B-O!gy%-z>Q@sqA7cw zq*OzBpbzvbHYg6=zkgrFERs(lBt)K+Ri3!gIF99V03A!y9Xq=jD1mf9eT&2_^ZSn< zVOw7zqtDm!FAU7QCZ>XxM;G)o! zg~j|l7Yxf9a)1G@EaByjl=Sr2)Kog4tG~eMr35lu+zIRDfB_*gOQ;{A*%idBj#oE0j|i9@o5J69wJ{E!wN7s*aQmM+6dCs)rA)H zcR&{!;`};*y?N#AZ-P}$H=|J(&ePkb_swWU{@ilr)qHdAsw;O}={6qwmyGif55Ige z^u$zqV})thATfpat+SILGBQ%d4yb07U8PQeUes?ggo%ks$m5stG1%~KKALNzwNSRQ z%AUD&;X>Z^F(((6KHtUuermFvO$F6FtVg^bQY$5BBJFz5p17h=>GNn1CLQcon6upX z@CP`Xpsd>YdkwT!SPQX>G*DOuw2&)!gKC{$wd^w$*ZvB=0UrIk-%qVi52?N_AM{zm zKu-PhRE=PKn+5Sv%JVmVSmAI#sxSLZ_@uC7+_-+d2|eiio=|wcuU{nYoST(}fH5kg zU-{`!v0E0U{JXu>?^CQ*y27NK^V20Rv^~r;sKD|>;tHWZ=vJsUi!y6;-vMd9s;f)6 zw=w0GpZxrJRNjr0U-$7?!eF0izLdI;dVv7gMC$RjfnnfVxs58yWL3t%oR3_~oR9%*aYYbXe$EuF2B73Dy6u& zhsv4~SPI|2e-8yu?p(?H7;Ceq6M8iLm}>lQqhDR}ydmbF^_gtzhB%rIdLXlH*D7d_ zbTdpMfb5^BaiS)?+K!>7rkUp!b}BBhZ1@mYmGt##{^K%wk^EsdznRM`JiYs2#6tp0 z`hsK7-ahs3XO2RzlV$5)Ofu@$i>AhmUWB@BQj%4w@#9fQ%(TG52Vaa-ryTjA(nR>4 zH-;U}ZA&dv8qih#*zHi~R|d$*@F1mAv{q|(df|84tt%y+_f9TrMX>bw9 ze+ZK4DeJv``zm=@bimQC&n?4%C`DxM$=K*l#m|!_#N@ZZHkRk&ENWQ@wEfm*Ldt3o z=>13E($;oRHre82mxTA<$Oj zqOdX5vdDkwoS1k!{B4L7K}M!c6l@?qP#p_zCw`_#5!HJ2tW11Is*Z5YEmzDk#vupmI|&VIZA-S_K}>KS1j4YKi1<>HCCKpsRt zM`4mM5S>LnN-O1$+|6|_lMD)*iYv=`bewvbfe=!NgOn(8T^Uch)@+rHB38KELiMBU zPY(GCx>yN!TOnY9c`!3v1(}?q{rZ?`hL5?Ua9UJ&+uy|+`G?xStZ4zFlcQn@msBKQ z7m^xaw$>Ruqn)J3L=K$KsGa3A9p@KeUcTtT&FDOhmsn)ZI$k)d^7pnxkmguNp0PJ+KdB1RSJk9qp^ta~$auUI@yC8R>@@V~ms z_5L>(*i=^?^)uu$D5mET1>~J=%CFgnm)VkI%4SV*Ppem+{98N@7>WiBQ2-(57%ubj z`uH#02VOWANcm@MY2{9QJlq%De??Iyr!g-Ddy!!rxfXX1y{@>(LCq`8S#S0G_png8 z+Y=V>8qca79l0J%scC>P%hDKy--CNsO9pNBs>{Fd6bpGhfLR@iC19(hyOM|1T$_P` zs3vc34q+uN{$6@e{HrjjX^tTy?L0c1COVwYzR&&W3jPl=7;oQEPye`BH@(c(^7DhD zT=kL|_WgfLY0L;usbgJ^AEBsMR!xyxR!d1ANqyk0E(q)Id?h)4?lV;{GY4$sLDb5CzQnX7^b9;N4IPmDJ4+VA*BUGN}A*Zx~7 z26VJ#+Sd=p%^!)xk;3zq1?l=d@RwrG&Bv@5W>&p+K@}HD1eId2*$Qnbg>j=lD)G{= z=W56Oekl?pT_Op4N-9G)Y(X+(<_o0Z9GZ6QMB|KRg{Tk(b)@m{%C$swHk=-WJpCnJiFtzH+x@6<%}2?g6Mg?`|KD}=P~DPX&xydSf46r# zS($r2DWjX$pR~jv#wx-G|!^HSTz|NvSi5Q=@<-S&69Ia&FDa_MKa#mAH zgiN1gcpR)KzWKMg99dye(yh)@+qlON>Xzd#;ZTF5`k(*{Qz$P~6(6(Az2&;8hMzep~ z@?UTsPS2S-dUvJXg$4Eo zy$E_NETIB7xD4`H_y@ugI2LW3>5^)28=yKS@~Ou}Q-zN+v*TaYuqN#i zGajG(i6t0EjEB@#oM7&?+owsZ!O%N2Gv?Zyx#t`0C;GzHpFCzKkUy%R&kM6%)WXw`7H;zq%jqvr~+E!8$ z(0p?;2W1_aZ2pHV0q_)rfM}VOw{PD33Ozfrh}(Lb89>M^>svdwHdzdA1Hwp50REsA z$H{Oxe)yo~v=g@EO)pXkij&xVH=?^3 zFU9Usg1C(br9afV4w``!6jd{JMMXq5fs&)nY_tVNFim6V^_uS3uUYGa7}DDfA61jL zv<>wMB)LtB(qhxNgw!do8yHmXHDP^#gA+M zc*XEm)eRTbLC$_&sS!18)9kjS*QQ8g#!RMRkQN;>-RnZTxu56k6?Gl5T(qO%6pCwxe5|r$qJMv zegO|MtPhe#-PfpiWnE79RsP61xe8R&4d@@CtA{=X*S{b0?-jgs?*B1GjkxpXAx77z zVM7^;NKisl(1AxoaT?F;zm<@9g~&)tXJ=(K<`*9Z+S@M}4|{ldiK?$d30D}1p|Yx~ zfl!bvR9inT1Aqt1WHUt9e8&K%QIC-1Un>YG0Y%r`yCRUs(PmtMKA&Wvg; z%0nf+++k*)yrH+FR>uhZ8{n;jPMn*Q@%lxP#wD)beO+8!fZWH`=esO1=09jQkMfLT z!J{k!zzl`G?xngJ%kv5v)&i5GzD?s+aJ18I!_=?_EV93Z`W=+$u@NAfLBP&F!W@tg zjDRk_2~xrgsGUd{bk*d%fB(HKuC`XL*rb~DpEb+3b4%@lHSzlEa6Jx1-*Sexx8jv^o}J|3sLVOm>-<;y-p5& zP=W|We;EYz&MXdZ#7(*?NhN5H`TjDN|MfkV{aK8=-ve5pclhC9_7a)xg4{o{%2H-f(KX*w z%r74{@FV}Tsx0g>{$Dr)RZF{=d#!c=zeoV6`Can|3X+?n8-3k^slC$)2jA1LRd5?u z!Aj7{KLUPJVDr=kBO&ae>oY^X<}7mRRhL#CzS7q6*K)}1ZQKxvN?IA7Rrd>@&uP88 zg29hwgd}Q!M{6(Y;;;co!TkOn7cuSP!$th1#%8wf)>#QAv&pdIxw$ns%&P%{HU>|D zwQsq(kX>5`gKTLHZsMI=%58if?S_Q}c?r?4B$$dC#K1Wzfm~-4DI_Q@!^@mS z8-AE8zG?vfl&C z9v9}UK_dTON3$Pam>d-$D3B+D3?lyjq9!PTixxy82;`vs4!;(cdct#0Z$pkUJa=19 zqD&mtt-B37vG~#dhMv@VOJ8t~LJe%;M?lLB*JwzZa=R_p7k6H=qaVNxAK-I5!PNh= zn*ecN^b~k>c6SX>%SQjdpS^BCzJ~axz#;Ex(|5XxcAP)&%@U6g00~l!RE*PAVB{n zWiY74>I23t@83rIHP5rT zzV<%}Hc%v{uj&Le0Lk;)S-SUjkf|W73SB zm`@5+yoIyBfSMWHa?%Fll4jf5fw`s2>}?t?koLL+Oqkx$fcBg+*13Z!ndvWq)c zy{$>1oM`nE>vE8go1qXg9ocK|@yj^GES(*My<5%<`a`A`0exq~)+)g4K`Ed#=6vZAKCnu9x{eu0i@ne-u@TDM?FuY2U9H* z6!UYBUs8(SDUG|97WHqFy4YZ<*<$A9k_7y{gn`)W5+&&vS{cqem|PYa!9}azJqd6B zq0UjDF3Mblf7}%lKcC0Oh`HV)?6|b;r!h>z2*$jRW)gR9Q}7 z*rDlt(|YRn>2uIaEsD6pP@5k#f;p`}$^R)0L0m`~2SNAn@0Yr{b6=;ZqGVg-PU-2H zoCYisfqw8ilw)hZ{V@aZNX5}{5WA+~>{M39dl3PT0~9D5@_cU$@CKQ#qKkn@y?7ek z{9e691hnh~?%k{QTK2ZoMZ!m8hLBe037^4uQ8YIYa3zvK3+TZi2sWqNug<0cU$m9m zbZkQR4u^bZ=~s^Kpsv4lzPdqe%J=GDK-_-H%~mB4x> z9?W={2-N#fRbOtqM-*-0fC^YVcsZ*F-aRzF_J87_+&QSG1j*#l+EP+fy}H@4b(!GK zqo;u34P!5afn&wsohb(543#oeIgNmrW3*N6Mj<9%g8imX>4t+c1$J=t8r`( zS}75x7MahG3lof{Sd{Ki{7YtkV;(S0IZri1`Ax^z_z_f2tA+$j^mKG6&Jp4OMEa|i zo;A3H>ama?nkRnJ_(k2j%11;0oc6Y!^(r@BQtIvSu^{RLk9B0Elk?8w)R-?ae@=Vv zTE@J%xy#wF`w;(Uo8wD$ej#Il>SU|lok@3(#2If#_EWbX^dEjL2tuO4(!^34c>LQ} zgc#ownzZw1XN_Ic`aMG>Rf{vniGX!BWYot$3#9C&fUIXEjb7bz{FD@b-xn8Q((Jls zbuX`f3!}-^fBO_bcXX&(b9}`=dR-FxqmjHaY%IuZdd8WkM6>b!1K?ykD!_z>DMWGM z6&0C3{TUX%6ZVo{fRT$}GokARjsCMuc&x49I~D?NfV{+wDvtQS&_OMOk2yVcJbT8t zj(I`Ls+&#H?H-iT49G~45bF??S0`C&#}IN*B)&9>0*0v4okuCGud$3eLtfMBTSBza z(dqO9G@;Y&Gy`fJU1$sHq2ZEmF zJAXe*=TsOB;^hFW(lND?yZ%9gqn$fpM=`65;x5P+$De1lo&E*y7X}ay;qpVLrIaeW4m5M5)?}a!Kn4^UY*1_d@->Bk_`0%^l@Kiuv?^3w z5g2FCG?(JI*~l#nfH$fhLp?~ch}HQu|0xG6s9g{DH|}U6&{hOaB`?>CQJ!;zV3w9d zN24VdPYD+xIhA__m8Yu)tT>+zc^wC?_wcqy6p`i_mb8KM(NN|c%@!+S(4Fq5lu`$ykH`^vl=MpQDPlDBANr zvgh0^|1I}>_$v_?j z!F@3Q2P{c9w@m3S?^Km|jsmvUcG16IH&U zY)cP2534jh5G*^(CHwzV1A=llssW)LF`xnU4R=CsiVZX^jX-}6Kmk*mzfcVR25)!B zO~2a^a$Lm$P1h~cDQ24K(;Pc67&L_a5ROfDc9q0?p0C(b{_z*T)_wB&fQ(m+2URRUTX6Dme2> zRu*>yG}1(HQ1?v0{<@h{2D(&@_p!b?o@F?>K!=rf(V&k!u71%VwC0E$ayZ^qhic)L z0VdM-nua5{EJuYIcxg53W93(f!8rp5VW&0Wb5H;AtHF0hRE-JphxpI|&J}z!Q|{+$ zm*>x(4LW4r<|#D33Vl{iX7=#rn|$cVArh?BUhtg?Sm8fMLxaA81Km9ELI=wcbF<@LnDqyW3}Am9g~05dKk(m8 z*zU=Pk<@_KZU!2&pmCkP3xHD;bZ>Gt^JnP zJuO~YGB%56I-(RQo0w)WB@I3fw?8#BZ{#sQIFgvQTn8XCm#mLmKN z&1l*6k62*A9H|eMMW#XWLdC(%faQx|DkyK4(0^z8uq~FBF%Gk@s|&UIWrskoRKV_X zB#L^WF;8si;D8{!hrJ|=>1ehB1Hp=zAkXqFuAE#BPAT6>kOBl$9Q;8rNAY$ENGLk# zZAX4YeORer9EFa9ELbK~--3>T&ELsd%|k;pAUZ3<$9A8yS;@sp8we-tFv3Ud zVrgF!O9B~5^9YOlwN-KePbdq2RlS)GcTQ8+@F|9=M=_VDV6g1=yRMiUVy}8yTNHeQF8I&%?uW z6<)&vSewD;@iDf-Jjee>cm6QHQ1eKgnJd_Xj=PkaO>Hj5VxA)+32tpnD!bwA0D{fb@s-vqajt|Z8hCO>$45!5~j zysICAAKD}dZBHMe<=(_*Sb6P5S0_!~anWRy*FPy)ockeeSPUs4U*JdBa_JGB2d7^K zhX|p_JesASjwb~EEA%x@V2gz{bzCd5zdQ0k!=SB;=g&;1j7t}+HSSK4ygfQg51oZ!O_8rh%_W$2svPbsF3Q1;GC@GPIO32Cz z(NKwuG|84#R!S->D?*gLMM|iYebHMoYmt?Zz$6aTJhL9;J61q|s`V5ZJLTXAJO@LYMg) z8d(>`#9eP=^RM4p2N3cWpdJ-nJEeYux8Pl49~E{5YjOojW0!SDZ66 zrfI{H_u^9hE(lUYS6B1*96Pk|)MZs%e?(4o|H^xtoh%r6Z)q{glW54<+**z*USEO; zw$=O?7IfaX&#C>2DyCW;77%t10)s0-@_j4u`ZIz)p!hc$l%uv^u4T`B`z%N(Jga5DwKowf=ug+gO>1Tgft}4SIwYRwnS7gB^Xie*E>bWI ze5hglUHlC9>;awQlsZc#gBR{o*0Or&W(;=@GWL^I2^e%Lh#Vu&GMS@=)&&sMBmQ&P z_64&kyjh%u$)x^`USz{pL!liH^X`nd7QFF2>AQ+jmuK^Mpf#bdn~B_0HqsD6kOEOV z6p$*i13~_WkI=BNlTSWUc~aNjo{v<*dHU0l`4owtu5QZ)RnCvy`qh~t#{arqFhPR~ zoxG~YHKf{nw#16MZ2uDx&}Ik8fq+uR>L%OiPUHJN)4mWk>-=%B^lrrvo?l(cK{mE2*~K@1sTV~rvg%L%^0Mq zFv%+JdryVRi^tX^dQzs0wI1e_5HI#Z)~K_*4$!_^)}>6K(oj(_#G>k#<|4zax7CWS z9GWqWKj?+Z)H(Y-zxHob2o@&aMjsnBb;pm(NnYJ)UwVLgmS`RUJlQ}r)KJx@rf_m{ z5=E)fA-C`my8q7dN*XlA-VA>TU=yierA+*IYdNv&u;HO#ysUgOzK|k$N96lJCjj)E z^*y>AdcZmYzSdz{DVdfmCFDH9mqA0ZEwc}bud1Lw*>~KAUekLk1EoK6&*MR>W3SW0 z5Vk6pT2cFsJQdTNd9k;&hIuWz383K}MUrSD|EDfJYv@+JWCJhjm!MNCs*xbxUT=T2 z0bqv2tY*$l+Uz$hETc5I!z0(n?g4ieibQy`y51uLAD9y2Sb?NT<2p8an)WKH0ij%O zn}G&8woR4bO$<9dKB6u!0ayP=LuHpzP zj0-n0wg}(*;D>j&cj3jw=Fs@zh_Xm0xmWJFkEtX8vDl48R)t28M~~fcF>qc;h+XW` z)(^FSgf6nAleJydr)?R>3WL60Ruh5_(NK*P%PFz@=CRd1KbT>MG z^=;+TkAHkX$M?z2nUE;m$dnH%lO205S(DPVt0d~p43ww;m37%|kUxbM4iWxvWq?Q6z-et9J6Kt_n?Cght1 z0I+-^?A#c@A%4~425D3`cKUOE(X>)k_WdzV^V{d=$wNU{>-Wg5cNr`q6Bdj(Q%tN( zj?OVw&ncdA7p3$Qh}3ph?QNl0jDLMnwyBX(dpw$*MpRNMtG=gJzD8Z>-f^E$>%0~e z+yu7^U}{X0$D^B`IUfAXgs#*gW=Z(E>7`#Ugl)0fm_rX<9w{D&+&gyp#$ zx9oZWj7GHjQ2Yh;cNi z@}ZD>%fo0Wr>A;Wep;LSW{~9Zjp#|3q@&YRXX6M&&nDnn)>xmZo?bQcIczIEEsB$G ze3?+3v=IaTB9}0eUE>8;g|9AnI;d~z7C2U=sVuZvqdYyW*wxwHVzHWgnTvdC4aifZ zH5uU_Uv?{>(v!(1b{hOSO0>91CX8%=I#4xP$7QX(e zvd<9POGgxWu(&B!9g?KG7B+V$@yTgoH58F07~5MS68T@u2S zpzJ{+n9CFMZ>8tvl+O5TQTi`OWw{TWoIAsS7Y)9pM4Dt=?}MjW|F)c23%-qxtPW!` zNk#qxPRa$lTW%i}!^1|FlOs|$%_+L7^ZV`}_Po}Y|V3Ac2;BhZ{ z!%WNynmaP8=z18B9dB3_cS>8Fci;op!P!q=Wb@gj5j~?jq}%@R%`m!Tw}%tOHl~-= zdt>_tG71NMreD**ZRX4J!jc>p%@;rUxbfxE*Xt`N6eIgK^@IK`o%8caeYeprvML#n z7*r;WkL*lx%e)-JE4Kp1K1J;=s#IA|B_e*2VPP59Ibe#Ux<(YgC0h+85@f2$Hgp4Z zsrXnXph8bluDu1j!H4bpSdUELTt~3M2DD&k(E*oJ?a=)?{a39HF7c= z5q`*!_tLyrbG^hx>7Pij<+kk9GFU@l8T)k3QqMe!#lH9*;VzaQh(ryTu=`8Ti<~V$ zF?>s=5m_Q7tlQDJi&@H4mr-+;oyMV_ZIy@godIc=u&``La&>bvw2J6JJEdLh6~FD* zz_1*R4A-sQv=U8FQf54ndBq|u5p8HP-ud_I^#B4RKu175IPVC!b=<*uiRJwl4$IZK zP_Ng0OpJr03lJ!dQkk9Q!fxNZsVGg7AClMfTu0Y*kI@%a?56-750uI;Mo8SIp7ah( z+U$hVw*n;r!%R*h`g8sIb%Qb2H3C)hKgXb~U{&Fj(@_jTg~NSi9N-m(fOty?D5xXc zZ4zVeU4M5LzkGg!6ypmaj0rIG1mt@Q9hZPGT!a|-#j97;6zD>d=!i&=$$Kj5 zIs>-1S3jG{@7fbxB#LPDrS)pXgp8@E$goc?Yo7h+D}w|ie9thOE(+Lf^aw_y3G@oe z!#4;jid4j)w+3a%q4)2*%I*JB^$SF(Edre!)x=Z2zC=bMfBxQr2?TPG{Um>A8 zUaB_2WrY}^yhJ>MCtkfQ8gX|on_k*Zf7$b0m^6YBi^yu%c;JidE4!1&03ZRK7DT+pIypYuva!=5xzU-8k1MpUl=YgT(r z*bWt>B~dsm8DBpAC^*hGGVB~d^0D+N8hV8fgIYFE$P2z04g%Cd#Jbb7?m(3oj|Oqc!g@FtNi@hOH??} z9gc6EVm_vFuo|2orBiltG*rHOx6|BYV>$40Q+Vqj4+!e1##YmFmF@Q^J}7p1czEc! z;4h-}ft+Ho*tPuh1Qij?g@_sUzBS`olzm7R!PtL*ULJ4so%g2kcwW;0wWKBP9w7`?6)> zScIu%vv1Wo$f|*k-xd(B#+FNQ)Y~}5AO)msI(+QfgWG44(bwO5>gT2`KE;J!TxCv9 zU-fmJ^9gy0hbI^XW&ymX`|;Adp4R&LNvvA+4wY-QP6L3hfboh%p(yU&uV>p7>Vb6x z!?PLnY!G?%t9}e8TNOFcUcGwNdeAtml?J8qk$xxo6cHSVA=Y_^+(}XPc#F@LC()~= za-TYN11ywiepjaiQE5*5cdA>wf`W&9xmp2xjEXIZjAS8nX|nBIx?~yUee}~3-xa9v zp`|_m$}QMN5I%57r}HUfqcUkTKIA?$B+rQeg0tCq zYR;ChImfCkth*Fuy$oo`c*@-^RsLbtM)o;$K#}+xv4OxL`fRJ?vyRxTOoP0g-iryP7 zVHIF7I`{ou7^b)@D)D7XlJn>IR^Nez@o^T4@0qa^Lfao5EaDFjlLP!%-1Yg%UzIu^ zr2-M9o@)|{lSJ@yqA_4{)AyyQ^l47cF-p9Tzw3@RTOvT%9Hj?A!9cKf!9cfFzN3Gr z^mJS|7r?SdZPmTLdultLSh=rYLrB9hLhGPLTy>Gw{cfD2Ll_gqUHT5q1IfF?Kw!?E zwpKtRjG)w*!LV5@&mad1lM7soMRWDWgm*mLtbO?)GD3jV2p$XSB44(>^!@NXLLPAu1Tl-gD=<1awM#WhPm18=Z z%K8qAfI%ktXo>e%s>ZABswW?X<$e#X{RvoBjnmHxbQ4)ID#cPh%8Ycu*?*%ZlI)$o zRxpn<)StQM?QfybAO0m8J^$Uz0A_XiApQ`KAe4>2LsDvI9`mG>ZV{o01S zozIelHoKRTTe+ySA%)|{F@I5T3p|YrIxd%712aV7=5$C_A1~wXmA<2)agtBu^-;M% z+$0{+rM`)g55yQ5pfbCYlUh$a%+sUm{fB+DcwG=$be)SbIF-_L@S(@6E#5gBo_jFn z^Ub@So(*BjytoD<`gzt;$bs*M;zjOWQ=Yml+Ao4@VS5bf(-MsZ&&eb40fX&Vr4pxdC6X;k;_t?*Vu5dbqxei6Z-SHT3k zAbl^`Vihojf(eo}Uw6pyqM%-};@Q^dDpS^d`B7WKt$Q0fI5{o@1SIathtdMZ+2QC4 zJ(KdgCNZ9$k6^Iy*8e3cl^!Kw((5vh*b$sCVNaygPS_m{-mvj{w;)n%AG=2lzt+FA zRx}kC{|1@*uclx@KutZykfxgap%9n_WyD}oSl#=SXk!>3RNF)I2jYCbJFLR{a;9A7= zBXPilB|Ucv;4}3ADA0vwD@vKsF6aA|sL28%NIh?zWdACLw7dC0QmlXCvMG=6X=b3% z>p5G2(i%|)0)83^I*h(gzrLx+L${OfZ7)3Jz_J9k*>O{$;E+%8K22)eN0pxn)nODn zbdS94>NCaXsVOLC_h)&Py+3lW`1WqJoqoYhoiXUZ}y#g zW;1b_PGJ)<8AN*l`c3nJy2JPXy~@-{s>*l8$bLd10$E4_#q8N{dC#05E^CvLB1W2W zgA~!)E$IV#$3!eQ_qH*Q=6j!ZktH0ek>8I(i>rY-to0b!i)06uk(p*NUgzLYn7ieB zRu6Mol1b1KM)R167|HkA`Ko8v8)S!aVS)kv7kpOR&As@2nPysd-Je_8{V&LX(S1vH zmS^7QN`P;{4Pwm?B$b$Vd-mj51&IjTvGWW@XB(?~ee*tdi`H5?JnZ{Xe@2J632O0T zO>Ex-P`+vsckt!g2}DIZ=hm}1bfE=9;yYbt+49Zf%1C|k0;7}9SWJo z9}gSYhQC_!@7FUrMkiZ-u%PxakYCtX_;~zCuJ?{CKKJ>Pj^;W^7Xn`loj%}oe~!Mf z>MCoX!B0Aw0f$Dskeh>Z$$vk9Ev<{d?-LujtgHR?m#?e%QIWJhLnGmk7ZRt?q^4Z; zSX+GsWox$;9O+rLZCZ?}>nnari4Kg7hK)A;8OfIrrtug#h62{+^_4b{4!s7mZLRM* zKBa|7MI%`$b%LjIa&R{vbHFT}cUyWSH#n}f&v#)T^$Q7{igIt!PnU2`tOEsc!$o^u zbsq3mQ5aM$St?Qy8!^a~Zz8Juy!E^O8Qo=_bam$Hqe&HPPb-`zt#FC&cWWHZLfMmqDi=ViEVF_D1Tb_pU3Fj z7@te9?}w%te2(kZimH2tb{;nDvPQ{Wg+(g-iJY3Xn=DWIPXA|$4P{V*a$+{}58qz@ z&nR@B&EQMid(>8qas%0G{kYM-=xi692cpBrmM)bT8rKl$+3zRj+i3~`Vc{rMKn=x1vXq@uNii+Lvhs^8NEe)U3|aC6LvIg3(?%ut-Irni zY(HyydYYUY?iVggTc-{GS)!daK%JvY;Zc2q8U?XFu8+VWPfx|BoiYEn!cZdG7(6i@cazpDkh=MsLqtMR+^y%-xs{wRcMIs30gHKxe`3Ttl z+MmMQ?q?MGNS|<7m=eAW{QW#O|r=%5Y}=GxuA$w=+e72CzDV zZ&_?T>Tt$~qPF&7=fsA-K27KKQ-!Cj(Y!O!`&@hfd}qYMd{uDy$}72k`D>+bWp@tD zcAeH;P-&R$o7U;`-5+~?%Ls7DCaLDn+r7S-Y`_#uwLFd75TFXC{hf{C1~*yKY>g-u^;(T)w5>kFx=Yrx(3e z#locuPl}1i7yj}V zYTiM7pxL{0CvorN%Y(v5^Z@Hh=u}~K2|4rg|9r$&4lhdJV!F_L)-2KYOh!+pU$- zougB0Q>?92#k_Tv8rimm&V+pL3fJA_Odss%<$)kD;xKJy2r#98t!I-{-g`}xEOWK( zch4E5Ca25W3cK(oa3|)Lu8oa9#P4`o`cBhHp`56?e72cZJ(xp_eySr`mp#tzJ>8_rw8HNO?r#uz zt3x_j|NnYc>ThT!)}!@)$nFEkd)EzmhiTFH{3^FW+U$@wP>^pG8)mm#i@8;OGi(+| zj-&KQ%QyKtvoj~&kwKN8jXw1(@udO0AxZ6s04f+U=p#FzoCKJ|*1)mV)+I!3cq@eG z3=QW~-W|kGAYPwg@_J$Jiyvf-)_M#E8F)-mqaM$;&4`Kl;hMEx>+X$S^l(~QFr2td z{&;ah+5+nwec_>qp8kc_u>lV^3rZ`NEbO6FyaEJExE0}al`Yn9- zLkWkD*uSLHOzZ>r2uik%a2uLv;@X+SEr_rq?QWxKTm$$eo0WYPmFPiL(QB(7@-hFi zdZ{@wHbKp+FZ~KJr|4dt&Ij3$p#`P5|FIC!Us6(1VjbWA`Bf=O z0nIC7G@l(VLc3_JD8aBl^8!C>VYaNaocWk>?&`+UD!(3eOVg1oFVsbam2!@59r^Z}=FG_yctSi+%GM`%x**#z_q8{Qe zF&vOwT)A47VpKQW3WnA|vBEU8~Z_$HSvKsE-nCsj8~9 zS8<%qM~COG2C2ZVX2eim+{mPURgUOg{YO0dbx8{{CO%JS!Gh7ZlZf851`etOOXC^ayS{BJU4`nZ@f+|FG=pTq7pW zZC&OM9563f{NHXAO_O7JlW$e1OoVJ?6vFk#?><+^%B4?^$$DurYY@anxQK3 z=dA;Xjz}o~-^yF(Om@4v${-_$mxybLBrh+o6Y6zV#m)wSMX0kjbSKto5=?bXVncGA zj%Nw?d0lauY#}7gO=vHmFmZK?mYFadPG+G;OQ8_;Of;z{rk?L?gz3j0+*XeU z(=3etno*p-keEmZom;(Tuwe1ZENqzC){vmE@mx?Y$9<1wK+GS>aGGLt&lhkM8jKEG zdMqqIV?lJ01N)yvE^G=Me0-r$rc9T10NQ+VvSs;R$XJz1`cDHf%nJFc-jSgg6u}Qv z$_Fo1GbN1%$CM2e%I;gCH4U7VdAp#DlMIRKw?{R?en4!Q9=Pc}Bf+$VTqVnVN_ zi9DQhuFXN|TW7y`c;4fN83ZCcyj&7`>K+k_s7-Fv$`6!bVekoz2;6b!^IJsle=`|% zb#-@iAWkw&5do!$f{M)Hb64Vtxr0_pxz8+WoB|CE^;7^nkcBQx708yDh zrmJ1Pw~dUnoXH`NA;SVOvF)wO{f!OC`sUj;q*1LYmD* z;N2Wu`Fe{T>Rf3$I6hiGJKrn0o%nCqqkANLU91jj&j7gO(ZwU-_A;b$8`;PJx)5k2 z3y9{T$Iq??V&UjCdot~xu!N)3J3j@{qU9iZMnbb$3;lmmW42>?m?OD5*`d4gY73(O z9SgaRe92%pBQea_E`5$oVnKYY?8yG_eeV2NYY`MMuxpR%k6}1TsQuEe0SP| zc6njXO>O&}o6Y2etZR-GZ~Pqy5;%ljqehA5jZ8_dcOeGz>fz*t6rTV1?zK`cQ!A64 z#_+r!Asx*m=iO@|&J!^)`_w`6`0)?JnsRSy9jR^yKo3Uz8yY(O`GukP2HzgE8#QEF zIMZ%-Ikf=PLAPl02M$LJQc=i4?-cFlffJM;nF2x;vA>=$yc4o*lMT#Dd%v8~X2o5K z8kLqdbazy1G7D=mCiHrawLwuw?bo3Z1Q*OinOn6Zzl7Vq{YY76VR~}lx}_~Lqz(oi zLXWM1BRYt`fS((ij&w17qqc^8 zH~!suvon#~^qcaRwpnO=gk^V;x*agW%BU_8(GQlz%RyBfbu2Ke{u0LiU;kLYUD$sm z7Y!A~*v!m%Sf5zE~wxx1QsR07TARYdHjO7W6jR`h-VxNR9kA|N9 z9g+H~uC6vofk_={BZ9i74QB%XUf7M66~P! zP)-n2R^}v#x~OmnrS2u-bNZR4ks=!e$dtRg*HCy{0u)yvNKn@8LNo{g)ODHN2wgZ3 z*JNd6WQeT-F`-lKCKq1sJ<3ho>(CFygAqd&)%n%1G$M$39l*he@*eaMyI(|0d&}7Y z_v7v9%ri({ENT`wwkQaKp1$Yc!ATVh~iYXO!_EWuFFE_C!hZ=JI4fT^sRmn!lXySDzZH>WC_%y_ zwv8&-`w=k~2YNo_mtuYrA0r66M~)JA6M}%ldxrKo(a9rS!wzq`%evx971tm-Mnv1> z>?%4(^s3QdCCwwq#liqna=hl38?lzs>s7{p0;l*LCbtxVytdBgC0(!zua5zkIGa-d zb%uzl5HXg;vx}UWGJz{c-pUZMe|G~EUG)N0JA6=+>C2Z%Dj-$3VW z&6!|y*Vg1lXKq_GrGuQmcQ<;Ih0urv=$h39(HA>pM_*=ZeAY&k6bvUyqVye73~xMv z`Rf-iiV=@NG{MVLKY_x)1>aR;dwaKIDKjHAzs9*1=cavL7ZcWZgUS=ly;3%?`4L6O z3liQ*wpkm{t>hsM*T(PAu?v93*91Zh!H0BgB60u*-=CO6{ykBNnm>l(Bzuayx@uPu?=zV% z&$D7W=sgn*UE(E}bh_StLzhE6cWGBljK7TuRzERIA~G<9fJZ#3j=s@s{7Uv935liy zDHkrV+X75sf{nq&WhF5pB|EL7qho1z&X^{o8~H`@$WnIq^xTYfLOfNkFZ`y*KBX5^ zKBmFe)wVr2TF~Qvx`kxL&4jH=>5t&}L;Uty~C&Ik`p&@4}W(EfT?UE`QmaJU| zkHS=m8Q<7`Wz7R)i!-;>?bX%P)J9$urFWFOW*ePChnJ3UJkSJfY6xcb`1SeTUYG)h zd^7Jokv(5i(?WbdcqY zXoeKwIXFkbYY#HY{s95h6mx@}m@iR$_OjeeSgi+2t>Z>Z=rQL*z?Bq%k+a4alr_3f zisW9pY~Awggs*QuG*@QfH(2EL(UfSe6ciLd4dh(v(kJE#*g%mkI6-1^t>3&ROv50^ zypwQ4v63jRTIle9`egg1yaF%z8&)-;gsW+cKYL~hi9sUC-eoSut@j}}6>AWhl*nW; zw;A^D-w#3%o@rSMJ*9L$TJ>ghW*l^j;k2B%+U`6Nu_R0((xHd{OMF5CRe!nbj_nki zi#n-wxLLv;X}W(u4O=Rni;e;u0YrUo6c#=`kb)t=4eQ7xTrq2ThJkQ|{U5RBAzuS4 zjF_)HJ$Vvlvw&2`?aKdd?x{%7IhF7ZMZ=a4JHSujR>fwUqr$CBxP! zg6yWqZ{h5sGw0(daGP*!RDT#9*7*DY^^J=ljX(lhFk$_=br9n2DjVSC=H^ey3mLVl zz^OzGW8r8g0|G}NT%QDqUNPLV3h^wIh54mjGwXfcEzS`|$n29H8hR*N@Cl8CSsY>j zY9NLvPs|TFVLwp5%rf_Lnpj-0xzU9kfNQ%)_Xi>lp=qq6MebS|0e(V3ON zn*iAp^*AOa1^vP=ZnJf-%02go>871r@WI-vW`OZGc1pscAzqajb7C7wse`RF9N?y} z(eE0)!1$<_w&Nr;dIZnxv9*;0OrDAOm8E_{Udf9U7z7fGHhZoHE#97>x0hS$3yX;0qDgf%^M>hRFyxHYa9SXL&o(wOah$Em$k0XD$WAs(f4Ihlz=<`T zbw|!~dq}b~VEFaYcjqCn5|fhB_XRnI)rAP)k^>BEuJ$2~#MKH4J0aAq*R$EfqX^b| zD~M-MNHKOeW}*lS_iN}R2LTv?{S^BfIpo%R4o7x~R)LDnjCfH8YD1}?;0eb~oMf?{ znQ&K7v<^VzR|rpPy{^=s@S|9XoSzGEi~`Y7Z-8QRFgb(I{G8%IX3XjhZd@?l9+3d%?WICRzl4n#D; z;IW)`znB>3z4@xN?@^NVFTW(ymRJ`MXE0&WE!RaD=Z?|p@x4Q9tjaWlYZF5Z;J2Va z?UsYk2g<2>>w;K4(P4i`#N)vBza8=)$3UB)k)FIKEj+(FD4Fnw2 zm6k%>8HNGG$lx9}N_aJkOG?tAO;0?5P_8h4_vIK4*}E`Rgg_bb)9qGI!_ART4#E?K z*cFmrkbd@27Z&*>jzuwfc~%^-WhlqFR>?QTYnZ7o=7qWzA%UB)(Ee8$U>+#?K{!r4 zL$!4~a|u|&{M69JtrJLDl0lJ9vw$X1*eyNS40n7-Xo4UIdhxVyFu_T=B*kdI)oKQ6 z9PX~KEfCd0Wtw7Eea$4jqr|rVAEfFjLgs?zHN1K05)6Z($S#5+CT6cV$vq&pMMS9Z zT!`r5W7@b)p_&G^u54^6v3Q}nm;pU)FH9<|h)8OBhj*r4eqB++* z4{KT={m24XUWCp^bWOev8IV8%0gvi)V5~0_oPOz{6DLlPApjJQ0(lalCz{__z;!;9 zzXwVl39^<%vOW;rZ+Nqy1QMRttv$7GvfV%h6gl-t31>Ev<$mI(ghICUZ%9pEF?1cL z048sW(*O>C0YIV-5-V`5;6)L4s3%x!K`0JGhQJS66w21T?CcIxb4TvI-Zymy)A(Xa zN)*w!tEf;L^I+#tU3C{=@Jh0GG&MEd00)O_fcXy|NBB7$7w19xLbazR2H`3h=XWs7j z`_8ZD4>;Ggx%S@hu8(U*b3vM<}PBspfn?`naR<=Uy z?B@UX6Ks|?hU{OPepXF><1@C6K*mkkS_7| zy(R8BkxK47JLCLLM;E5oLt-P=875g$V!I(6_RPj+;vib-rGmnf%XDvvAMW0WT&M9O zehB}wsB#sB`|o?4|NnnH-2MN!2>Vw&59?@)r~N5Q*S6OB#}76xmpN|C52#w|uaA{P zyDa}27ma4SzG~{k;-+3Ux>hvV0bdj2bw)j7CAQAzM+?HIr5lweY`h8@v@r)!p; zrv19<>FI)deey?(iJ_6A1J`2q+=L%ViY`ou`By$49LFFQa~!w7u9*JSFwVVDKC8;O z_YNVoP@j3IW%hcdr|Z{<2yXor()qUUb(uvIfg0Hx>vZ;|pFdw^tJr--J z*K{bVGRt%@Yp#w+T<>6g{9C($L@-4|tsmYqDJe6n*wMB5yiPIQqwTrB^YcB~n&Ji> z(SI7QYX&7SQF~O`uMF5X@2s#)x*t&2`4gB9@}BR+U2IMV&|>+#Rnl-VGFvrQ59jOGuOho$k1FOP9=W=2HC#X4tRo7d63i_N=&^7dv&N3%w={s& zmWmULNl3UA>v3#+emq!}tM}(>vUJon0mo`Dv>`J-i;6u(WJ$8r%ZiWYqnwYIQr^Je zSFT*4cB!hIf;YR(z`(G%;W+6Y@h6PYb|tgOVU#=sv%9<7?PRS8pH{5AEZ|nD_a!g) zdg~_Y!OYN&mF=A!w09pqtjvG1i;)#S`|_RJ@G3R+`1m8^qLcNq?CwE}iE`(ploZ>G zvx7XlrJm|7Zw&113D*tG+*b>+u54jXJheeM5hMjJOdaibzP_MMKv?v#tkXe>* zNlYnwc!+)f{(W4?U)LM9F|76F+t5p1qSZc_ctge3^lTB#o9*P+t~D;ic@h#UPwqgx zY>(M?Zo!svc$_+|S6z6V!?>IMN}6c#-A3<%gY`%9jn!=1c?q}(kjQ0XWu5c8u5p=a zNAqB-iFRSwFiyWAkPKoWt9S-iM*M6SOV?~;7R}>m?z)EC))QP@Tyjwt9%R)ojygS+ zE8PU++_s-ZX_UF2>~GC{V9(WUBHVQmWsJ5$A5?dw=H%q`w!O#9?0hsA@utc{lrJiH zx-I~oKgeOX*rgcLJHV;tH0@_LoXfCz;ZhN6+aVb6qTrLflC5C}4^$&H^TDyzgV{SX`dU|^K$M(6y zX2`aQoFC4zR(eR{?TM;ioXq@6iPh;(Q%Fiqwt?w!8g<7;)H&aH+crqPqQDGt}hrCjXE#? zN;zCgiF+3kGQZu*zL4K5gSX_-eino_X}7CtSl z1eJ#~c-7YrHLM%Rq$hTEI>i@eL&cMGaz6h3tJfiZ;npF%Q7*B7ggjGVE#wP$D#5|H zBP})|ReWkH)8@`LJhgGj&ZddlaTE5Q%eW^AYf#{9x3^@o7O!NzbmgIoXe8w$)3^;- z^^%!D=Hl59VR8Yho3f&Nq|VOHLFAl1qZVbs`T6;LReY?&<<8vM75fx0{>^*$0^tgia6dEKg4n%^4!%|o#f|G?J?Uc0%o)37n<1}xiU-@xUzz0^Tjin7m<2z|FxJ^%inD0aL%26Z)^Ka4p)HaZFQS#KxDigaa)pb%@5ynt z>t4T-Zh^|19IXdakuSnojIAtOX)lfz;<)XXUk3&TeiQc;yK&>jDdYqLctnQs?*!@W z(Omsja$yG+c_nTGx3~@3rrP-@^^je2-|N49`?eLl zdXD*M;m1znPV#H4D)oOD6H~X-z`8*vb&`8-nh(D zXf|A%`ZCc8mgBpyBOBf|7Okcb>L6<2Z~{s`2-M^KQOjSMnR9S%&CfrOKTh2+zBsY0 z@xg>WKRw#{)6rpYyt_nt?V8OWhKQ*xC**Yk2&re1!emVHCph|CF?Zn9eu|1}or}<% zm^$pPp{)*~7T$Cc2_D!ekdQyvIjOoh5f`B$f=5>y@z_A(+u7}v4X|6A_h=N^AJUbI z5h9CfZ~UsH@#k(zbgkz3_Vo^toi?oOZg_sl`SHpPUK7%b1J8@5Qu`H18t25j9)p^m zqE*NJ*-xK7)tavLOG--Ou$&OdDw&UzSnz-+M7wSOsjsi+aN5*bFIk|OnVrSB@az;l z_!u58@#G0+YdC8n1YI|8IIC*o`gqwR7gnEN;{F3-lOrQ4$oF7-inkgmzjNv1?##E( zMp;&B*S^JB9WBak&z80gXV>gVdKQ+W%)+9a{sd%ZWDDqOn>W#^`G2g_tJWPSL?d(czH=Dyh^B;cmjT z#VZD#v6(W_0-TEr$+B@-%X=<+6$cY|RJKAf(i)~46BYO3&kw3D2&jZtGV=Q1KxK8? z6JYrs!!Ga&i0RZ{-uoLSYhjfk8tNz%V`5^G=Cb{VFG8=WyEJ2C65$l=Pml|bLyx0mdp;t+JGme~BnP0g-4FHK8J zTi$Z&dzmQli(Vo~Zq32f*H%_&>9##AXC}=kR0e9NXw94hxg6aeBK!)X+eo_6ycF^^ zJUk7{_W`w_P0}&M`K1u0*RNCWggvW(x;0|QUe(H0CM7!eMZOO*OFCrEWlGEP?wP%E zjck_@uD>LE^71;X3aP+8O!$}AaXpDFkANd2 zgnM06D+YPPuk(hfibE$ir|bG58q#YxFHUw=va2k1PxDnWT_8PPI#+-7Dgk{tOjc}o z^>=b(SL8yOVJ8il95)vigrmf+tN#O!XV& zVTM3S>`jwMd?_n9M_N!=$Y*s5nMMiC9=6uprK6^ic=<#oKU5Fp`u^R!%WUPFwbfN; zcdfDqTVWBZVF@tSo*+q(^ojP#{u-+WKObK>6up$1-(fOBzZ%+R6 z``&BL$Y8l68%x#W9#Uw~P62=eN$XupAsKp4pFNwd#bf{5%3f7(QA9#UhFJ}J@Bjj5 zN+d=mVAu@n@>2AE&=1~+)GwGc9er!6;W!_y=5Nu4Gj$h>$D^! zj}#RZweD529-t%VwFF>a@!9_9pSHHYS!L@cUv7wxoE=Pd@=vEjgl;2>f{TAEva;uPI33`v`yzs^!K9$@ZrIpMpWq+7or9Lh zfvA*CNK7o*?RkMfKE-r0qjA$-sO(HOwzfxrS~guOyl40FzO{enx75%|BiCB)`vo<+ zF_d=lW~(Ta5mceYIK?gnpjEAh?vwBLKk<51)O(>}P-M=c7yteI;_!GSyJW3!^c!UO zPoF+P>JB7hhV(?IeqaP~_2ui==`E)&lY%vma!(h!p%MUfW)tNl4c0X6p6w5Ov3QTi zrfPhxOVmh7NjbD@FCoZ{#(nqY`Pqgiw{g#H8HhGOWP$hRRGAj?4e>Fs3Gt7d{e;5h zs@4b9Yzbt=j&5649^FAoB`+^;`NjE3Tby{@=B5>De|;RU8qPw8lBT;~TAH_}4s4y5 zW%t>ayYdeyMv?Twgfa~tC{OXNNP#WpAjf|Y8u8^z{*eX>sxHy#1(}js4Itj8pAi}@ zfM0#YA`oC7K;!ZbkG=e3!-wnqhhy-41OG~)Rj8%smZ zeweJ$6ij)2cV$fBzujaX>hy+Z&1^X#&|@e^JJZEnWg8G-Y%nFiO^4tDF)eLp&<$>Z z*&uFZKm=X-xRS!hya%3{Q9>TO2jLe-n8Jz|g4iVgj_D<@ipM!peTC+uPJqzglsj4b zR(%Ql@L|hIgif7*NJr&@C@1;+v-#TWnYfwH*~83Vzi^DBB~8~O`}_L|I-IAxu@OY2 z{96YT0g#qeXMCaJ=K^u=`!^8i(u{0XW_ORW%8orP)KCN!XP0l|BD;i;KE?Ec8kbua znn%~wtkC3>rEr9jGcqzhHeyv4m_US>r%_q1xt9Jq(3EdlF?=|3az+AJA0TWCKtbn-kLz8ME2m%XgE2efSq74FhG^(s-h+{X3QlV;Dh3mUT}j~b80 zZ&G(^Yio;lI)r^g{?Mkr_4C7|eq?TLo)|~3t*tG6ZmpuOPEDSjmgWYPfQ}#cK)hqx zil@{dRh%evppRT-$L;Ll5ryCJ$lF^C41Qmkm0&A16f=}-w&z+);OrkQh+q6+uR86~ z5l%>~3OE%Xj1tngaBXG(^1m7@b``Zx>{3zLFP?PjX-$2m^g8Fs#klcI{d+IVmV6J6 zxh*GjOsq^^I0uj>0j>upS1M+zJW)|m@r_k~`SN8nKrZBK%=6+b>F3X_5z}m5a@l_e zBeQ!?pOYCh7mcz?w7O_>8LOodCgDa2fk!5P*hzTX6v4d)lb;}_YzDRCYn^Q)Rl zl_|nA8UaMK64`_NCiXka>De|r?fkZYT>gU`>f|-ewg^6&?}}+!EbVtjtTC11X@I#TGgoS?QJWe7&>tS zcphvz!ke(pk6SuA<^k8PzSQ5wz`~#M!DE~HZWwEvgSGM_fX2ijSpCId`C`HcC)j+- z(=K;d0|45*z>4`%%!(O6$i$2`2aR98yh0e@3$ObR46D$8`JKPN;sK|d_{xe(HP#wIn;6k)5a!yr6*9RtuZnCllBhY(uXSVCdqthi> zPaSyAw(s023J2L6kdFXU zsXdjF!Y`U|F`W_|=<7ph&J}8E>gGasK(f0VlX2Fwjea}>9%skar&~=s!11tir7$ru z%c0`28Yo5e{C6q{sRX*FPF4Uc>i+r6aJpYqML>nOSAf$11*{z)IR(`YyDClr!3$Tv z?Py<|J$J?tNiHwZdJt(^PByAK;Wch>>0O?lp7s{=l79B|>D1)KIY0ln9f|nqCWf`O z_0XEbgy)6(9jR|!Pw0u-q42jcM5xsQ5+>(1z=xE?qE`HIsW+v_nW#BJ!{t4tMX@*V zRW87!8H&s>VMIppzFQF#gdgj9?hFN52#bh@N_p%eUGpqZ{A@{?Y3-Zk{~f=Z6YWyquPQvK`nE$ygezKZ}Bp7@Oo_A24r|pECH!2RC7GfMn zc2A=y9+}2wPr?~$lcaU8cRv^pNK0EC&IhMt9fE}g?_MdBw2n!Ft_HAMWxVl4GMGZxEa#k6rRd~*9{;g1HBhDM5PJJcg6RuFY!8@OSoB5<&AknBqyeU^4*m9xjHEa|*pQWw zkVwqdw$+Uia~JZ(BA9`7F|%9K(yU9a%=#fxlsw@H0JCXj4=Y*h?6iF#)Z_d|We81Z zz}d-x?ct_2#1rg*$!>vN*?9YYf!WetHv5+o>NBC&N=n$39f^{mgiB(Qnu&My_4QXL zDkv*7IzQ4q@=**cRb%5bAGvhsK*U9kFI~xq=CC&M1k%#8XV3KX^)V+*UH4bD0U)rb zmwp+}Gvs#}Lo%t8lT(*{GNdl)D83)POXU0(R4SR_P>e%@f`abX*+jJd3oF3>81kPa zX-$pse~3*2x#Y52ltaK6B8VVM{o_#pz*A-4yC<;S11+7MjEsx{#l-@UoO`B3NmuQ2 zhRrfm3IadTOY#lr4qFuMfV2Y#@g3HU#{qRUEnk`cw6x$}O3icz&LF4B1k{u7Dk{)o z)=HqctxXRipd3o+xF}V(48S$etNtloDs7j$uX$daOgaPBz01b7UO2}>&Fi1&`=c_R zU2I|E=>RH_?YHfMOeM&V)m7sb{EidOj8C3C8MEt^9v9&1erYE}jYuS25why!djR^FFKu?0yqhHO9-`+|>KHqI50Mv2BJ#K$-ae+lB;F1^8f*^Je%0MIi*No7;jr!kzBwbFTF4tg(;!J3E zlO1{%?_y;Y6o6JQ4rXgcIR-AR-A0)O)CCanm&N@+IvFlm<>lpyYdJP7pHMl}x9I87 zCMlWj-Ajv-q(^>R4&o~8)2Azkq7&Djp@s<0jVFNz;Gq2AXBx@u?32r6B$I-If@&^H zKk=!B03;`GLc-^FJ&(IMHSFo_rF6%q639^>Bts@DaBcSxKfXan8#YYp8;AG7gli}$ zMAmBsg9&LSVXpWS9w%$TV*IxAZCI26MRTS9-m}Svh89%`#pBDDFPrmGmO6YLS*-H(8r63Ztn* zU=}~tX$A){351T>76k%$;B+B6Fyu*a@k}Y0M6O zhIs%VM{*pmKzMXC{(TP*j}P7|=H{#$>M0+Kiph-Me?EtGzK`5Ar+t zTrFfmiBKdYBzIX^&8^xlHb7gtMtcDpW7~MckjG?qD0~HE^@@K*_jGhp^66!|#~U!p zmP-Zb!NfE)&~v#$&BDThU!fsuVZkPoLK60;Z~W1+wTs(R5$A2afs8l3H<^oU=AP^5 z=s>+N$_pK@aOG!K%K8iNa_!>^MR4Q&PVuEP#<#>3aeDqC>e~h88lj%{S>@Z$p}G=@ zpK?G}6LsC+1aZywY;O=d*^1v{?5T^35GB8b+2#kKkZQFJR8i9R9+t}yB}&uC!CpNZn*-4~3Fc&H3b|a*+i!4i1ia zWfmM3>kKQPoMdFvdoKTXgexc?_IT5K-?+)~g9AnKRm>B0Gb{f4Ffunl5%o|2$;ikEI%0TDuK`P( z&&cbTfxZSbY5aVA(7hx=w=_>c7MzCFHf;V#*A^oj0hJOf>&>fI51&8Bg+XECt$Lm@ zZh^q+*qu)Qu-}x+%l*$dt=aUr=JrD|&GeTXl=#P-u$otSxLr{AOlGR_lcmYt1Fhbqo2Gk)DsKGN3S3mRfd5Gm` zL={%5_QxG3+h-a+Jd=@`hftn_rP2dghAHr&o0~`!pE+*y1>i_)SSY|gWcf_;c0@QR z*P9ht_75VP(qEZ7%9}f4hnN#y6_@yKCq+)&nuPXSii)_YIEcI!e`KE!LM8;qA~fQ_ zL$Gh|pu*^tOY?&%;EbVv^k#tBKTPT6H0fhP5=mC+@;&IUh=F8+u^_h7#@!YznD@uD z0(uI7C$`(TJE50^z$Os-5zNzIeY&D~p|kz>4@%^4$~TCDHxTkMz!ZOpL^|lHSy^11 zpAAF53eh8>ef18$x-1v)XB)!;h_(BE^xs?L!Bq+NQGB_Xc8^A(VSZOm$6D_7+|87> zhu<6gde<7Jx3nBxI2L(Q?|b+Km*Y|j{!~m`vryEF$hlQ^3FWI;XPo%?XfFxh0RP#2 z=HUmBSGp0|z3-PirCpH#bl0o}sDNx>`*3+dXM*1~6Uos)26+}E_{~T1KQ_Xvr&eE_ z;BmkVkk2K~;(X#qzSE4WQ3c_Y^!C{D|5lzoOs6 zof{YX=`5j{Ia|No+omOx?YyYqJGnMjLUwZ4D@b3WV`AVa&HzhmlZn$>1b~*3Y80fxz=Zr_;el>{Lh6>D zpD*Bhx%w~4nu_g~UO~IpjIC@nxB545;ewOW1l_$=$5NxPpkk}}kY{v)E$>Ftb6q?I z#n)KP8Y+TO z#m~2hptS*62^K(94J3=(jEqIgDuWuXtVlft9l3sG?=y5qAa{(da~kOB<$#U~8qZ6G zuKD5~Z{)r3Q7rzxtI{EuMSD@3JPSPdVrJQ4%y()kyzQK2uX&!J%`WTjD0dvhfb!ThQ;*${xo|%gy}^m@G&_*LRjJ;zMq3F4ouLsnJ^n`T1Xf{E*H) z?T%}jtuZOM3Lz9g>(LCd-vdZ&Dw&1dx<2Zv3JSo`pxt967p;>w4DF@Ij~~mas(xrU zz~lL1VZuWFt0ddn^5|^*`)!ON?AuQwzkU7sRwi9eZFcHpyoTG`!!UHMX>>65e)(|q zeqDd`#p*qq)(mw49RM|~@87>SCOt)4+&h-2q4knUp=V(D`Jj4lNH_GQvhvf{uSpSC z1;7YH5Ock6g(lLHtd0aGeEj^m=jI{CWjs9kTer}?Ha9o1%HCh1{D62__OIYvk&yX? zhyEc=l@Ohg@ZH>OR5G_fx735LF__sIKl^4DYp);(#0+*w8+w?JB_z14XC5a@eXoT) zJ3d}_RsBACwb*UC+UAUDNuO%k{VzPKi{0X4(M8$9-n&B_HZ3M4^9A;~cjO?m(p}eZ zqC@(!@$p_jj5MInD<;e^GWZlV)N~tb0CkU4QExTA= z@tY?^cy#rgjp7Q-$AmbjllY{kB)tK*Q6JTnduRIAr|K_jRBk&-xezetz9`<9&3wA{ z5lVNrE1*}&pABz6eJ2h{t6e_RXWc)I>Jkq(WQ*~V@P;g3FJ3u5{)8UEsgEVYP&q_V z0ynRPX*?=uZ!bJeyVfagugB$i)=!R#J-1+|&DuDY?gbEhx!VI4Pg^1;e3p9_HS|(W zx}<-&mVWB_Bit;0-e^6W!R)~$BE&ANL^4ApaN$aM6&e zs}PVYlWMZhg7X8ez#Lpia8Q_GT)LdgJg@soVc_wZBZ}bKu!taCIrY%$sPjCU6xDma zFa@4`=*%FnN{vk^K(nm4_#1O}`Dche!YT*Nn`rUXNrPP0_gPS*+v%yli%x?n^m}$T znD1OM?)%M_;)7i^)ID4W?4jEi#5$|FuS%~}RVf7&p)i9A9?~?sw0Q#OY6lb|-GUYw z1#>#Ic+^eq8mU)FSF&-Bz7~F@;TGWZ@zmfVeB#Zow6NVV;u|CK9HLZI0mw5VP01Lx zuKam&&|BaZxXAoUSBi8{fGN}Z;jH;>-$>D0--YM#XE!ES=R@NxbZ5Mj{qIORtl#$| zP9RbRUk4&pz%qfu>GFD`Vapn`R2J;y{BD_$yN9WjWFlg#rV~lmu38*S` zf3Jsna$o1|M%3?m9n1b%i&);bZ|X>_onJ#j4&Zrz?cqC_ZBX>AK`KieTtQkxh|CEM zA8sqXQhR{afSI^JwnRKRh(OO_J1+$p8#)+&3r8(xe>c(Ksr9bxak=iBAzl^mg~(A6 zVngQv)RqaHBdRdyBflp>`^Kq@#ckN3_qX|zcT;DyU|3JjD}MsYM($3LI!N+VhtX+i z$Z`O+@M>$5diClRB2j&~#)=yayyu&s?H$XCJwzwchL%5o#Ufjczm*Tk%oPRrF5DoRTG7PiG!~~Q|s(~*+tjvdM?98>Vlof9$;M> zE&&r>_N)yV&GmjdySNqW>zfX;+in5`oB&rB3n&CfjWrBO+`E`Q$rvJ zWQCA(-rC%NQmxJ#)oua;-_#J&e1`^(Lc!=7U0j~UxDc5f^SyiM3x`d+zz8mdoPqc0 zUVQl1ufL#6dI5q&KS1Vwo!^%_hKnrY(z=cM#>*Vj;b-9Eh@>DR>z^8dt;oYo1-Hio z&2%kI-74L+14q?n(wxg(#=Q0ZluSiJcMAkKC?9#c?uHUAl#*a?wQX03?9LGy5X#mk z4LZyiA+J2FMk6s%mDIXXHp`wuVsUwGVQsNH5qPN~vbG?k3xQE;7o?sV!90U@+|vu_ zXZg~!c6Jh-o`ATy@I_vR4%)<4tBBhI$>g1}qCqsGLP@rf+;9Y{FNkQxs6b9|13~Bz zcwP6B9pWlcP{5!CUr>7#KQ{zM<;A(HjOgBLplIlWC5TE5;?^VQ;m5?FonT$12Xhq0 zOnauws&pRK&b0p{s$)9K_ zCvXx;AHEB@o;;Wf%jwwa{^)1FNy%KeYB79)K#FuWqMp(O~R7O+A= zYYpqITSx+vd8sGDE&0r*T9~uV9D+dOGq+;l=P!~zAQ5|Y=@!M)ROU;+QthYr^D9es zhIQq?b8!#`jJ9f4jSP3!k-)i4WWt@sQjhS=zhiX_Gz!Cg1C|DMFQKroP(4%0<7`E9 z2U1cFgkiPPmo0!WF*qc5IE=dDKXz^z{srEtYJYLGvyi7>>>6W@hAj8Fyk?jT5<{$f!&OoOxYEP^GRe0RrAfXdJ$GAY>QE{F zoLzWryLaMMGQqROq;6cg$CEaTU33y5RDZxh!|`3p4NNqrkR)!4l&|HnB8y)%?m!7M zoqLN{|`uTT!$KLI+JMTHq7(xk6#qR!Bc=q?%^|d^0*=98hyzD-eO+8Axln z_A81KLF6^YDKS`w1H?$}M!2ZFjG!OTd7j9t*D@1R({@*l(wCP_fE2;ey9I($SwOG0 z$C!Le&9+KovLv?-5>%)f+N6>RZgm9HiOO+D95TH--9llasVa|iykRb|KL4m5;ar)|n^OmW;~g3PeyVvAyWNROtqbDNc(;@LY6l$?om zVaYFBsbX(a+1*S$=lQYu^b|uKKBHj;<+@yTR(`yHz-J*0C3k5~6I;0_1pnsY0J;VzE6Jul+Ryo? zm%GE7JCk%H+{~jG(c&++OcIxl%s0Yev2xhS`p!ulrcoFENZ~XmC7<3OG@rGE!441`_CuFR}V?EfqYDwCfuh|DqC|)bO_8NCki=TNIa9gr`V#Z|lBQ zPuE*M%Nw`f5>r1&@4pHf)=(3lh=`g88#VoFg`b6m;WIOk&vekwu%A4FH@d^{nA{yr zD>zXd?Pj$-BM9pKB?xm|KAV%GrkdRL1@(>O$noS#KrbPpHMT0)zX6lDpi!M*4&f+8#+sw*gc+5=q+Ktk7WpUUdz&Bl3%K z5n)c-O#O;Nx6uf{s7+m4O?lq>P4P8mU3UvX672ed)0>bx^;9wyeK5Nho?dxp^y>9D z!V1NjH3i5og(oh?oZ4z~MGRx`H1mT!*qh7$)a*NV10ULavAn21eXbgywv+tEx0?wV z``gTbG@-wdh!ko>je~lU$2C)n*37)|4P|w|{QFMhPqfXpZBc3)>3@L`0)g-b9$-Y8 znp={ZYu|QjDaw#Q;-%J~{ad+srvDr0at!h@tQh|qdn5n0#Bs7Wk%HYA&*s*5>$Z;PwR0~^77{a^Dog^@RS`+JW-k!M z0WB=VJPQIN;^GDgpnpaewAG8#1#v`MURqj0ypeggoeqilH*n(sTgJJ(iS2D#9j+cUy?*0$dKs z!%gatOHTodEC7x*I6K}$a2VJ^u*EhU${<B5`q9=A}Y`WM>JhM)@~rWrTuxUFweJqZyERBLL5Y zm6wZzUmq-CmbHuaI0bz%ng13Wnr ziJOa)lx>uWj$JxCifadAfHNE4o^5GpdVV&6#wF-fmZR>dJLFmMsQ zjgF=Q+qYe`jHVnX7%-5|ePal9E13Y6x6=;vLF2zcaz^zQcYjA8 z2_0iuP*Z^g;2eMZC7%LLZjA2_QHkAyby?^3A%$=q;*Rh03trISDcp9SoXys9QWgk| zX%K!<5k5U8Ic~BUUDZaNPKTMBb)>Iux+15~{S7=N8zfUOECW2Dg-$M5k#e23bSx^5 z4DwZ2r_vWQC+ju<_cGkM<1Y@r`C>J;wDk0&S=x){_y@kW>xq}B!2ulgXiIRZGcCRY?7uZmg}v&lj#Lem2AThrr+0r>*KDcWh~J#z99MComNDtdN0T+!V8G@Rv4El72oQSHzdkbCpy z4}{W<)H{`+@dEr&dMYi=01j{j8zVCVB%Z1oYiJ4jNzj9o8XdYq;uZK&H#3`-pH|_F}?60(UDCV^{yygIMQ{uT5G)6!afnFTOn+M`4z3*jGOkY2p zNddJtG^NJQI`!Cv_6M{NhQl?bqlc?+B+3iT(YSsv71;Q$pd3S!6)X1fr1Qq`-2>1O zx*d1-CMUb_xV-khOC`s*dl#s%0T@)1V^1lDa5Ken8dIx=zh zfE;Q8$@O52sjmvyhkCjmJ4DDqeEh*h0mbA3qDX6e{biH`shx&wJ-0-P)eCjcYH_#R zV4Ec(1Zm`dfXbkr`|8$9Ql`{=`8T7^-otCQ{+vRrxF71;@g_G`@=yMS0$dJBP`@SZ z!lmP0=4)qgO)mXq@ofGys{CADCPi8hYm_jj9z| zrPQ}N%uw+OB!g(^(Hu;%NVVBdJGK4wU$rUxh?29r?1>s8BP%^G@S?R8sh^mMl&Ok? zHL%VAcwqN#Xfx{%3O%UxopwjFUirP#+0pSB4{@08j50l1{37x1X&024jAhC-pTlwM z5e`z!$`O@jP?7#O2(((^2{DR~UVpQc{JPE7jBfDrvGuz38S3zafB6551VwL=!}{EK zif!cA?7n=!kA9|%W;X5i^IW!)6l5+e$V9&lv9Vl2YnI}${j+rgszQ}|YT5|H0fOdS zgaIuCETt)O?6F3Qe&MJH55{IbGLU>3F^)9E7Tb}fXw<|pvv;y87Oo<`bn|XYJuf#F z`eqTsaIxqFTS+z&oKdi_LJ-GvwSR#i<&>7LRu0C9yc@C-b^XBVRy-~Dzu_{G;aW5= z_b9BO&=RCvK>E1k#aK1&JKoPbEQy@AqR%klROP&ES}mn4j7!C*Z_xk(zEn0}*o(6% z-JL*U%o15ZIrS0-HTOFe;gcOVu&VP~4_+yZ+RJzSzdt{J_>rQFGNsHEkE??=u5t74 zQ)qC+UU+CmOdvIWQTpFpk_N9@bfL=`uZ*z7D<)bUe6K@u((gyJd7i26;`whv$O;O0 zK3dGmxU?U|EAl?fpJB$%)p=@Xt%phl2Dp-RC7^4E%Sb5w(T5m`IVONUGFMVBtvC9&1tx4(mn0_Le2g54KsY<{c7_aA z?t6F-X-;*p35!VI!VeH8ATynPDJ#Q%X3t@xZ-q4lpAHmqpk@;)?m4PW$P;%j{TtS} zCvoteQ`v9gdiJsS+5J*?pSW`iB871g8e{>>kl2uRd+SLt)ZI?+ttl&IX!PpR*8;ZK zutE-axnluXo|O0elxR!^b{j(XQ89{jqJ{=&o6Bib+sx+UBDauHP5@R51&d=S4`86* z_ma>3ETAn%1$roBxSr#I70l(G1@ihl=lEJ*+x>dSMTLF(QkZb7;)Kz?Liy+NSgXLU z0F2=w(&KxQg2QbDb?E-V8lGGJ?sC?_UlxFDy4_u57J=N9a-^yDE~)mVWv&8foYPp>2F$M<{4FZ8 zb}g-Xirgq&yoW6D&t8*vggfSVgJH?uXj!qJo|zTLp8Zr58~HW~O?Y@>X%OsV?@@|( ztIH6N6%acDMk1`KUq4-~ibemof~Lp{s=K|-zFM4tt$==_&dD1F1n1~0--LR^;Qxks ziwwi?nCcG-Bo0??ELNzCm%LJ{MnAOQeRCf+qDc&y_y@w?#9pRi(R=-cvGSK^9RF;c zJ^O%@nABK9DZcQ(6_P<#$SyE}SP8gL-^fm~H(-hnGSs-$klqs;*O%w7;J|<}FW~qv zxad4uJZ2-0Ym9%)O;*6BalUmQC>8Slui^dKK6Q0GB#vlm9l@AeWl3Fc*2aXco`OHdZZ);l1XFD1V{@J)N@Y`)lA4RN*MKqmicww207A;+#Kk&PxW}CP;cii>Tg~LV+dA!7x1=jY{e-zOE`KC7 zp5f1PZ~sAiqFI>l2a#djwnTE1LZDGy+IksFI-)pt}PEV)SJ@f<55-P{e26fqLF5eqpibLMS zdUJK#{l9{gz`S>e$|*082D0=O{9L)N2NuX}LK@FgYiNVNH=uQFAXC}|aSbs5g~i2n zBKL;Uvnxl|R{{&U7kQEz{Ly$uJM@*t7XTZ)Cmh5MIl-u2W@~P~VMlRpHE~g_O5$1s6BeAvFD`LBj{#6fl-Pa^)B7sMGHmW2;vPCS>&B@+D&YD&HGWjkfD~ z1{X1rJF6H(B3)T4f%}yG?6_Xhub34jXQebAd<_m%xh@o3+x7PyR@{fQDD*6Qmrc6| z){W4^j224N+zjd+Gm9iUkep`V>Xv&I5 z-Fu|Rp4R#A6~xy-3*NRhw>$3g&-33OUdEtdU%e-CRc?)C7qbsgKLoUo*nlR^7}<^c zRjnzzh69_Aqb=A!OboxRTQfd-fMiXg0r2iX;}pEv6jaP?Y=mxX-++AwNzfyl8}3je zMi*$J_<)9(0|sI~O)!W3za%DWVIbmY5Ph93t!8>(%f47pSrP9rP&{&m{nFAZ0329e z-JQm(hI~1B@sXZxd1bBZtVk;M2YZzaG?BqfhZC{V{ACiH*^)r2{^K-Y{>7-&9P>E8 zIJhWc9pt45h7J(#A+dSbH4+KHkwudFvY-4`6DZ2>-Il!ZKHKz=DoC7rsK4Uq^DSu+ zml|@EhFVEn-2PXGr89&Chad)}^sG|cOvP49&l6Qdxh%0^K;-l8geTs2M|n*L;(M2r z;bJN(Ld^yT%$H;KgX-XRl~Y!3MjS2R696lZTJs=T4CuTP$;ar6tF;u6lKPYI2SGmG%{@8a4we8KF`ningE5H)y) z_`LVn_C2JStjbkv=h6Vp{&9>8tCJW;}SQZAkh|$BH3dMfr zjR9eR`;sp* zn)(U){~%`qsoE~o7o<7uOASlw=UU7IW>a68Lm7Kgb=74sJ zbM;=v`hPXK2H=m&&)8QuZux+&JKjGc$te+0yO?)LGZSUJkMM?50M8Y#WPe=}i&RX^ zIsCi@5%5V>v6Xtmyq0;i0V>v__P>w3zKJok!)5l{0E1mk?24~UT~AEI*xvNDRW?~i zq8Bjn%TRuIpNsNhEb`wGjg<7@#R{GoEjz4T@SM?lWB%V~P{>fPAFHDlA>fK#4II{L z-!GM0?~%eb7t&_Uucj#F+DX3r@59J=GA^0^9KIWCqw;xPC~p5dn{$>196vnq`yKf4 zCJ+6ZE{gDqcs?LVFBlnGF{!(Vu&c)xl zd*=RcjhB~JP%BWYPLIZ3inuR1f!EDrOtnR@^R#)tPGMY>2l?bjWH$mAz1!neZ91&a z4iA%;@ZS+F$oU21#a+CYW3?w|j^dc*ed2T{AE)qEa^>Jt0XZD|oK;wu0I$}$>pV~s*i+|Dv+Pg@Ro8`aY zt>=_Nzi%x?9(7IHte7Tcv=yuusU{n(@kn*5*^$85{M$30(Rz2|Uvvs6LUe}UfYBkp z2FHk3PELOzVhk4-Len8`Dp^f{Ge$F5wl2Lkp@{$08|E@UB=I=GiPV*_D~{bd(?uJS z*V8`Ax+jvM2&^z2>(RB(A=g0jW>og(A3&TdveB)vf{7iz? zzgwki6OSPuhe3$PU#bAzqXk_)ftKhyweyEp+y6;L?5`xbQm4Gl_$t z?~FaABe<V$B5F%f4@%o zjFP-N#R%s5yE3_}M8Cq6VrYXuFTe_fBr8`13pY~??B}kswx-BV`sRCIaSy4Y5XdgS zX35TyEJy0sv=FTCc0rzI#+K!5POZTA3m3*j4U>vTv7c#=dAv}jB58Y5zFVyPF%CQ;1BiI~e?3KgN!NU8HeC*dhOg9(}KCfO$hFOJa%NM!A|5|Aw<}nl~Ftcn0h@X0s$clUd zW1%(tg^q1-^vpVx3GWm>e5$jwY;5*Re4PRqPXzMwD{+I6ACpDhC7+y`49qaaG(MYaSf#ECR zq9(w+k1;Xr5WSAb-;2<2n#P1H*DY|15cyLphT|&lJ`$w0qR-ns;GXlfKOrJ|hX6<3N{tX3d#NBl8CC7EihgxdNEod#gU(p$0((wW~sq=g;_=Si5@drC=9Y zZx?@z$Xlkc5J2o6XW4PC_HmDpBAC*PUJcH$Xry7ooK@@tuA|R@#1S(vC-|tq#|ynW zB!j3hRA|apxfxP00~7(ML;A31*D~=B?Tmu?vic^$-~{p|M%T>@2r`%X037F^Trc<|LWPQ zOY5OBi~yPO<1hO3fxx2brrkUx1(?ND(fPHU{^#~@qLW0Q%f8|Z+9eALr2Mr1X(!aE zv?5UyQTT>E(}H?H=7NFi49|SPo{ymt@n}MV=Rxi;`;^-s^E-|95@F=Mlsb|%YfT$< zA6LNP6qT+vnn2?}A5NnW-mQBp5F`}yBVAhZqlaFJX)oy3zeBGCypAzsgrU=2)NtRR zH9|m&b~=fOiZuqDJc)%@7vFz1P&wdP!YZG%jtEU%v;%EA`EyhM-xrBSHr9tI0V&fc z!3}YH{TuTU9kX}tzP>T$UPB)}t)`xmcrdnWlN)>ios>QkbH0NKXniFPzQ(9WFBduH zxQ#3%I`xz+hxAwPf5)+uJYYtzn@OZ32+-()d>DVt_%%m`*%NSyy?5`RLpxRheMn%E z^mYSGgq)793-TgnH!aDSBotItRqNn3@7lm5JEOx^2@J4Cx z!N;x1B4UklZu%MO1=l%+U-kOxILR233~U~hn1KSNHPQR_#5iFN$Hn88r|YlwxSo1( zyO#8VE>mn-O?BrD8m?MBkq|=E!_-A5Ur7FWRSyaxAY9S;3t*Rn;y?M(|rS%E!m%VY_tSZzVSn@@Ky^u8lmqGt-?Hr1|n*%zDKc`o6x_ zf|c9<99D3M=&6)Lia3sNsXTZvUgzUl9;f#3;Vmht_n`RM1x%^(gz={+Z0XRCuGG8R zzn5veCK&M_pA>88kR8P>Xj0`b$Ed?(b`Ssds659G@JGq_V3<3Zc$b!i-403pld2u@ zCM`lpN+S!%!E3_lq?Gy15U3B9QtfL7S_I?Jb*(~m^ZHufpV zp#b|4ItKxKH?0t8f)3v@^y>S`{C|O+UwukK?XYNJGa0>RR)ejEFIy-3+%}tr5}kHJAhsW#yBoEvkaBQ6W5X4HnhI1uhqp*>@c)m! zI2W&eu+0INwOxhFf+OWVI0ewjYG6?efcQWz5J=SRG)nT})O&9k0>g?C zb+omWLRue)u9Ja-2O}U}Fa-R8F;sJou}C+1+=;Z}8M?wlqikSTvxbN&E(lygD^f`e zhn}H-qRWiH*wSZl&s)u+qy9Oa)h7ioDV0Ap*w;CPUx{UUahnzCtZQPT=IJQ}LRkSO zE{Qh04YGMpe{o=g+?SU*BPF}Z>K@cABvwLUKRXj7kV3Hh_8QdQ4aw&yXhLPLpS}X- z@-uev&PR*q?}fOoCMhp{x!hVWJ3}wikTXH}GmH^x)=H9hJE@YGF_>nqoWGOa|KVw< zhJ~~kF#jvk_dHEl-E?SxV<36>{CC#Gm zBG3Q*nRCfdPdx-ap9J?i{}o`VMoYZE0J${Tf%b4NLJOxrMq!eKQCKEk=XHA6ZJ+Xk zF6HIm;?nx)$lm#jKuVp-I%g@kdx?K{&zGRY1hqpakua%Gbyq_+-A<)&GXw6x2@rMn3U1aL#wD6^@k=@zpk24lx?axsYyJcla~?gPr9NmurIgS25D+ppRsq0c5{LgYjd}xL>v=%cIpK$%q~-A7Haijxm%nWzToVmd+hoFxNI^HFX^%$=<+2 z3VVyD+w?heW~=vo8RUivLbeZ+8Z+~rJ>VLWkbcHc!I;F1 zh3v_G?Bh!>J+gklG-#hFYiVE58a6oH$UQG_{maq!&w~5EcG>jYLPoT{@=kmr8iA4i zcVj?qqOonAK(!Cmqt=%IUjhGh1yll!)V#|3c!pP%fQA==NW^j^G)0fsVsAXETyjd! zV&{_ZVt;5NKnf@)Oc9t11swKSl`-gHiCz~QWSeRo<___CK708=;Y#~{H5C;jw1%7; zY(^29m;dxp_e^F+=6ef0EB318D0~7wFT1MKW4o1@2a8*dxmSR=5N>+m%X_Zil2X~b zh(@Em(Mu`O$C0Ah{gM@+vgnJHFajL6=I&Lx2BMgeSC!0`c_pT@x5M75EgX&4hWB5#jokgk2Jn3CJM_53>`G9o@R}_;EDzR@!5R}o9M~dSNg6#K zuL~fz#wluoa=z4)P_<)G{0MluD5P{4oi()Z`xQ;F%~JX+kvL#%6*kaoAaCZN17B!2Pvf5!s*~w8)W(7kq__6{pUieH z^dj)KxDJoy8Gi5Y5O-qrC%6+|j}?d2Fz_~To*vLQ=hZrWXx#!|>lIx+%3t({f-y@Y zRd}xw*rZEL#Zx3_XMdofy`eH`sY)j@zoM4a3OhEEs3n-qs?4;JS?t_qU@=qpj{e?B zfZl-C2^m$J*=I6J*zs|6xZr%E#$zDUE!#6^y)^Yjezb>^@-pi z5rB8HzCQEl`i;uVM+@YEh2Dkc4^%_V>5qwmQ2}^y7rd$a9fyk*nq4o|quDshyew&e z00v55o)PPYngq0BFq7{mG+K^ik6fOB?5C@BB*zP>n~PUMNRM;cp8TDo=u_E*>6i4o$S_mYpCpnyA8fkH#QV(!Cs-LS-8&WT;7|RcB!GSnxGL8nmaJ_n zGcpKeiX0Z9$>&;lBkEXZCD*KfSq#`?QhncA;~XthQlm45K<$V_WFfLQ1I9zIU~f zyVo>K9e$(UK6}ckUR_-m$p+gEdX;3v5~63lvN}9wBIl17S>eUDS3|5G=7(hdYFg&Y z;fXIS^>#w6dioobHN^M&CKmY_%RfudE0IbE?^vXj(j7VME^`^#P1C5O#o=!w6L5)A|w zj}}CD240>v;lJk55Z}zeEdBxt83~vC${&9Jtr}$*{rv3npA3um@(wy^@Y(-ea`jtq}e9P8BXpk!r#rM}iDqPzRe* zBp=W}qPlJLHN8~an%Xw(vY(?;M51%;sLa8Yqf(vhEG&T897OeTF7GNhVnp63EK}tVoLcoGOX}&KbnBj?HN5ngbT5^{}9V(NJ6$mkAyN2 zCmPn-#ET$o(PwJ>>=HdaZN>S{EiAS@>E$Atn0tC2JTCR;kcR-kqCoTt&3Kbu z9pfzY!}8Ipv-3^c=mran?+F_fJn>HVKlO%pZWuK^4X|-C&sa1$^gG+)u5v4_r;fo? zO55qw_Z7s*gZg*-fNL8{cO*^lSii|Nr?mllfPeqV;TC8uL{8BTIAc;xMviO@^Vi{<)W)n1+LO=luFMa|9%v{GV^2%O{e{TRuEQFDoX1V{Gpz z?)K;Du&geB{!hx%rrb=y-=VLT-;5Mp?(YaovCOE-Kf|cjvtInBqPxY}zNK?NMuh){ zuz;Is-f#40W}k;2@^3qmy@A5%m7(p1x8GIy119wN zA{LjB9G!w+As<^ls7l7!e|WiGLC6-^>J<*VyF^iFCxf5deUI~$`kLCxa0D1OFyoDM zA6OR=frn-2+a5YXLSaKNJ~vKf{;+_Jf}+?K@MK$=i<=%t}$ge)pbEN^K=i1Wj><()H;GuD>WnQvHlF-a_(usGk%RL zn0#Jt0W4Qyz}BPLy!{6^KjSXHmz$K?ltkECyx1;W4wKg6JCZ|7G7ETP}Gpy z*d^ODCSAR&QjtJ__4r;4DG}qS!<%Nmj?*nmdGOWsor$V0{h>I`&M$pB&RiVe#cf^W zbZ7eY5W0cs0|p)Vy8g4CV|z3E5;DK=D@Fg-hWJyu=H;B=i}RGaw*ts-euxnoJC4CV z`S>yxxEauu;s@@`~$7Fc;nKa23+^pc3JC*y_b4WMb zM*A{amK=Oz5+=7GIK1?yvUVKFVXgdur%f1jjB8TWKn}7OLgspPc14CUJ9s5jAJ)i4 z_hgqfFl{NH(@6zeyXGzQDq{{DVLP>I-#9sVyY_?Wb!boalgr%6uUpe<4f*dzbX`fz zJwi+_<_6})j|}JWufH4R#B2ulFxrv{AU8NG7Qph_w&ik)_XmQxLD;kev6z;?NQJ~f zs#(2g<=u@8A{RMx`kLp>IXTa{ z=R#B7&_$aTXxO-y<%%8uHP!CsR--{ayHQMXfiOZdQD!I`T-!Lc_JS5inI*on=Q}5M ztsj`biVSS%V2vBveZ~K8?2_pEDOy7W#~{3=P#41}I=Z(!51vS{JcL5dnaJ4~_)FvC z<7I&=fj|q@NE5v%%li-Ln%|CG4%4^{04+25MsGZiH)C+i`k^L?;_#7D++oRO!R%#; zF!}ljiMJ{a~K0LH=r>}hm2h?c>sOP5BchI5C-i!`u|gzIR}}_A5fy$x+~Qm4sg%M zRv_)gvG5yria4+qf3nA$Sy(E1^F!fiYb!_M5=YN2apLZJKlAbMg4?2-|4(*hKZ+{d zXPS|kx!($^ny!0k6HAZ)7_`S3g9uR!pFaOl2g~?fry*A z`dcHMByuuZy#RX}uSPukR8f%S4g^um1BCVCeL@##d_Igih`H-y`W4CFj|n5ek1$wVSag9Fi%jvOVwlSt}y46HcP2YSjyn>Wp-<~Vp z+iw)OGoCz~DU*FgS`GkX8ZLcVa1p`hHV3jEE!UKSQ1B@b;<0<}GlB*F7Qnp#Dr32U zC~ZG3_&f~k>*axG-rEg-P0>+bL6G2Ay$*{a70Q0}R67^akhy0^&v-al$2tNn=6+{0u)a;sAr#WBz`}Z%u&7I9(He-=#n40#XX~-p%2rW`kCl>0#@=hPx|35T z)I+Ltl>OzGq8LR=^VuXP?+=cjfGfVbCv@P{VWUhHMa&{(g1_*F*gUr!qQf>Ych8x1 z`DX?`_DzZ z2JWT$tbeznHWNsf395|&g$?tinFyMo*^k}mgf5USje3|>kO;*#V3W;LD)^#jvHhd# z`C-Ae1L102jS7>Ch0Fy9Jjg047B21-2)ws z23f)ti{H=W-2Yj9aNEI@H8qd%p|b!t$TxzaV%3Y#C6~T}t|DJVYFj5zF0(Ol@LYK| zSlblm`Bk>l&dBN$iOyH+ev_QF4Y%8ckK(;o*P_p*x%}n%b<7|O90P45BoNn=EK{P+RJTu+TnTf`u5hXR0|V6layHU9rNLVsX;ytd@YuhMq* z;1~MpuCd*ZvKMZ2U#+BfdKzZ)cO5VI1!n$w4}R53WjA;ED-%15j1iS4TJ3_-m(0;z z%EIz8#vB;t+UFRVci-Ohq(i4TB1^7({INiUf{ZIq`tU;aA1JT4Kb{Io66FIX0(BqV zEfTfWKP^0pn#p1;Z$V%0ULy@=zQ;g$2F>VooQ6?By_#28^w@D)$UhLkm}YFjyRUEF zk0WSZ+EZIJWORAbU8q3oIptwPo&76|L8{NpdR=E8Sck`E&%<9wu;H4_u8k6=HTS7Cr+-MdF02zwBdf;K(^=L9RO z?nE$Hi+kD&@E&=@6(cYtOs$`N66X4}Uml!x9iU#og}EjT6d(&N#y3%Qbym8`6XT@> z_dgK9oUtiInzF8^b>=YoS?vS zzvv3XyrAQB=0Ph1Uu-VO@<-u@+j|X<9G+mwHt2@Q>CqsnESWN=mpnJYbi@h<;-Y~mu!QAXQm2*ns_2*aZ{00mak~*X7 zcsRG*{NeDiT6a&3|9vapax>Rn)CpMLA)F!|bjM!`G9%burvtb$EzQ*|DlG}j#ZP7H zT|~WUVylkG5v2hLzwf%oV1=neWXAoJ;pa-4V+I;(F23CTT(dpFqs&%6H$VKRoO0Yl zGbwJoM$~eum?~y$ZM)WY1H`W#nQamM(-~Alj>5F-IS!NB1Oa(1P~Gu`p`{9PpGfL@ z201U0_#KNn;JZ+uHTugrs6~V5P^7&V#iwPwn3>r;2BR9v5 z(3RnM-;F!^!BK!Si%w#7FBfoLHIkG0@iLwI`4=~q# zbgA7;9ue*{H9>a5gw;RjL%~|`@Jl#NEcEq@lA0 zv8(35aC|*?s5|+zXQZ z=dTwu#`3Lye<@lHV1QP1`SixLA7+VOyP;lhs+k4R*CaEwY0DcMjm!X2gQVAC19Lfu zzo-Pa_!>KtiN(~b)8KQ@Bh&FBDlRN`i43T)uaGc4KqspeSaif=3lVxbmil$X5`*$% zcAGs5P}F3(R)DS*BG&+vJAbA9Ey;)obL%M^*-IkT=O;drdza**>lHv!hqRD+Ojl&e zVt&>xEN-I#<1+OC@h;5TS&t^Tl=jm!s z8t`quEL)%M)@uUZW$9ky3%n*~1NL2OuNscesi-Y8*Ow^sUHxR-I}(F$^_UGcHpm8U ztm7b2g=Rt4c5=UeuH&f)7kx*Z63M>wa=g>v&?+1o z=H$^@WuvM~vS}x1fN>#@MG^dU8|w6J;G(k$xYS3T7VsyN7(VH7__}}5`_w3b?vLI_ zHbr^@QAPq!h}!sRPYHvxdwqoVNEapBr?1E5k=H`~%kj4vmVPjy6zjw@r9G2!?hVb2 zk{Cxd+<~T>_dSyvXU=lhN*<)N|NJDEJRN9-#{e-g1wcqXTcuF-<2Lx*$TbJ3b)LiM z!w@Q+NrSJs*wuQh!X0g!g&#AAV^M39_IJtYw^|t;MKaknHV&`_ZlNwC7%EAMF&fvJ z$~%u1$!ufh07EngT2WPJe1}xhqW#9&Jx9;Z17g!rhl7s7XmPHI zxOIah(JEQG07VPL%85&mQ;!CV-jY zIDl_ha9!}*55?ENeEpr7A97FL^-N9&Ma)4Qk!#u9hmP&6sr9y{J5IeTZUopPJsh+AhG<7ImZ zvcAXyr=l6#v(+ET?elEvqfaDhppkoX|Ju_yAsvEEvh{*Gw-;k(C(J-dyL~bdK$<83 zy{eD_2tRECeb;jR?JCB6D_P^GNt;m`Q2Lz|Kb|s8d}DWWaFX`?q&tASMm%18jt^F@ck@Wx!C@){*wuu<< z=`8NzJe^kazlN~KngMb}*WWt^Z9j zqn3kvX~~$pW=z<8S3<9it(0lv?NnE3lLtD3!`?K&o^~v0g7gdmecHTjTNZk8kCODU z2A?WpHs7R^4Mwc){mS!tUS3R=XA`Sft8nQE z&##X+RZA30bV}>$LB4R$A&a9T_*C@vJ)-xkZh_{VZ&XsFpG6IbnjbyH=#1C^%Oz%r zjYqwyFkd>T{6LSz*5G>9l)YnS;|21B?fE}>kRelm(ik^$uzY+IG)2qz+*b2@ zN@*)6nji5am36-EAIwkrp1MK7cdo+V|H5(1$mv7Y$iEoiBMq(UPX>>{ykkqYRCBPJ z8RDkoBxd2q1Uu1g`&&$rC7rU>G_`>0g5;+6q7v~j>z@nN&D^py1HM&efu29YBXdZU zWJ(L6--KCnr(7ku)X&f8yb!; z5>if5`UFVb#RAh9u*e40yu*UvVkdQ2-=fCzT0u$h&aAyJ)ZzT_CctPmSj`|0g#Sq) zd<`5Jl*um6C1Y+_^zEW*dX_#oIRifqU&vA_%9ZH2`97NE{o~iphT<@4P?yWrg#Bd7 zlqz?UfnDOK9i_lR0Joibm&7kAe?1Ffh9`j~xsdC6KEf{uPS|D>1TxfwQ_%(*$B1}}R8hZ^xKVv*EduV|ed;3G4 z8SPb9k)GID%(Mvq9#jU;R@{6LBe;^?87K%Q<+<#lm%4dUrcdP zd_y}ms=6qiDKhYznfx=}QV!=2?azaWzMRIqmvlHs&E-$6OKD+exgHaVY7iLnK6Uf2 z4?&D%T0;G7r0mxI5+CcG>wrfBJ9a<(WcGh$I@NkGjJFfY^iB{<)VwKNG9PI>o1< zjo>1z-tjdMd_AeqR|hXP}Z>-)CS8#{eJ$%AnR@shTa6JIM9^cHT|wrD7+Sc(mPvVpUGTl=F9-_%ddaj=K_BJ6jsePy-^Sod))B z7PK`Bwv%CFj7SjEfOx@*?bvUMB#O*-JNXgR9boqhY0mk~Wo~a$QX^LWL3<+OnBnxa zK;+Qy(@#o|Qt(Y0Iq!;#y&`bBy;y#yIuyS6xe$XRX%(J|@feq$g zzH-db*F|sE-kw_&w4_U*AI^6_<&?Y#iI}y|);bnfMg;n~-lVjiA^>TyYsO&qeHZqn{k_ad~Ih^zR^{$9sj zC-Fz)>t10-WIA6!+xVt$T5nrNk8sN)#}rorr=D}-|JM{7CO_);*p1zy3yDN!O&jb;xXPZU0yoF>WV z3Y7a$!rk*ToQ{cur{&66l88Q%+LOe*!Flfdoe|cU*2B8D$G6`G#zb>En#7dZgJ$P7 zP25dE3$l{SH|Xp`ImZpsbby zlJtjssL`(V-QDTp$LdT8Q=6kXsD08AV(~sF7S@S-7KvdHDFWvaFg%?K(c+9w+WJsB z0S5n1pc491s?hOK@io1(ye4J3X;mam(AYz7O_CLvx);H{8Q*xfhO%09}z_$_889v$eiFU)ZokgkcMY2qU*|jtc~{eGbA} zU7iTiH_EdkQS?j>c~Vf)drv98KlQ+H`_9eia6#NZ3*8s>d)hokq&i=AW6b1h8zGTL zMVDMpt;cG8?pR6tJ9T8LVJ=?GLXXh!*fd1IwSB(%D%GifvAX7b3QY~`&ILCLmw{J|_K*AWtRikH|LN!#52(w=rvj_m;!e|@*w0~$3?{*zenO)C zj6Wh7{-F2mUo@k;yCq8d8~4ANeuz+HX>_lgBJ7w=;?-|;er*~(p4YyIS)fUupzEqVYhB$Oy^w1-lp3WmyVz+31c}F5Fa7jQ%xf^*O z;?RGO&3(UiQ>9@hECeyYjbUyJ5)l|!-)ZKCh4Qd2@q08kCu`Ms`=b6Fcl1qaIP zGsOgY3MGe%=ivVUm+m1PKT%)uQlNk$x|K#Ko&RhXJX* z5KOfP?qy0iWuV75n?Y)3{!dwMUc_jS1hReGM%SeL&kyWbO5ajM!^H9=>vGDH|A|}c z^>;=h<1#$&_d9dZkzefjRbS>3y_|YW7Qo7HENy9CUSg3sYHm`>0BnB29u?!T*p%E~ z1<>hSs`{z1+&iEN6EmK%2~$QV&qL-f!wJnVy$R!xh6nK3&2m(-u}2KNatvBum)3>h zA>^WErPTgncrsBTCQKUBy$AXbrN!i93vSiEaiiqXu6l_dYpW!{!JiwWI)66J3Rq$% z6HV*RO6=T)*`KEuD~x~E=@~YJ2sJJI05Zb8rDXog(XCd;NnKP?nDlm`dUs);Ebh`)0qT%;GB zZd~4QEpEoStw~!grTzZb_VLFET3uKAnc1*`f>RXB-ldVJ6uO7Yih;7fg_zz+op-5H z9l}0B4uikg+#Og5iKS*LzV&Xd$vo}=L+aJ(9-i;Fd}N&I(;YI#7UFl_!sVob$2p8l zF1!F1?l~vZ^A;a96yHzCY32ugAz+39ha#|7K zaW9gSP0)4#-MdykFb_=3jT5@fz+|!tlV+((*u>piMwKgHnf#&7Lmwlrt3nBV<#&!l zok5XGJh#B*TH?%MU#ol%)Q~Fqjh9@0J`@0rySMi^qFo}F$KImUkqkIBPYl^$sVMcd z zrK>xMB$2~$?lh8ao^| z?N^9WL6G!7Fz^*uktg5nvwr|jaC&y>rG>RR!sig!B(<@Fvq}62Lv$N!^(Y@YZ5B6a zfeQwyW~Uha^7NM5c!|#V2qqUYDz6Q^xFD0o-U!(%rjML+%~WYYXjxjD9*&xpc-(Rr z6Z-t1Hm8%{0+;7~d>d0P$xSGyq!p>VxzyoIh@TeRw(fYh-a#ixm2B$jFl`nXLY$dB zPv0om`H|dF#BGbAsT4#FmEubwUr>IJB_PuZw|Vnw*SSN03;>U+U)qzpr1VW6n1++& zPCfuWMLpYXyCw*-V8${VxG+FVAtYflaFS!i%b3yERCESl!4lfrcU-?1YMOnU52tX^ z+<=?kCh%T33kso;-3%vMH0v1=p#xSSqLRY?*P@#*%RP+fRoZ{ETe400n120q^y0+l zQJ&d{Ns|K!GmW1M^v!;kI|ons?E^x7C1A!M*;-_^5;r3F+Psj5CuW29UKeX_P%CQQ zizBgx02?4QPKUP!H}s4l>Z#@q6zQP+1%vb^@0VAM);9pVgT}eXo7z$Y*A;_eQv$*u z$KLKt^69{%9jgpRmf@13#RfCdpMb+Xh~0Up za*)7PIJx+#d)exNDHSB?_8ir6V+}rTfoXwO6NPra{O~;HcJUSuXq;)t0^O0)?bL{o zrAMXLt6#0%T}T;|dHa!_A`2bg0t0NWj5xbXmWq>mG=;4qI-x~{szIrl|kItFtRT&cR}E^PUPfC%YsaT8S__lQP_4YM`x zJr{xDuP&F^&~@m;4gFkA8guM}xcL!-yZYzTrl_x;WN4ZkVk^*vGx!hDt;@`@_$@w? z!eREO^^I#&uu@18=0j%V)jb<5q8w|1%V!vEBNy%!bptK?oJX4W9#<)fSLXLSch_

D@K&@N*m2Kby?8{*65SwDAPLp^EzM%{!i65s^gd)s^R&=}57&n?O z7Jr#4fQZ3FzYPc^W#Qv3cHfP2_1Op8m9c<0S~w}S+wQ%|!%O$YqTaWcQh?&edts48 zpu;-Rk#sd3-@IIlZBYbRPj}A;{K#LR6_hYoGDlDIm7t&pg*PH?7WGLOhz|8?n%vIl zZw23Gsg_m|19^iG?Ll7=`b8|ju|nbo;-$cv2BjIFrH7yV%=PxAJuS`Z*uu}mng0m1 z$<)6Z;oMg?6Ac;j@_AWYw}Zftj3&&3pI7oAoF*qaA-RWGg_yic7@Pu{4(_;^TRDsz zZ|#nS_k&FWa46EzLL&dtk-)7`;Sf^Ai{&|3-p)U#{K$BBU$Zg|;+RkT9Ircibc4;U zuMPF(y-e}7!ANHN2ytgOPy)Y&v?$zL?>O?^cUxWr0#maLRYk}?E?cs%JE{#g{Kg<| zr{ynu;Lu*7cg5cphwq$TkfM!M@)g?ku*wse z#X)Ej^y66{JLF=fsr1iiyC1puANymBQ~^rZKvtTe3u==n*p;+Rgtz+7x)EkaB}F*fRa=)Or_Ez)bhH!HtwvX6GeDuG%abtV}xyR)A zqb!P{_&AcgIJ}e?cwABJ95l`x+*=x7yXPuYg;jXHuS~dqeEXQns3>;-W;Y`IGs}w) z-!O3RV&2w}eHCx@TCHrnXaCI7L%ol!E>&%;m#1!LRMlpz{NdYjf9j+1jFpps^dW_? zTL>p_Y-zRIH13|&IRcWb7=|&n(~ko^7_?p!=YL*oZc4Qput2h6jM5wK>BJOSZdoQ{ z$%+I5KjrTe*VH*rqI=}#M_(FD**~Ys;r*Jhzh*9M{Xnda!fbfVZTp=qT}#8sh2OBN zCbgXpZOSC~o5NR)Gy7diOb3PpJU+?=v?)~=fuDynA0(EQG2mB+5pm)o6%?x3SvAQ_ z{56LAr$k9I!#?Q+#-BN0+}t>B{u{6=5>bk&&xS`pB1ausGlf}MH5XPRXa58-_R=tw z$z`5^E%fsZhiH9fS@-?W3Y}J=`cJ9s7z03{B+{)OVn4^dv(|GPaAKBzzAyY*n z%Q%&NQtqbc-t@&$>$*-HaB<(EpKl_~MGVVo0@E6?G zI`{n0l*yv0^!O8;!-l@)FZ{mI1v0$ZYtC-x{XjGD%p54DZpl@uc?${~^+6B9WIP{Eb%0F)Fk5=2ad+4cK3n@q$2eI`QTt@VA`C!wV3NzI~_z1@4%;)nx5FRl`--$HK3e2D*U zys&s8JFxtO^IMwSN)x__C^bA^+Xh@(S;pnw6?{#>2XEcS(Wy}`3{b2_D{7bn+9 zmO`QKJ$8d`%Dbd;BvXo7Fr947s2HI%dRFqQk{%7kWMWl@xJSpfU(B;VyZ1mqwqVby z>NkginSVz<*s`FQ9c$!5!EJ8@m6Dmmb$u zb*6B+JD9R{x3I=u|BZT&BjwXe__ZOUN!H{}-;Ma)e}ld?bPEgLGhi-K67k0WuxqeB zt!uo=^EJi<`-BcFBl)4>y;rvD(|T2$ujpib1Jg^0&0W1;Bt*;oo*i~%Z5kB~QDm{` zM9<`iF3AvljEV}c*BF~aM0{`Rka=BopN2#w18`}oB`*9Wf7<ZUM?aKI|W*lefd8{j7)J~q3=%M(QY->>j;LuzTGfRGmPGA%ap2}4ca z8~Zt>9WP`NY0@t{U}zt3b{(;n$x2y9N9U9S?;jxC~E8nW`we*vmqUFa;pQ5hla2&5b924 z&o+3jk-t~Jg-ga<$XGtPRRcLMNnao(f{%W2(dgFIcDyi$Zczu)k26%%h?yEQH&n~1R~gi~nhzv6gp&TT&lEKKDO7s!s-~0PJ;n24F*o-@Y z^bp(I4k5NkINRdhi8!2|E0&IVRkJM*thPD`tQidRnvu&cEsDbd`~Sp@DTfS$${eM8l_rJrf2n$uEV*1BXs&V7X55FRp#$D{=!K)(1LI!x93QY0oOiaq&_ z52wNpZSCml=~=G*`lMfG^?a5e9ZLba!%ydsXD0H@_Mrl$uN)pS|E%Q;QPex7o1afH z{6g;}8D&;o^wYUhB2Ie{N)9wvQlz$~SP@RMxA~^b$j6BI>a*@3&?nu#fB@S5V=eR?39YBC}wXYmo7Y!Mm}feXj$onAD|UTpi=xwv%HdTn6dL7`8}dh+|; z$4{R=eEisEd&~Pq)?|v@DF5(s3C>H~_Yw%=;1P~&?dws-R~a7;HX&EM9tu4*J>xAA zz1?{;4dY-GPs0U+Vw;y>jSZ_zo8t6$&poLZr+Sq+Ik@0i*_C*kknmw@RH6ajzB-3w2LLr3FH~0#UKkE`JUE?J5oZ_uoWCoxXu* zWKXpk^2Vm`>e#iN6PUc0orV z9iQ|E$5vH|Jkrtm0FNM#5C6g;HyL&HW+@!gvFe#Fx?5;aUJA$6ZcbG8?0l{Ne@Z*k zK&ZYxj$g~j&WH>mBZ)Rmma>bnmB*4ovSlhnp|VDnq_KxAMfNNq(PC#TW1Ezc_!rr- z%a*m!^SkwbmKV>v#~Uy1xo7S@=iJ}#`@1ve`vD4uuAZLpEkLSkEX#(H8zg$=0z#P% z%Es>1)t|VX-k8_b5IeE1R-V%q_3+pMBxck;>0Vqaa~YyqVZ@M26MiQW5U~2t$Xl@Y z;~2{ccMGYjpO%`Q7}!B`BLm^UCddER5&({rXbFd<=w@=~W} zFOd8O>h?=Za}D@@j~w_36mc?4^k|EjkbqdG1E~{pmNB!-wmI*>Yutlw`!l(Vij?qf z`QArY9puz~Vlxc4W*x2@S}XE!2%4WuSsOla`_!f&)N|r`Ryl$3%l;_|HQ%&0`BD_! z_km5=?dE3f$G>dA$Z&CS@m_K=TY6S*T3=)FlPB%d1Yn`@Irl!RpDyp3JYDKvnxzw+ znVwFWtH4ESuP}>eevZPovWs@ER=I$FDL22;7+<*qQCEvAG3&TPIv!*le)Id!AzdxG zeNT_>>spR!N9a?fF;@&cf8KZ@@=Emyk~1IvV}CjL`#OJq#R0I!1~7(p`?2IW(^s** zxc0}BBRSR8JL4q&(Ey+{u%K&77xC^kwyyaCPioUS^U zDGqlmS$UH-W8+M&tw6-Y#KKscSNc_Fp0JDd{Gu|UT8sEKE|%^_KE3*@fKV2+_8_Lc>3Vjsc-woWk+7jdqrPVJXB!)kY^s-{oO|C$dudCas zW3wMWrSPZoMB{Gdl&-px+n~F!*!9P$Ok+zfGqxZjiNss^Wn8iZBtqa%uhPpafv=Hf z&c9C#bV5ixe>$h_M=mfOzJy9%F|oQ2TA~sR=O|6Ae>Y5_)0cHf?>gd4=BtiHZzxgu zTk=B(^85oMNw*_uWHNc9y%gs*(8->ij6<4v{yt4yuT{@5Y{}7x?8ce|jU?av=|4>7 z_vMg>*?)g{<}p7IHGQ;4^TqL38ww)PIOIzZga}04z`!8* zZ7>}2c~Vk>m6DQ*QH>!3e&nPG)L~tEccaUAE5R4L_oCBi#Z?2?DD%EaCZ9=mCzfUN4 zUwF74N44)g2?NO6f$7C>E5gITtB ze)y0LvBPq0Yqc)gefncYMTLM%?Ye|^v`8fU&(R@CdYyaaT)*qrnhwP1BATDt#t>Ht zSc91tnfflh)4?fR6E}FI*gZnvH3vNaNZt@2&}uRV0)d^Qz_e&l5T%1EFShOmcp}w4 z%`XI~13OiH%UejTYIhq0;g)Pi+v6Raotprg^~~X&*a7or6sJC5fVmC$tq!%v??-X4 zgsXkWX8NnjT1aHxAhBWC0?G^V8bGD+yB4B}37{O`@;iMj44r>KP1wHIfH}7-zpvK& zdycN5AwSp-x0k?0vB8&ghpZ~WKdfQMm7JL=wg9Gxs}Ag#aj>+6w5DFY^!{XngRD=# zCs0S})KiqbPbr|DdkZyle#I~n&mcj&fpu`$6a6)L+Y$a{F7jR>Sc)eIK<>T~W$Gq~Kv!+vD z*BGIJN2HdiX@YB2e|rhApv@6(`!^{p(8Ob9<}BR$F*gl`6~Oee-L4m{-CQ{b=2}3$ zuI!v%&MYZ07WfXE0a=jYtY}qMANCl*+<@I*L5NFAO3o{q8W{yZQ^6}&u3!}ldOe{( zP#Uapdksya)~j~NCv!k?@GD3}Gmr(3I{TwL5Fx`aDl`vF9|%^5T-pgE4Ra`}rnXD* z5huFs*Z9<_ASfZcBNhC&l%c|5*NeSRTAaQG0yDkE$TmwmvLWr)hJB%V2|Z}#pVwk9UU>p z9w(WZncdad<;ROsG8*o%#g7C&y#tVE7?%~;9=T(AdAYaR`}qK&dWTD=QVu_>db0qlUWk96d5sm?8*t~**MqsSvM=UHWGN^;Fq&U6v zhM_A6*xlqT51rLdoBR2xi0cKlT?p$uOMME8PZ_p1f)1?*gFiM<{8iC)PWS=-8QkJq zh_`>)r%{2%cORMmkZXQuoDLQ#W3I(l0fGngMjF!de;54 zDzvQNLFb}5ZygG>&mWOzYP#`$n zCjsYyOI%Om%o#r9?X=~YGnlf^MG-MJt1-KEm{daOm2R#aD1H7sevk`+ea`7U({5w0 z1(4L9MRDUSclW>U1Zr?u1!J>v4wd+hjZU+!& ztm^Y#yO$PJppB!Ek?7}F^OgWmWj>!8>l8JAYv!T+d(~ihSRHmFNI+9%q=1?Dl&tKt zln35ciL^aAhG~ap>wayCz?j13dI`8aDsWHkldieDpFR5ke6?V>GTu2fDa}=9MSzoH zj2WH5VOZ*5E_xE`BEY$4?2Kb`jM}Myn)Bu4XhSwwfUDh4O7$KSh>4HiGvjfylSKZ2 zL$r0BoC=cUuRH{U?d@Pp`T_?5wH!d1TAG@g*@g#mUZ<(q=*EiQ+8Egt4l!rHn*Yzw z1NRA6%g&)kF4)_L=cf9cfNIzjCXi@Zs-hS!%Stx@)I=yze^ZZ2@c|c1uaIJhy+VZE9+YW^A2k5h`$1GP*CLNho5MS}iRJrgGG$ zBSoRh=~MY$5*Z2jm$bk#gEaY%#Q2X?`JW2pzYg=F^?SdWTI+xz|BQzc5T(iR+>usi`*8$2M&Muv zLgB@FD3L8${)z?w#$o|B({@AKhG3Q?CC@`(XA%NyN>oLq ze|!yQ9Z251{QR1+;>ACqT&}+AKdv;eP^scEV-8@0EXcBsj*fUg5h5|8iCq*+tp@nd zAP6z^*(|YtE5a_KjDrlP+R}b}0HCk&j_22Nzs~{jGp%gd#}Ai^!5UA1(9cYg;J*s! zq+$NLH4LY)VlZf?i;6wAhrP~hL44qWd;+O~YeO|*W^G}_x-42)DWtkuIjLjJNR2}* z^PU|jT*9|5Lp3U7Wj7ErmKE19FxU{bG0hPI3L=9^Q()t=Wx!(c3D)PC^ zr3K)_0I0*4eAH#dX9iRbslU>_+;xcli{GjhTCIc6L3C4>xY!g{@5a`NlSEz; z7y|g82bppVl5}ZlDVp3jX6)4%5Qr~)YU^!=FqfRk9U%~~crh4^7q}yoTpu@pmoeuD zDS=+_m@m+5wobLpb|euPU_IRBrUzjh*frU-I7$;hc-~zJMBk4~gAXtRWGEeg4P_hN zA?LLm!|4AO^yuTXtO5K}eF>A_&ym@`jwI2c#o7N`JpJ1BptZzq>ub?t1pf5242VxP HY=iy@e{AJq literal 0 HcmV?d00001 diff --git a/training_rewards_accuracies.png b/training_rewards_accuracies.png new file mode 100644 index 0000000000000000000000000000000000000000..c3218f5bae2cfbda9b376d8111b9418c6be65822 GIT binary patch literal 48034 zcmeEu_dk_?{P#J?UfDYFRQVncC-b1C-DEm%ZmSeNt@F{$gTaU?3yH_NsLv?RgU3u!xY!xJe@J zZ0y}@BFU3In3#?_^ViAd8azbvCz2Gs@^*GNoJBgkmr{4?l^Pk$*n=qL2szS1itCtV z2|3`4QMz+}|MNZ4|Njq;wEveyQ2j)R@;zD?S522>%*n}Fcaq$)>q))gzLe%RTEnPK z7TFrm5r4^SeY9+Sf+l0IKri$brk48AN7be-!G`h4Zp%lLKGNFXd-JpUpI=Xse0fdG zX870S{jI;7GtJ1CYN--^UzS9fqTLS{5{2D1^pOub+F!T+y)~I`U9go;@@JJS;nk*> zeUVt$*shhd&2TaL?6B9j*mYf3K~b^%-ysPJNy&>hJTlC>ya6JKk)j7%sD>Cng~|Pfs68M9pJ-dVEM3DRtrE!oq?My#5uNRK(xE zRxYc9WNwo$FX5B34F4S})!`qmesN{-XL7%;VA*5K>r6Hi)wGWvKfZdi_jk^{z5+dQ z$*mS@l%Jk`9qm$2T611eJ@FfrU^Xd_>nmPx-_cU5f6JRv20iL*bGRg@#`4HmXLFM? zGGYq!D!!YR;LRV4k2~Q0?(a`IX|!C~;uexV*?mNaheLd7^<%*)`_renK|On0%t!aV z^@=IeU+-_b@AfGPzuY$8#Y{ESrO-HN_j|fD`k{x*ZJ9$TF1+%@)X@_W5mla@9tm6h z;Z0KI@o9jM;^g2!=V=vuA1*N~ahQ?QeEisCbGpfWB_~n$#3RjLF{`Qlf^Sq%5FW~} z!~A=%%vlujMzEYBJP*>NK7al!X4^dQK}2TimI8(G`_}e$E@|odiC32j9uy6kwZCFL zfaM*lxy%}(%>DP5)ZO6VU_uHCdyK`mej~IV%x`*q z@g54LTR;~hwa;MabNDn&ffLm@UggX|6~1}A(`(igaBg{|^jV%kk;w2jOX?swj*kyA z$Wgp}d^mn$C*EJiLh|lB^Qo`!L>+9kUzn@IPU22){C?YEj`ABa@?{MqplHKR`NqUZ z|07%-Dr%ps^W54SGLp~gGu~P3mT=!>Ki#irK%?+*&@{y7{_U?vwnox>x`dwXkJ;-~ zIbEzj{b$|M(t`49e@Ve2;V0N|Or@B0o|;Fs@$1tr_BdtTb@#@Tl@-{Pws7i8l(e+L zIrkEAQ0Xrh8T0k4s4Oilr7;iXu_y!Nkv>`z$=9nO zmpMBYIU_iPOKwfEuMc18|1<};vsASAOP+#*mzS`p;q)eIdO+K#_3c$X6iP0Wa%N_R z;g&1^M%5A4?W2Sdc+O5z~HV;C<`UB3k zD8@O*jbxE$v;S6$+5;)12^&vJ8y4Q`ZNd$iOgH+wV<+4kPmfKD8M z0*acNG#1_Of~%aDM$pk_sp=}rX`y@S!|wbB_2bS ztA#blW{FR_bFpJP#ytNRoz`BmYAE`*w;Eb8<->eU_pP82d9rHA&!4KbJ3Y64 z^z^hf`r~f>6zOHZe*Ig=5Kb)tGb}VdDrTmh*{%`|C&jtW`x0E}1L;FN-_yfSM(Fnq zLwQ$4M5yf>PQ;v?oPOnL3rcSP;8Ipov)k2;K6!OBP0b6|;s8qMecy9rv0*`3hYZ}( z+F$Zrxv~X?I0v`H=DSoU%oKgFR@z(aiM31Ww%A=8p}zN)|Mpb9_v(6$Ni%-b1sOK0 zGA8@_Lmr=l83I%zQb}djL!6S5EK}ZCR_WtS`C~X!2XFwSUM;1+flG2N^_;Y>$jmLO z*cY*ZHhr*|Vt;U01Q(Rij?sRExi7CTK<{(BrF0DY$b03AyoLsqUG0`4Qbxzp(Na@x zYs3Dc)`Nb+AvGJ-kut7xZPCZ8m4}Nd&|tpP)mhjddrygK*TmdYO%g)G7(q{yb0Vih za_6Ur^4+^=)coS2>FQtsQV%5--Aq5A|<$L#DE?`4Q4c z=Ag6fS{EwFW2b+_aV?Kk2qJg&GxY|w+qffvFNIp#&2y-*=;&5hlo03|+e^o=^2i+W zI^JqO7R%}ji;+2HaH>k35_4WuJ!KO#s%ObkifQY7b4B=RCyhj!nok3~ZWiX?L6^}f zPR+!tb0l<)7Nuy^TmB~jP`O#!MTV6p`(uu9@Fe&CJlZo{f_5Zq{)19eQ**lK7N!My zV{Bq#Xzrs=gJW*ZA!JAie#pu?w1tnBm>N97G+cmVpLEMjz|ec|ag3REp?-L#eCUVb zVoKk`E+dDNy&9f=I7m6uyE662b(j$R`+ziJwK0}Z*3!Q+W1QkLI$jCx9f^l zXF@Nu{Y)0g)W|J1@1WwobO{+vt*mb2XcX*clSr>*U{Vsp=~=JjPE;>JX@jlhTK&0m z=WYum&b`q#^q;W9O1vf6t#-q(6(7y7OZ^q}ounQ=vKlHh&?&cJRD8t}j&u!ZL5;Jm zk&gRoPsV-EP8h^&7#4fdA|J?{(2&saKOZcsEg4%sfaX9FEawm1DSXQC2%}^>K9#jd z{`g-t+oda4NZ@cZ{mPUtF>b4oO%c#2iDkh9ViTP@4^fMr)Nnu-bN0SR%=>F2k1!szw6qM;UJ}R#=(|n4 zsGNIsD>gYf{B|I|3ACfV(S0a1WB65+AJW7pJuwSsXV5UFGeg;MQ0C_5#$)BSdxhGD zhOb~C%jFG-c?fz`B#qV=Yq}XHzHUhSvffzHgKD0 zwJ#m9k?vh^xj6!zZzSLx$$@Q#*ESJu0o$g;Y4Wpl6RPl_H*emQjc#Gb zohe9&iA`bpAB)vY^n{SJcA|>c$10Azq{t?4Lz|m49zA-ZtIJe6wtkF-_QHI_iJMu( zg48Uk1dta`obs^D=@x}g#=(KRnEj+Az8_SkP#eS1LZT4^s@!_05P!@Wju5_Ifl)*H zl$gu1I`W#fXlAKVn1XcpegFbI*_PZ-50{daxlLjG%QUQ?9$}tczI+*0{_*35t+H+l zGpn+9b^D{%WaaU~ZH68z7kS>OB)6KHL!wkKh+(D_D{n`)~! z_~N~{LdmL&TP#o_{8z6QOimphZPdhsD{#Jzi)*rXuF|*Jp6^i2(GX5kYqy`ObmYQq zbaHk+v;~B0h8n(<;WgX$QHkwkP>1vmWj_zTpEva4?rQPqhq;<-E1xn7E9&+!*7Chr08<_;;&7jXa5Ox6PXHXG?`=$s zndv<;EUgebII6b}cg3K0hd$hiJUAO-GnDe!)9l^;AHKmn-dl8|7?QjDJM zU2v*G=nrzV5gq_w`zO|6u&(|5`SWbe22|mA09`}XdGp2RJz=R!@h9L__0cUg3Jwd zzBl(zTP73A51gky-cJc>X;JXnA9;4{NEdkyLG-mRcMd#v zP(EaB4F9m0nCWTbnDxem^vXs3D?mwLRFMAH+6<~`=mia1wimh{8W^nalxb>f&wWg> z3mCC!qc`%J5#D`)sl%GW4IMXB*S)%5HF;lrVt%XUy(S+*XKbeG(=fL7YaWw6O4JUL{;o;$I?aop&WzdAlVY=-z5YrRl=~TO1cDcza zvySh8<)&bh94^XSlieB&`B-bHw*HI(1sxgp?%lgO4L(v01(&fOg)=iVVGCsbO7$`y z)wJav=_*_!aZwUVmIEz@rcgdvtnTII zRd<8(fz%!i`331H0Nb4W{G5B#mmbpYii1g z%+4=g_{N=krO-7GCMUB_x3Oi8e@|^^7JCjy4Gj$^*Q|p>LbjbHo&jS(l#cOAM?|Wq zBWFzMwgB`=a!D<<@$3{U1Aw(@?g%Xst3jrQ(iZoOaci* zCbaL#s?qBDm{x6B=H;S_63mO0-@(3h_p8KD|HJsOpt~Cr%+RMA54PqIA*F%($-C{E zR)#>utlUKP-^14XZBtl-dj`Vj_Z6YPkdcW%Y&d~i!>0gvkGvdh&_%foNkFabG6ghw~hK>>%XMExim*L&YW&T}om za|x$;!VBgI?buUE^E#Lb<-L5lsl=@PAiNeOxftNI4x|Rork7k)h1gLk1cq209P zfdApl`Y8<6IwE4?08PHVCl!&N6o;Oe)z@7MFm#Ng21ri#JiJR68xH&Fd@;-@WXF+x zEU_BkJ6^Zdzldeb4nWHf*LSCcXmux#8XRC~C?#@c3|S@Q?Mt3#7gIKQ_?H zqjg^V*;Hsyvw66b;mNvnu-pGY>Qt<)wN>=UWAe1eVXSg$sI5>N>!!(1C(lb`3Q~(9 zb$GhZKg;awY+0W8+q^Vl!}#PCMHSBi42!VOF-?I4Fi-xvMax&|lZQ5=6T24TerY{? zI5V_0>23{!&E9M(udr~@$o|nrv<$NTQ06R>?v$SUYfYds1RzZcPE9Ld{;B1ytA`V_ z*Z1GmZDGBKG*~%N^L7?y@tmuCf`Uu9jA~DwFuuAVGnr5DfIY0$G&?6}2Be#Otd#xO zJJa3eKB!G0rs(LmX9$W0(k^B@8kBa+Z8j@L8VBX``m*@t^8J^U=>gSs3=L7;n$iKXXk zOZWj)mgAUhg$clFWdEgb1_x^&)WgBI>a@1beQO9{Mz&~ZXf?TfY&}WFSGwG0B%oLN zD1TCuQEh#N=V}!jibcZV{iIl70x3+aKda%brcq3y#8p*QNfM5xfqN|dzkf?oty@)O zip41hA&?u8@E%SXAPpRcGeh)7`g}q{0)C#tpSKAKc%S;ikB_}#P)&L@#|s5ydnpky9TMWhd=13h-)EA5;L zv%8`9Q!+D0#&Icmtce541o|0sgq$ZX8JQ`wh8j#g^F)o?(h{{JP>jQLbKiX;3W|2o zA^kwmivoJ{uLugZ!)3H!=?=3*$JWWTsVt$=K%Ck>n0&>0YZLem?j~l^vlKcb=)|*q zN*5NEo-jr$@&jrh4#olAYrVYSx$r>mxXwNmu<115?#iWfPj(vO)pOhhFEhOAluicz z3=LA98d_r}>ww_}wudsOsf8jUXOwWv%x%~_M0{yD-X;M7w%^0~{c#__Vo-~>VA;2g z&Y&+01CC|$-tD84k~IR>fH1nl?FF{v53nT{d=5Cye4f;M-GDI{?l$F}IQ0x*6cn*T zowM}ed_2fzACyeis4uBaBMi4CoLUN}@uOF4rc0C1XPEnDyB<>i=>UApVku-7FJ26biLsBLrr5-Ydd^{v z3h(HqD*h%0xse%8A_)fuPSPU2#2-7}Omg77+;?G5dP^LnYIvq)XGCXV)beKQOdcs2YTFyyQi`yT9UX;n8z((hug0tcG9yKKg5;CpRgjv>;tEZ$1Yvm4ImJLzLKd~iuuk&Y z8Kc=6csJ%K9UUD8gk;wFLc2{HIx^CGRMWVEDO&swQvMr^`!LMELgy_pX$~m?#!bh@)&tg*Hl{Xug4uW2Mrt1s^+~?u>kFbso%Q=LP4$s!3WM&g z?O1tq&Zkd1GRsg2Z`0E^O3g!{m_MndnIi1pqYi3+7*wNSD6s=?XbDdMT#KZ1AB!0+ z4Xp0*OG%}@dHc3}bSpI?g18(cTIss9qs)vO&L5kOeh*6-M+xT*bb`Co>57@`hQpWC zweY3l!Q;oY_Z~bb(pKaU6pTSWe!=+f?-iFd7%^+}9r4F6`}_MxKs!A2CTEk>5j3bn z6cuvTn=SC=kHoj2j1mCz)35Ue(`*E;Y#78dNfpKUg#}@hP5;OH(nawgQ-B=R3?Ip0 z76l`yWOvu4CB*D&~FPN28vfBpJm1x#)Pj;&PTM1p5OjcZLBfTvgM6E#Dto}VxGx@|mp zg2g=a@sWm&#JWF#((<&Hw>_=JypwO#q2}R_(|Q3w#tg*4&%g{Tl5XY#iJfc)p%gb- zu|L~HOKz07PU)_7)#5vA#2L#stos*X-^^@Z>kkqM6!Qb-P_PrJjKJom?!!S5LUm^0S#cUNL#)rH%iegFvkML z&clO`i%L_Kzy#L+d5_a={-23eH|NWjil`;tsBpO;;4sP!3?k^G4 z;P_`hWib0(Sf~gLwDGO(>M}3N#vjxapZhxS!yx@904U;;l7=U{pVQNz%4L<62~k*P zUT|pA^yHC`@?GBZ;J$cqt9Pp>45yK9I>cLEUj8zQ8=?b+LTNAmX)UoF@E|#Yl@{Lr zzDu}b{=fftPHyZc+&1kXG3{~_yv=M{=#OEovuaYl@QNRAB5@i~Uq@`fh6?F0x59jk zMXB@BghfUMYVv_!i{usV%b|_^;GTdS$#YY2NK3P6?8$YotI6Ir0mnLH0j@a`XeX?1AJn`Waswa7gT z_~FR@wn8`vP;0*n$dbjr%|yliao(K1t(qat3Im)0rY30FQZX2N@asWzXa;%G59TpD z=r?dA5o!4jVVgSIfAx6b1w&4r}gtuot6K0jph~x>VniCXYVUTudXlOQ% zQY9R5N=iz=d$|KzBw{por-&0Q+fm9XPcLY{bGTkaeC{#NFiYXS-7A8`$Qg5gI;Oy~ zj`mR&0hZpO52L0OvR%se)ESe+79Gk@1j}{ieN!_4@FM0uDE#iL1r-k4^LNJq2sl*f zy8{J9qX4TRHa%jHAp;zYi`!r#s%1#83$MM4i}QyrX4)D-Te)67<^YR;KupD~xT#MY z>Q~)1AQwP@__1IZgYXxDAY15OC_kT*e>1?Qt12RMCod8p`uq3_8Hlq`T+pka|9 zmBmq@&~C!>kMp!LVIQP>0qfYCAa?LfFg*%Y=dt%4CfO#qt=EU~+ZYD(p9BK>M>S5J z?u#QDm)fUzqksZe!C8>|LZRE40!E}kQOOlb4A2pz3dnNf(P#*Nxk|3dVDnjM*r8q_ zCI$bJ9G_hSx`r>l2HW%e#fSXSh$Qv1)%3qsudeos*I{Gv=*ZC26qg>Px0DSTu9nyy zA8bLOK=$Fo^9}cNHN_Z?(T&i8gkf03*aB*_{6+=>J;f=C{pL+3K)w(W@Vh08P(tKa zfOWHriP6cN>{5fL$|NPu5#)0HX6Y?ujVswn$#gLzfwRJ2^dz`B(Qvg>JzLN)4;hK26ikkmj}M8ZL{BaDcG3f$rV4LatzzP& z3a_<$7KL`e@)v@i55+BwSj2$f5YG{A;Q8)2^s>I^-5U)BR#ius91R}DiqFR8)=|6z zdYR&5=Nb8}8}^e0&ejD#UvGXpyPc=>T6pn%?OScV%-8prBm%zWT;V~vNU;3q?he*1 zP*hL|GHTZ;(4wKE9)o%fde zaA8$1_Jb8kiP=BiiCV}b92F^&7&W_zE_*pBu^m~1jF46XsvP73|M(c z%4BmokmBE3^3DR-MvaKdLB=eGLV@)f3|y(A)mBwS%%Rm8mz#+5Z3Zy>s_cKznqh2x94NngKIFL0J7<-tabKr_wu1>!e70 z2ILbK#BvP?3=}qQM5(4qoClI>8s95wH!gwDYMn|4js%s97QN}w04&QUiya=FAd;&x zw;c2luvLofCT@b5n0IH1J1BO4+M)UY^`Kz$c#MH+{ zv~yVL+Mc&SNjQF&n@8{HTxrWAxC`K+_dxpGV*CuN?!MVX0BH@QMmy{&K0m0P@Ihd$ z5u-p@O#+euLr~9UvS+riW<$=zgaf_=4Luq$Ou@50I|VJz0brm<`^zhTkB7}-GQWHw z1|nAJvO=Yyp&=RadX;T%eH>C#N|4LJ3Wg(^R_<4`?L()iNVU574<4Sr(8luKI}2ZCb}fE z8KqCo#ub=Dm`7ySm3NuBGHZDgJq>z+5KxMkYI!*Hw_m&v70|Do-b)H5p_k*Qn*#%_ z6%6iT&>m|6sT>?lolSn&apl4BM}ZM;=(!5VfRdHfz`jP6M_yGms=b`v&>aoEqN%A# z0!|6i7ZHhFI%dn&u5j(%#ONcH94b%?P?S_uIAyvM#(IPt(O3Sw!@a55&LD4*jQ&LO zV(;|aSDno*$*U1B=xlmk2^#krqOv<3tRaz;DQJ+YJMpJDkuA}^V)<)_# z9&X(58ex*px}96kgCZq+&Cb`7)&g_Cy>BL7mXD9`*QW;;Vr=yv#42WOd8mR;eF}-U z**GP(rgx&&>QA18BO(~MvPzLX)@8aTWrjXGfA?6IVw9C=VIx32k}DdL=ch9RFoxKg zV>M5LCpH$0 zdozQBq*0_w78zGfu>9|y@Rz#vc&aA|T49$^CaoLsw~AzK`daR5K9rV`^!}|p58Zbg z=S-bvw`+Ab_9WVd7tCm>gz(K9Wzoh2zh^vAt)?YPhv!jVl#A8^BQSFO2`+e1j#bzz zsi~27c6L&NLk04B^NNeuQEgG}HnAoj?O9RolajPPWT*gqqoJpl&l^CTem~Vgp9NAv zj(Wy?av^+)RDR=~o-bB=?m3DCJ7>_tzwy)<$w%IAO%pL>4Vp3d&Q4Pq*e%nO;F`qb zS>KrzVmfcQiU8{*Sb(rrms#fy+Qc6SUBkI0vT2@$uKiR5ySDzgAq18%CXp z?;?ijXbn-23t?g>*|0|;4V~u^>56EJdENL&m8=4PsgxKJ^J+yt;SbglXGQj2yr^l- zOma2t)owQ!|6fHn@&`5^HZ7m04!G-W%AQD^DKfTov_d7VS0?2!q}5S3q)b*oR6A;R z)xeHW`!e;*-2~T27YbZ@&1B;j?!FhCotfnWxG9Ox#ooI^SeV?eGZ`fse0Oyfj!_U1 zb+H@95JWehF{H5qv)l212fi81)I%x(kni?F9J{)@4l#$Glhx+e80F;UrB2Vwg*C9K z(Z8D4%G9*KW0;d$m+~m4!>1}SmrwR~ToGH5p)iNK^2Ccpfds9J(Y=U0x+GhHA1!j+ ze@L|zgMSDW7_oeRLp7X6nt1)b-o%HpVHSZTtHu4pzi852qIaWNpERuZ4KsvPSJeJG z2(wpwKRP;aGWI-tai?FhkvylFz>kDpKmkDCVsAza$i@Ff5dKRkts0%pVsALk;^C7r z_<>r6`Y%HR^5zVWY44j<)YK>c&4`bw#9V7?ZWyh{ejdYKjucCx z(~EH ze;xoI-s%>gng*=3fPKhIg8;LP^EXYt<00`AAY1OsnW3AIpP5bf+-QPW!c_JSm7KD5 zwYo>ur(8Z1`mJD;u#L1qfRP$)^USW)*%wzohA@t4t2|r*{IEMXymj2yT_QE*E+#fE zI?U)hc6p+&x?UpwqAI#n*no3Kp?llvjp7yk0*SRXLFs$t{tJDTH~bXyN}Dna*f*~v zxLX>TCe?_SeSf}lGc7X{Rs7x9cEH5vw>n61S<&PqkS^Hm|M{ zCg9)u^P@%m3O9T-Z{L$&7d1M3V}ut)E6Jb*D{}_5Zpa1qMJ&g*4JBOi?}w&E#F3qI ztt&56q(($lJdO8z+<2$f-S5T2X%esX!tY;-h%FHQFgn}le~;GCQ@nDr!7ffkSpla~ zXRLem%S7q3=f)TD?PLUaY}ZY!>SAW5MyZ-%CQs z$#mN_zZ;qBLZmidZy38>Bg9M8=FW}0f_{{}r!O~P?)-hml#{t$5x9$`6FH}6fN3>r}VLZJz}v8dZr*!Nc|%%O^* z!ASM<5y!-6^Pf|E$-wvl)cAtlyOhj4(GhjaZ}Pk-4Ne+qY-Ik*UjH|F3%)7b&(ABh zi=^HL^$+mP@^AOuV=Z!Rco5-27xUrQc!@r~gRMTso$;LC`YRk+r&eU}BK|{+?a0Uo z5-7xRs(byKDqpvZk9~>9w%ycin_@KA+f1m$?K%{cgg)uBh+T<_h_K!YlxOzR$fT5BjuIUZuH4-7}Nb`_|<(iLbLN=W@R+Tz>44>E&i4I(TqUBeT%s<`IktU zIJbHnzs$uc*HYQ#=ytyI6U~i>0&%U_W6$bc#oc$=`5&bmkREJo()Gp8G|7Ve8XR zuF)D|mG%n7G&uf8dnvYRKXU2=TL)Xt=`>vvZZXv2x;&V?wJ^!DeASgyMWcDfX{&6{ z%DI~1RN@g%iE8QVrMa2G{lsjh~?~piCT3@WNPz7#!Sj@lx!)S-#Gdb zmf@?b{cq&j@l-9EL3gJq{M%Jx)Lp3*ar-uq93XED#s(6XL2b+o4&-UiAwUPw3qV;V zWfmg^urL1g>(@=NoGBngpLFdhF(B!6#~z4(c>%nU@Z9G|k^>N?$+DlS_rW+ra0S7C z#kvK@#cR-=4$VOCM1tI0f`Sx*_+;NF+@{FlmbWiBLF^JDucp8oAZSww^w@FY#n4NA zqpZGZkSr9yDn&*L2w>%dS1+!A{$^n?mZaWGbeh}OB=PujAasoIN$hK_7ghRE6j866 zS1GQN-y@RGoy3W53i){rmzxut?N+7v-9FllGu*SSU{)ZmO-VCRb#H)RW-V0 zhcD`(QLn8O@Vh8kIh%8bDU}uExI?y-g7O4LuF_PPa04TN~miu4)8bax@X=%|w zp%@xY_L=Df4WmHHLQ*D3&b=pH3Q5_^bH+`VkJ&XNj~pPb8w$)tVQ|WVLPBPd?*n=i zcHcC%nXF}my#1#21$dwWWLP9#yD{0^S^XLKEfgqzfltKw2k_h$y?cW6SAloxs_JUWd z==>B%UP?mHW@Ht^(N(lO4Y;xeBjoh3`Tj#4TPn#6mf=<`9R=UFysl>4NnxV>j=lC} zo{I3Cf5*4IHfO?NPkYitbbf4gsajxQi;xZrOsBBNFY#@HbwzsUwV}P5KEAE4%xo`{ zf##<_svER-3c{%)ZTi70Z0xIb?jttF_WG5|&gacdYs9FH--2X&YjmqWfAEP6;#ImP zRG6T2D%72FCj%(TpUtM|`cH)w&MdPs2TZ9YzONmPXs&u(dDJCOmX7VSkKy7|2$3jb znIR^c*Ek=*&H2OnbT6Ew^_${G)~!hF_R-9o!IOjDa@C@{yl`>EWfm-5L$fLJ>3L=^ zVl-wuRz2tb`3SSg?DPlUWcl%>5fFf@K5zRF!Omv;h=!zi)`R;oHv=Ql@2su>%kXH! z%ksQlz%wuk0Xk2)34M})cYm!Bit zJj3_2O373af_OG!%vzBA0#b>Cnw^^~frK)=1C*%=yaOlzVXYe#$Dlt&UVij(8X}>g zDmmXlzav2*kri$#BDR37^K0Cp~8s54wzr^+OO80A)LIo&>!^b?NZXt)F zUTu4$ckqtVE2l(w7)F@5_@c!$lgGmebNdoKJA>rVe~5|rqFpr^ZT%@w)?`g1ECQfk zdekY53$cphF@20}G3&??OBgJj9n@S;W49Q zGYgs8(mhU~jxDXftuz^I)m84OE4Mlbg{5En}^|r6`AmlRC>cfEbthF+yVKRg&>WH4sWx~-)pC_?kmxx+A5i`;llPhoNSeax6)6xXawFcZ~YjZGaU2m+T^bF z*lAoGxA=`BMvcY7i>H=+?RQqwy|+9Xq%(14q0xgZVMWR!K?z;LPa{{s%S-ai8$!AS zzJ4|I0-T%y6sMK8dgV4V4U<*Qm*7E>RsvU)1E|8YklYK=$^+GH-}-_P$T=5|(XwEf z8bf63@#Em)Vj+k~3l@*9yHEQQG%`4!&A3V!m+3lgjNgEONJK-ug45y5H%ONgqlz4I zJg}SgI^7UVr<_u%h^AQt`A)~XXaKd+392chVhr6^tUDj64d>7 zXWA+1yp6+ulo6r;1=7BqSKGrVqQi>lF#u?0REXNJwUQS$yu#V?_7{xjwm2EA&o$$q zDT`ji@+wY;MXCUPO8>dg_@)gPe_>fZI!-{(a(p2g zJOR1_cg}*;NmVtuu0C8Boe37kPaAo4Zvo${dWlM4fIFX5O>3?rw@#?qGe}9Dhl*H8 z;z{)IFLqMQ2Sx0=$$6IO^G9F#D5<#HqH*VnrLstqpDGTg31lnq8kbjvZsrw`&uhO^ zSGQ~n{%w_@rMGnwhvVg&jp~>oj#^>!mw3bC_?Mmg^TMx`b)7Q7P>NWtz^Cq3x`IEM zU+V}Ss6~@2Y8I1TB5?`RKF6WS(U$z(D(Lb>!$29-G0P*+G**vVXDgK2W&+or=tx}ojdpIDhZ!9-wA9^&;VRECujMh zE}hqpggx5!HPO#*bV7J=@lAap9o9XSm_KYd_>J@|g=6*K`9xR*LZ;b;vpLbwZS;8y z+8PyJ1ln#^;6;f8-cxjoalnqgVF32gk~bel{)R)DGhk$~rF`e9&`7F!$HmG*?duA1 zXdjtJ0fN{?<#k9TiBMPB`nfwC=wazkgCHsp@XV@}fNS~n{Z&Yki?BTT?pUAAv=p(Y-j%};`@ZelX-ODG zyxC4JmCem3LA5IJy)Sa_;Gj1chiED8tL{A^p>!C+m3;DE{z)0_!^~@8K>_%_JwOd< zG|sDvUHTFwrVxs6a+r{=Bb{@pA*R1|^JK=Wl0nE*y|&jmZZQj0OxAIcGu3>$M?mZYbDu_4RlLc)eRT|a%od(@P@^SZ(wfoqC%;+Bs+fYylTzBT+8%P5yYi{RHM&Zdhh?OzgQ5T+DO4u1!+YKk?|6(Cy#^!gEf1s>2zN z{l`_f@VURdkBxAgYy4Md-H^&3(qp4^hWEG*b4c~+^_)i4`H*+}htw!K&E$tGX6NV% zKc$8E;(jty;>zw$yZM6nf#en*J{c2|sf09$2|Rdm_2!ao#YBja&*3?EJgynsR^%B{ zu+iaZ3USK}hzD`NRzLtjDMQ*@va|8}JaqO}#8-q3j$)Hyg6AU<3-ZN~LHmE|V+(N6 zP|y?SMy-ol;R)V@8Tk7MvmR$4YyM~)}+jtzb% zJL}Bhls@>PN8D!9ppSP`+37|j(Ie%D`K7YfUpZi@1Nhv2WojuOu;ocRW=go{QZeRu z>_(7nRa+^nKfYMIH-Dj0)4zA$d`?~MqLFW*upIipIy?vm8uc<&u7Xn~&fOVeIQPaj zR@qbjqKVv^HSFI&b8CI~(!uiXUqxzp;1D1rM@8n~A151xGvl|Icy&8C+a6sL{gErg zakb+NbtU_w4!p*%t2I`8WyA8`{@2dCm|^uWJRHJc9G7VIZK-r3s~ZY(*zp>^tnSt7 z?*jDlFGM`7ssA|n2xQ5$I}H`?_Td^n+;I-GncGXgMNNzf4+W+FJVY&x>M~f{MxQVKJay+}zxoMkIJR@K_^$d(4F;>*Hv6MD<#7{@o*Z zsvSv}*SN0By?l8i!%w5)KJ?K8c>aNs%Bjkx5dv#b@I*5bwS|WQ7_ONUzJC4s028Ue z3EBB@8SIs!S{&emkQAtxwtKz!bvSJ}G3U0;=kaGn8fFJGQ;L5Z(HoQb{lOjy%lySR zQ>Aeg1<=`L9v8pUYGfpr7X)7zeG_(&`K=mlyiPhjiq=i~&58ma!P$B-b-+-!z&eQP z6S0fX$hhc=MqR?{rsx@_cTJ`CjZc%=E5lfYu-kX7NbeIh$Ic721mWN2cu`>>Kzp0x ze3@>^-01f=8v(z7JoBXB66Z2p+9`t$rFBt0wX@;cZD5Wxn#l(j(W^bt-)T`v@fb*Y(%%P-T z?1bkwer|>gQYtN$24X9F@VvS)So(YAZtzze3?1ho1)u%#qleAv zM2)xycEbR3fIO@Se?)-Hu%^TtJWj`EGVwpw+O~+LwsZuK^_y*sS4sC?r6d%Bhst7X zztK4yK{`P`yeDGY>PofJ73TG(osfH|@GUNs=4Ed6E90$xJ6F2dF6voXubW&hlMAR- z`P22y_Wt;LiW!&|Fs>Z-(ygwilelu!h6hf>-vBg9zoSXm1p2< zCPC-sxQJkew^Xkt=qJwQKl=X0%RYC~w0(nwiGiOyEI5D%YZu(v`uX~(W3@6t+qm=1 z6kR#qi~1|%s4G#1+S(nwRjG$#G#Vw84>_(S{4F4S8}40r;pdhzp74m|;)*V-n$PDH zoW{n?GCv{?)`&^dr9?I7YCp*f)XU7KUvH?}I?A%6J{)_+I@alq|I#%mqn6cO&78l| zKS+-aEU|pjtdC;groDaHnc%nUrNHi)S!`|!`sd8G;1@i%oUW*P{d!p8_Q^AW>RJh< zVqU+s;^o9j<8L>McUQS851YM*<8wh6YP98wFFEO0-7LCs68ARSE^#`B`iTgszFqMw zXuy8AMsjjx?CtK#(&Lg_Xv5Rk0esXxG6pzlBjjL|6V+v89}(J-VX)tb9)6es_Zp(S6Lz2c*sw?Ndjs6u3i&s1|Ql7H;z4aUD4+zo1z1 zMf3WeI`brDRA@X$-uUthi98Pd2al8F{$juCTt2Uo`eO)eq`hjM{K7X>vQF0(S$YcO zY@SnsF6~gQQ>UtDRGuLy|EA-W@C26^`N_c3Tv0rJI-7-V`hU=s9H_wN%yAX&;424g>}?F4yIM95QiL5Dyv^?)NvNA647Iq9r6UWWG`}4!1;0BBC zl6NB2#+2uKv63Hk+$OKu0B2??`R`JTCJ%(0Y~zb8d9R#jT}zM2-Ny_Q=FkK`Ui5(I zK|kBwI$!i1G&@Ij^JgKQL$+*dPX!YtMMh8op5HI`c(KZ)@ex~pYA+w~)KmeGok=lA z(eEI`lJwip?k#aYX2^GUTfO7uEkyB3cO+lVzvk2W(4*F*QE~kEqc-<6d#$J6GJh{` z+#Sn!jE+-p#8zI<-lr6rHv9qxXCnWMhq0;`#rq|$+v<<@70im8%$*55=vDHzwhHeJ zyVn1F_Py;&L%LE%C1tkaIWA3sropDCC?T-anCnz zNAKY{H5nBR8e0s{Cak^W3VduTq=txs{;4GfNSp z>nc;OLOvhimemd7FFygbm@0ogqX^WfN4fNS2!m^itW(xECaDinOJBFH_+1x9eH%_Y zuz4VMTEj&$AnJ_yP4yT!(2t^P&5I71zn?d6L^7?_e{Px*PrVHkRds_pkfXyyNSF2V zwGqd1olyPgaHD_L*j6Wmyk6G#PZw@7j2HCNMH}BQexDHW5X~&JMxwugP6)#TZb<+# zjyV;FIVVRanU*Hw`j5Qp9Hl=SiyrAEYH|lD6DF;143&zP;&_S(UUE}7*R}ck{)upz zy=tko2fnUyY>?pFtLKR%JDaX6^(Gn9Sl$1nIVMzVEm18NYqAkD+O;hD>>!bvo(V5^ z*r1{aNk{!+KXoh8%lLpi`JgV8UH&U2_b)c>ma>_-3(S*9m3Jqb}TP3){HCD2+N=P7WcVzLV*7x*UbuZy0Ydap7P5 zazgw(T8n^Gbm#0tUH;ivtXDyU>*e{Nf8}b~B*k_{WarG)5PG+Pj>G0c!A-IWr#w9lpcBZub#i3d~ra$RFwMxj+*TSJAJXq+aYgx2T8Bo!{#`Ys1ZpnU>4VY_jJ0yii$h#E&qL$&$?2 zyP!M-9rrFK#@_+mJ+yTrNRz)MS?>SP_0~~UwO_RGrWA|(jl+P=R#?ik+~_x(#>Iqb9dexCKLHP>8oGAS%j z9pCe$Dp;kRT(+}yEdIzkum8GlGN^B(ni)s zeFXWA#7r*PyC?)0awq|~^_I79Ml<%^8N`&Yt?=7SE&L#6#r3t zYV`bK!DjgPheXWsdGJl6mn~lY%nu`cHJkYcU(UM7YWz?rBjt*+LonrKV9bPj*IH$2 z2Gwn+L3pk()F;dDB)8VOIeRqz*=b9MbE@*OfcfulGj3_AT~R-7oZSg9t+`C7sMB;X zBa%BAZhnK#8h&40+mEM~YEHv>-nmz+spX){CUuRC78-qId(+Q0Y02IX6NN@vDvdh5 z+>cNxYx8U!ay_3!6*BLHN7Zb!v{@#{iph?bkm6)#Tzg5ReW_Gf`*h6EwQ5qK!L?3tV9~P9=NF>AZt@NrrgLN3`E6c_r4qkfqLkE`5 zd=%XU8UX#^l##2i}(!`k3sdVyS%> z`%g(6Z>xw%ne<|mhSI2Ruh{03{(h~^a5~eq=p@fYSN5ewlaDf^=>Z-^)7jbQ6$&x} zCY`WwSqm^iXK`QTMjGWW`nTE7z-EJnjkc(8s{!I!nFoo*)3yip`l2k;W;>|>oO?JbEkwU$H?p#Ozf-vGLjjT6h0@Lz_6(Kk!Y9y?!YzGkp5I`~ zd*CAHn=^qi@RN-G{W%kvXzYDiCx|vDNB5$B<+hi&XXQ`LW{aIh2)12p8)AMz7a2tV z<0^6e+sg`2UK~3*W1AfulHQ!8E0UDkyT3zoVht5!$GC?X7?Ctqta6)_sG&LL&W+) z#C}uBz2OaJIR`VX*pY!XBjJNZ*W`v9cRRKwMsm+@=41rD^Wy-mpGUXMoGlGOT6`$!eH(m$t=K#Y@z4M+9xtyFYs8 z;wHZfj3+PCQa`oxR|n6$2vVu#XO#A(_XO4AEl zM~PH^;o^?cA2NI&hikI~I{@H7uLD(f;*zm&R?*PNUc|xSjLbI6UzIYfSk+ZNJORI7BBvXl-vf$+}<-}b&@3@ui z!zTLXx;$cPq`5i>2dPgAuIVYN)VUn;-6pVqW!etGxBBI8lum4w#%i(3824(G&~?2jUWjJw zYlUH4wywuVJR(wJgs2kRNwFG$bodtVl2>Uj^DRWO5C9ykaJPu&Tp*dU(dW^r9B2&d zLg!gS$D8+$L$SG8PwsuKb=lGhQ&PkG4o~1bgodO#u!LD@kU1|EQ3=f}v?Q@KS#mdm zi4ufWeqdRU*zPj*j?Ok@64xC^XtD?O+zlO`QF>BJCQiHYuA;-@5_8HJ2@uyyZ3{b7 z?}|XXak-oP?Uey*xpd-IFA_lKpK>UqaM};K?Ar}{F{Cdg1msd9_+MK3=qFlJwPZ%H z9LTIP=p=E1_)`ifJP{{79bAm=hG3h<4uR=_KaZV`s>JDr`r57Pzc(X*Vo%>^@y+b&UW9 zQ}^I3;8WOG0-_=Vs~^u!xrOVpe`pE<%ss?oyY9?BvVH%=Jib4qkbK_C{1yK7of2ju z{;9BF>wokaG7up3sKEFlYk*3A3+ZiGT#CYl9mZS#+3 z>|Ym)L!(wmeWLlxh3XKooCy`TFj9p8@8JmB$Vod2_ey>9W~?!m`|4Y3(H{<9P-DEA zzTKK^5)|en6)Gka4Miz4fI&kRUhzZ~yI_-L$;1221x|(VN6#pgjYyz>IPWbSciwPE z4``*jd;ueOLq{I%uXUF`;lpX4`4mT18iIkrn|02b9)dE$6|6_pP&EuR4x5gOn$ZT4 z(BVYb(yA0Nakzxjz<`8oWmVo-(|$?(GB5YY9awgQf7)js6*G&Uqkg_<8~a|c>8>j@ zs(usp42f_`)sS5k#Vc>Q4R|Nu{_DBQ)-baP^qq9*fbOAv2Dy)43yr9H;Azb;+K<=sznoEdlF;lRp(nqaebAIJlF%gTgmqO9HU=bWYg+EpDP>|36R0m-%B=VJR{#*7M%A& z$mj?dWk#OvUY~Titkqgu_sQr^Kcjv3mZMY5H#_OiSMF;FF65gY{Pd&@!k!M;o-F>E zX6JO&0hG8@Ts5WTlvLa8E|L?St`_>&ZcoU@?#g- z?g9;l|C^?&_jH!M_NMuGrB%}!46-uH`Y{3;L@#Ki6nIY$G(7_%&+>cyodRta1c4R_ z2u0Y{Zr+66JN#7s-~$CCRmbAyN3QbR6*c(w@CK~X8fyKr`a=XVOUz`-o7(piytgiKkXYuFv<5WQ_SnV*1q@YaQJrDZr_S# z0*+i{^W@RREvku2s~kQZne1Iv9P5{%24v6AR4iA&Y*jQlQPW#_qM~Y(UHv&^ zqE?fxy7W6%s<-rH62~(ed<>A*!h$g07s-|EMu~HO=^#~OR_)C{7@PN^T#$wrc2%?C ztKOw|9L-#bg0VGMsBx+X7YvLmk5bD`3Wgt)IWsggc{L`ha!*GF;{f$IDxQj@BMHXt2&x;&i-$wneosoSwv{|IQl6KJRXF>JzZWzf*#qyvkj$;Da!-8B z#7N)2BbZ0oQgYzl!dzv%j>dKZh25m|J)-7E|21EwX zBRR`w(vT`2cuumJDt~bB+%nmU zlNf+r_4n2K);blE-V9rlIP@kwgD*bu5&iU$ICiYP@j=nbD!sidjL?JAC|`ekd7FWO z;ajx_KfIBpVrdxbg3+{vz%L-KiRx{@%#9Q}u2Hz;wGeNx1@|dDrxzoaBRqy}B-*fG z1!=beA8qO3*vrzT(}FS%ymyrperQMlOE`O;YWXY5X%zDg7v9)?^XLZPhS5)+ zeivCC#+D18niWCv1carrGL-H<$Kbqi^B=3SU`bf56%KBP*~G*f2JBQH}!i7}!LG35!3bVs5_W-xWNK zrYuTStN}oqwZ!o!~a+yxy5_RK)#|rn$E=aU62^+56sQXHa(5$ZT z-yR*pjq$y6?$~Zn{4LMk+P$;H$o1|&6^D8@Yn{ItU0y{5zm~j)MRGke73e$3L@7ij zgNk;0w{VlFsgwZ!b+chQDX)W`DQK8HZ7+jiUqlW@r_W1`IF!$U;BgaZt4Rs@`hqqa zFe7#jeL-_5G3r(JPi{y#=y87Ac-U7hezn`l(za_0_qoDS1l7~cw#5X;W#H3)@3z5bT`^?pnT5z&j1u3z^qSGE9UX6@Ld2GR{a{5nm|#Hp_P z=`P1wNWbx#=fddD!Q##R%?i2ccb~6id2_V6MK^5m&14H0ZO`>9tW{;pr;P+b4^%Ks zh;)K&Zms2CmI?WhjUmB3ofYK1}N?rV$3NY zUYYoK2IH;9Q_8YhFWLh2=2Ear-I5kNRq9O>?i9gX!EdnRQkCwjWcEJ?$bci12U{q> z?Ea@_D-U^I8rG)vs@KpeskNHaD9=&s$O!Sj;P5RM=beCwEj39SK*oqCw4HFO7!8;LRCxXHV+Po8evUKNf(lmBr zGVot%R*ymL_8;4RxqI)6E8<%t8+gwOkar3qykwi#Zz){vz);#!_nT0dU0@mfa1+(_ z4ZHo}#teuQwZmv+&!+246W-SpSr$-CXwSa&{$M@DcaMQf^EGB@Xvk~H6ajBjU#bi^cJvd6;>-Je{4a(M z<}`_f@z39&T@gsPTOEBi|H=P?Vg?!cI=QBaN#CN3Zc%Rq>*Kjg54)Y4qPCz z_vsqP-nLXI?wO@TT!>g72Z|#dm&K;LW%;HPZnq+sf>`w$ArA!R7`DDYSIw-ZhoeNH zvJw9xPD|5bLP8}ld8uCNRcq`Di{kPE1ex#u$XGO*Vj#fnp#BvIF@t83S@ph? z2D$5Y=!~MgRlgL_pqPO9M;{kL#E_Q`mw;dnW zUU+ARZT|7+Uk%dRa$Iz5`m`+sn1`iV?Qox^I1NzH9p4{UK6d#?A629)SW-d zh3=P`w`|^5Kis+T^L*g-i~C!K?+OI_(>4(8InIi;yb7c?V-Y7vllPJPh#1@ain}r{ zCdhM6oS^7Q?(LyA+CH+~t9Pul)6W5qLCvn{5G={S!J!%jIen%C&x;E*@B@I!z@$*KN9c~TlsQR5^0c$! z={4RrF%baJYB@w!d+4_Nn|hE<_k{7(H~)3e4!Exn#t&2WqI&xF0fVhZy3d2G3q)`y z2AJhS2U}%@75_5!=w0Girpr;%ucU0>DFt9HYdi3`fm2>7xI;o|^BGWV%z}y7tzpRXKm+xbvirwN&9U+E?4V|4<;)oY&o)yB!#PKKdV_O9&*pVnF1V zDF=^vR|qp-nxBwvnc!4>{wPTs5aLh7RtF{JSXA@Rrsq2gPC_B)3EE1tc~O=t%Q2?9 zz4@mV8JDJT5D9Chm1Ud|I|0YXnA?_6!9(MRizB2|>U=`V>C*dS4dXGlPlUY%vUtA9 zNVWTPYivXijQ+S@<$o9jjh)%0xYpx+81;n8%7B;t)zIbIObB1M(u4qjpdef!kWG%& z&(qo2ygX`y3t}m6s7!e*OqZ_!VK7BF9mbSOj%=oZ4fQH!II_)GxpZDB`0Luhh z_4a2~S{*^J){xmpvCJ2LJq|PIG#;{Rr=J_GuW(`RZqV39a1sP zk|Tl{tEg}#vXC9Xr1DS2Rc+wK#ztI)K!COJendO>dn zsZIWY1co_8nfVoBl!8{huBUmwyss_Bdg~bwJ0KXg_PrE<_A1N_h5ahlHPrwVPzB}! z9B$>GH#FZdEc(+;=CZr4a9!ST%@J0RCNieyS57WYg>}lT1y?sxWDEtU35~agxtrWEL zN}+Ysxbf8m&^x*pHl%95R!_?;|JGlAPnNRT-In0(s%`3O?#M_Vn&5bDy7am(H_dd& zNwJgQfzLBY=OFNGOXpgu|KP#IjAR1IlVX+teQkY7>rU4gIM}i9IkJoRbFnMqxiUm_ zoW7qeAkb!`-H}&yy&Aw^Em9k*m4eejNr+27DUDs9%oj4X){wTQ9;No|k&9%PEtQ*2=PeeANI)(2&Wg3W@Ejm9cfj zQ&XaUb1po8sSEa^g4+WTo%erJ&KTbN)NDr0LGUSq$eI)m@fnu$y<2!mFugH5qb4l? zjmcb6Y2eJ8?OP=bm4oc4NFh z(fo0}P%U2XiRU@vo=Ss%;|LeC_L?$e`txO!&gWJ!A}ZYD^%+|C2VUUvD5x&UJ*HND zGwp>`{&6(+U@U2hO4z8P z$>RI^E{^Hnbdr!L1wH*DEf0NYSPDQE?IIgVx>tK_T_)K`e=v=L_W-ozcRsg`eBX(e zb%+$jKc#VynO+>^gjtSnE(J7mUP_|h_!4-Wc28k+)@p&}EV`Ny0ap3o(WNs=o8Pkd z>qlr{P6Yb-a_lrZ==I$M;84KKd7ZL9y?3n61PE`qB{8T(bmR+&Ttf0{doGdCQxK87K_ockuC+nS`R8d;blxoJj6O+{Ap51)$Fki$zdQopC z|2N4u-&;5hwL0w=;=HF%?5a!e^v`!7LnjwNnF8AKFEF{1$6tO@0o`TivL<~Jc!FP}zS zGk*QhsO57T z#ft(S(MDA#n~>T%9L*!Y=?LJ^c3^&iA-MQk&IK3G52S1O0E5AO`F(MoM0nJc82W>( z;tB!4h=Z1K5(VPI(2($>ZUXRoax7Q8)Oev=4I#=vf>m)NyAJo-EFRCDE%aW=JV>TE zZJFsTcB~xcmp(V*3vwosGLnR~tpNbb8H&r2nX<>{?+U?7G*RXzd5udWcATrP%1S%x zU!6Hbs z3R52nI_}8jOm;#%Or$9@`(9|z#2+G7vT(vzGk^SwAxZ?qunOjppXGaX4yo9@<+^yf z@F1#UJr1Xj{?YPTmWb0y>GaOTK6r8x=s6~LsE*9Q_=n&2pUZLGg|05rmH9_A^50FKh{An#tWJ%-l&+8Y=;Tr11_O~E&pk@e zYO3_=XOyE75Dg{K6VZ5fNQ_{yYF-L%vj`l4Q@ODD=WLuPjZp978&FsP_D`SZj+}I7 z+O4zqX|d4|gZxMoWaDtwbKPUBHX;4N*wvg1T$a+|fQ?(~d1gWbn|jyLz2tx{>Kp;1 z#@CXK>F%Acsw$Y}@>!%YT-DY4H+gB~xb{eqN?xN0H)~I-rPi;rRpJ zFI9a)bMiF@7eT4^?Bp?5vgF4HJ75#*Ykno=L5=@iPb6hg5y8 zq7*DvFhgQJl-%_bTbToJC-FM zJ%ZxivRLvwX=QTmM+`t`(e%FlnF^iVXt+aM<8kZ=@DM zdrqf<5r=vxdt=%axvKtgdpgP5Nzme?Pf1Fk&iJ1QS%+S_waj4$?K44`pPGzYvcrq1 zs+et+_?+K(=&j;MOR>3wtN65qd!$mMYppU{-Yk;{>Ej$o=7nYgTm1k^YDVNZYTil> z#6BR^pZL5&L8?!n;!f87MT{)f(j2~Ye%72cT;S&YvVU0}&6c$HGosjVV4T2&)bf?7 zNcM3?zH4tc9{bVCP$^do%kd5I7IM)binp8kE^y%@ePTT!ad;9mx|KK$F|2B#Bzcf5 zR_yzS-qOCOl0b-eQtgyI`uHV?dBrS3=29X719GaNaX z?o2c!Ebj1@)2$Y}$wzAiRN?DP3V;ki16kg>2yIutxFDg=5TC!KzP&s)mt7`70kF|h zWXOdm{e3V~8|W%{4U^!&36q{S?29Zl!` z?_vZkloFhLikt}ZH{=P~I9Ln9oHM;QDhbM`ym-*jY4CjkoP_{JFzp7!Q2|oarz_vj zOvk)3?IA-0W5I_nqe%@}NmK&A@L$D~Kz@1O37cy-e4F9;v9MPp(-}Wk(!$dX@)MxC zx20gh+cFi}UWFV6`SI-CX zvoMeBD0Ol$cSVB#;af<3`d5PF5G8yu`{hr?A_0fY4Llr0c7)cXa99-qNa!bihxGF# zQMfARtj%sa@H5A&pTOQPaAA@`Ov)XY1_lNMK*AK+sI-FaNgHaBl6-?8UVV63yzb8m z4`Hyv1PIgTdztC5h#jBLiuv>Q!xBjX(W4RxOV^4OP8laxgqG|#;_e1__=BmdeN6GN zgZJvzxVI9)+z(d*U;}KqKVpJ~(v#jSt9DgLsPFytGtu@SC5QR4&;)>^Ab6{(^lpQQ z&J2uMs(2nOgxb0OConT|nImshYpeK}#jI(E>#RrOR@LZBM+P zeXsYIMQ3~gC8}>-^8Fv0d+_~N&rcU@)t$vcz-v8_2cJeskjirygRTh~1O}%KeOb@4 zY;=HNgLFwU90b+v?u~gRoeC-hLkK$BVtAB3Kfku>?nQn6O<@UI_sUr}rvJk~5g zOYDlwCb(2=fwIxI`RYHpKasJJo+cm~*BWbSAu}*j$30*K+}o8%GIO5BjXzXR#8GqEWP&TzRHx#g{!17@{emN0M3jB05SrfC~G5|;A;WCO?z z9V$A%N>(VcR3nr~D#UQl=1+P~=LuPSB<1{jZC7ibd?FJ_(OZ!Kn4=ks{i*4GY(4kz z*sX>TiAjAm7YjMMhpIx{k}?$pm4LpP6cyBF4ehjn_$A`BkLwGA@Tjg+O7<;nZ4CIj zq=3Zz)-@2tst+EvZ3SRvPrv#{5E{|LKpOmuGEhOdFDE5UXFV4uDI@8@2bW&rUhsHq3hZz81r(XzN29V5va z`dHrHduq41#XoIEb%O(!kq>k~AU7d`2C-6UD^{>>5T&W4&8xiDjTRuQHh=tE`5z8f z$x0R&*F08v5B8C&FYF^YJ|;j?zzN;H&>3-E>e)3cz5ugVsK~I?Q`!GH`9LS6TZTWU z_or3SH&XX_rb?3c`a!4;Utuzju!l zHP_*$VX`9|Sp>TzkQ)Gv5VT32L?tr@eR|yc&x2Nm_olOgu_Z;Y8 zQR2I`EqRz?y?L22x*7|v4(aUsN(ZPOA-t4kuyzmtMNT=>SGccpxTp=-XsxX_=>g{j zG8N3@U?IEe<-!CBggS-`cyE%#n>;N{h{~9b21Q6(HVdrj zk9xTRAczb@90-C+KjxX&GlR%9tilF>IB_07q>?j109;6Yp&^jwAq=$?BcI207Y%65 zHPIv_#N6&uqW_*h*L}n@XzcW*{m3~>H5xb|BU56;Fv0Tgekf)WFnAcS{7?eKVl)~3B27SnSQ!bNM!$y?oC;e3%Sp?Y zNpk%R)E0-4LmU`R6YTY|cZ_UihXK83yj1!e5oAV;pBU22whdO_?iVC`C)Z+`c(>;AH0v=ivQHQrUi{}>tm^ZMUvY_OiYtRff>2XYIf2p9+Egv- zGN)4S_ZLAxjSZ%sI60_{aCX)27KjiOeg6LLR>&ETiVu7s#}NS2Lywl|P;Jm|>OKif ze}6w}k_LT678$9S1P&~H4|0q9xALye6+1@bIE@}wTgsUniH5;rdKiEy(7Gp-Smd&x zjvh>?mLM_>7B<&FaFLZ?1G{C>3C4r(A6=HX6>A+j7#upnh_d+sMDlc3N!fFtLRDSa zu~yrP4S9h%fZJjv_|@iWTQtiV1hz#h*uXeLS6${(kO@P@j5!RJt6el2E!(T9-*-Ge zF!SjJn)754KVWJAsX<0*FB-tfuhdI}LOnPNfN7^eDxVg1kOp$gJ$jJ^Ou&)~s1hckxUGeJyE9TDV#MTWGkFPV zV0y13ki7U8o>QedE-y&7ku3n(hzXHkBu6g|dVA={V!q^J+@9mcjQaP=rHw?j2#CK+ zoT{#UgG!{9Bw?gG(PjuLx(i_VaTz#fprVihZ@N)KL-gCWJjgf4{bTzW7)QB#O9*n} zJBYbK{To95Pe$xLU1$|GgHzFShO0IWk3{F-L}B5jBLOnw*5FN9d9Kyh!G7V6Tz=%! z!%U=im~KebZg9}!ERt!pluExJt5!o}WG?Y?+%a^e+ThNM!Q}0M@HyD977)f`zAOaP z@Dfp6C?}oJGsFG!*FF)l2UZwOTgsj%fk&OI-B9fUS>GycAeRBx=jeOW1zeDBAEa`v z?zevbo2sumUa5>;W7Tf>;vr~DJHe=3)Oj&-P$a(Qe^S%y+YSm*a6*a%pT0wMrN{lVzllijYf=(08-!Lp7j^|(-=>s8Bq zIi6S|nH<)~`s7$7bbVieN&5z4E^ojH@g6uUVU#n%ZDJ4ziSJB8B(s z69-ZOkE)Gy`u!8VgOji$-#<-xClscciXa54KzI=%Cn|LVU2P67F0V%{U~FdQy)FVa zhxic65KV)Jln+3-iRF9`;xu{;tm~1UE9~$|Y<~D8kWB<_zP|Pv=cFQn$;Tk*^5deP zih@r;fwV9Oa&l}!g74m`e5pk-7e;J4X7l57J|66{dqg>Qgpev#c-crR^goLO-B+}mb z$$$c&(8t7Q5dQe{PD@J!Y30`hcsWT~CIxAPw&VXMp(}ThaJl6JyjBW`r=Z5Igl4-Z zA|*Ejei{~p=*a<-k@xsFE3_v6w1&>^REH`$z zZ{Tvm8pSA1#bZ#Q1YD}PkYIb!^WY9a%_!qT4}25#?N$Zo30s1qKDfz1gkyxHEAYcRuZUAWNQO|S7f?_{jdW&CgM<6kDIO>0 zO;Bvbk6JIf2}&Jz3j)}ws{N(dt5a18_jau;Je_3YhIh-5QlN(gBA2O?25O@iZ_XG{ z{G0_P26`DE&-Y7rz-$Zh&u|#O2eV0FvU^E0`yV?qO1O2b3W6Rs>Tz5QM;5Pf87b^2 zQ;)QonwqIP$P_`?!=XoGO*pEIM~rCxnXFLJ#oIWQN(Wbv}2U4FWxc*4Yi&?YM8E`T&ix&4gz6OG?5ujT% z2ckjL6fi~qb z$XLBQIKf4x-`Q1J*%KC(RYkbF5T{Vs9V7 zOniLgOx@zE*SX-SGYu~YrB|U30A*Eyw$phrhZc}C{ZC&S9HZD`E8?(D{*2cDGa{Z1 zzgPq&wT1t;AROMv4G!nQ_Ql&hfoXTCqCbTH16!^RdjD_Bl5<+z+(oM`RDxW@mIeel zxC!AMo5uCt_C8_#ke-f>`1DNP2FeN8O2IY3)tjK9R(P`H;UMbz`rc!6ijZiVksKUi zP)Tkyk4>?^1Fo9j11xxAS8EmxQqo-YSv=vzS%f9C#GQyu)XYzo8|=Wj2NjbVk8ujs z2Z>^^SX&eu-bJDAOdxJUmi37Sa=zqW>a(>aKgG+AvQ$7F-!H) zcv*hyQYFZb$Hd16YrPQ#y#br6s5B-jJAmrfqMoD14wZPop!m;roGY$#?vL#877kb? z!*U=*P`kSlqbsL>VdtQ#YGB%=A35$LGBb)*hb@G;Id8Y!4kwgkb<1mKbUDW~-?$_t=!S+3H16(T~-uPz?cvJNbs1M~8DQCTf|E30Wd4lny!2Gzc@< z4IepWUNvRIO6_^n{z>GzrH7E_CQGE`^$#Wg1#xnXhLx#moV!otF)%M;?`XTW6!EDT|!T(y>U=&sNV z7`4EcTZZ9ikb$1{@J9Ayiq$ip-uO^$8yYC~j{9ljY{R@ve;7HL?dGCqD}6IM(zbs! zQCMgW=l^JLp^*0h zn}sVQH%n0{VLW@HaWrcO}^NT1d9O+t(T0&)wk!ql`djaPqCE=RG%=S^Gu_ zK59Y5|5Z$Li+?|Z#BoW=t%=HPXO+T4iFak?Gt1Itm zZ)Oz8=>s1J)=xtS=5)8ve+ITZ^QpRq#y0p=T>#yG_%5VFnQA=!Zz_=@>pjHJSKus! z;MaUiWzWzP=lam1E8+-Ma!YF~`q=G#9}XxPeI}D@XT+9)Y2I*bCWuKex%+5y5f&et z!Ao~FY)ax_FjH`d)}WS!oDynhgy}QE7EBF+q3+)~3QEmfU-W0SD2v1~02nG-TBfy& zzUdA@#bH5kt^t*j%hrg~Zy-Cpd@r56{FOs#>vOX9$<2JAL6y7Op~pGT%?9j-cpigU zfG~Exfn!fBF!VsE@I8cNH21-)B9}Vd{4l2sIyuYCnJpa!GwYL#aMk$;YN#?GJ8y-< z;#~G%98zt9on?Iwx!P8gWpl8<7klaDp$1$+Sh4-w_ys0>18kMaMlU3K!OpqB@Jym% z*qc!8Uj%3t#)w6R7~~lSK-Ca!4<0UgV#1md%=w+kSQGsrn0lG%jlb2-7E-!Q0+NYv z!B9gl_y6rCzfnkhDN|jG}{s1JoKu9d}(DHttdoV*1EwkQGgLkj=qGDtu`; z{n5wOOAfj@g^u{k7LP$A6ZEoQ zOM8ogo6U1r_mGfV&9;R9R~bFTYNM|wR=wW&$@g#c4m8MApOLrK&Q+Cqxc*xrW^y=k z2ztr?(#rvLIGg~-ilrco#XDZ_&jy;F-{cSf?u|1!uhk7u6z_`iVf1NR08*g>1wvU@sa7yhqaWn>~^Dj=*u*q{)nS0<@SQNZAV_inmLAxEpg#hwa1+v)FkJ1j+xSJ3 zKbvGl-{B(@qCyNfRC?QC5HmYL8VXr6|X=1T`u}f2uTqEP$gO`gKpRFxOoIyfN1{{4+0x) z`F#BgP(pxpY#RtA!>j3<7Z{taTiiLZGDUNg@6RlHLF2Jfn!(GN$@LAl!b6Jgz%HY>*#8-c{6{ zZHoWjgE4BrmTRNO#om`H_Fqszs`D~LKPf8SScLvcu zFX=^4{qcmRLJ>%Sqgss!+GP2*zDJk5Z);U7iG>KJ*{5vX8s87y!9sRIxd#5v#i9Ix z7J-1>2smFTq@n3;(UTn;FjHbd)gP7EPeab5CoBlIDP&gFu(tpXiDqA5=UCW|CfZQ@ zK`<$6cMqR;aZz;b@h-K9YJB8MfQfLY-&=qQ6eoddDr_vLoxT=#yMHnMdx;l-1z+eG z#a(bAO<$Lnm#^5UT1D?Eto6i0YH?}l0v}(G_4)nMLb-JS$mqc;4K2$-cYCI4wV)YH zO$lnvex&aJfgVhZqWulnbDQxDx}z_uPWS=PaD8I`Flk7&CHLWDdUWgL!v#GTzcQd| zRq$U07@>n_8b1BAHk*{*87H~RyPBjiofC;4OGDl4z_uH;?eRO9Avgy9Y8yCG1%i|& z12B6-2Y)`=dt&}%fi_$B@`<_5K>VG&Z@Pm=7ZZrb?Ke`sv=(hVU_&gJcR@m)kj?(% zFiry)dE=tsBp4f`Qm`PhiVoDEEMcfOqrq8-E14hu2Q4iv^LRxe_!QSNqbhoEa-({^ z6BW*=f3D2Qf%V#WIcgIF*N5W~I%e&s)jFXO-JoMI|6*_T?|6b<0EmwPKhoq!Z+#Fe zTtBGfIp!-CO=Rn90ZVNC0+aBlDAKnwzUP3N+zM_jkg%U2r58YW^z#~~YQ1M%D$hxc z!XDcOS2-`zOPg>#Ha529@1H-6TBDmSHI+3wbFm`zx$%nv@um3AyMSKq9(ZuhE}r6* zS|c4~r#*gj<0LBx;{4e2(m$|H%{3H=RM9Q9&-Lf4Vr5?ur69 zy`i3Xh#dH9pk)YZrR}5B4l1|(V5e8-u?d>DfiT|z3*8*S4E}6E&51zZl$1fJWpl?Y zpYI~3q*JGF7bZ-O-K%gBfs~PBv}71FfrAR{W&4}UV5OmIxmRtzHUM}J9!~?yFPzXk z99m0(31(hIknt^pIVf0lh8URp#{X!C^cS`e%;m!@k}v9}gZfDVfQWi_ftN!&{N#a| zygw{;q3?{y7(b5ZV7Qeb6W{MJaurY*-Nu23PciTjH_xHUfv10U7u8u4b)1R{3c{_~ z>5=q=&6NgFKG31pCMrLxEqxwe2cMgTg!tU^`5cxbvgX8;D=G*?KQGm=O3k$>f@gVS{iCq#bCJ7uG+5femm5%+s%f2@EkYF?cyOawXqnk7X4R8McezO8A04`{?O2 z2n>;fzwOG^1G}{v1D*mxH*em*ukPqSvwmU}7KHtk;cegI=tVS!Avg_CS*ODo1Tyh> zx9iInR9Otz52(1=D-hU!|YC^Xw0nO9-O5OdGr$vu7F%A13^n2bokG=qo`c zhF~1)4)GxwS~55V{lID~yJgd#CVcpjlgUpeN2D<@ZXNBjF8k*YJt@{XEgq(VKM28; z&yH40d%GgYSwr1}gP^8j@B1x=vTvbRMhtMYxskiGqH5Sn$=rRY2@^;FQhOgUzxwy( zEg-MbR8>WdmWsil5H*+vD=!=bP-7qP&NcAOiGSW@Vt0}v*H@N{c_e9$k5rW1r^&Eq z^g$Dx`A-;-!50$*>0v565R{lcIU17{17axPJ9ALE{k9k10 zwG4l=GkbRs0J4ay=P;ZSB+#-1vdQRfgzcamdUGwe;WOY8*iiL&^`LNPX9xU$DCy`z zfIko0sPV24_=lmsL*VU(BZE`%3^Y3S9YOt^vhkB>ttgt%NR_TA<)OVv6fi??4vq#? zMjFoR>wrz6&D(taNOUa#y!MZ^ZkBYAQyYRQPv*x%G}C8LW=F;(-XpFP6uSlUSc{dR zoMX{&rKcc5#wIRa*%_RwwmKat2kOf}Un>S37zE_&HQ$&fpsCIjJXcwGOTItuJT3QFa=xV>dDdkh%S|LXeZ+5NrkysL6qM)Q4zWM1Nuz;du z=DxeMq#;#(x4?G>7#Jidr~%CecEj{D2UF(%ZzoS2_ygNPr{YuA%aW8zlznkMc zzWR+DsG6w&EOI@_?9>lTANak=MGrsg

PGhMCQIJUOy)kMGD z2Y>TlKLtGEuJR}3037k=AO%VI=v76w_ZEAEA?jOvH=?Sf#BqJ^J4w*pv@SQ&w@ld6 zjjjf1IsF$JzA$aap1df(4o_wz?pUe_4qRF=DFqq5%GO=5n@fdJRvodMVns_dPHlyw z*H2AeO8pJ|cS|G~1wxeY0zh3*b+zQgSb>cQDCt2X0E5-{+;&%G`PrU0o)Tez z{Rd(!L~Y_E7(VL`kK+VJ4V~sYC_xq#3x1k)%J0ZtS6?6X11BURY6Q1ZSV1e6Mp$c$ z>6qNelB=iiGGqKp&utW_ldd)m%EBGbt9;@>d--6EMFQwM;4sRgZ1!~e%(#bYk;-_YU;iXlFwGqf%;bS7Sb!VLkdp7 z8E~t&tUp|_(0n7iAHJnnRQMso9@cvQdMq!(b@Aex(>rO})2O2Pze68WU0to)t%I{x zO61m7`twIW@Tjs%5DlKafZbjMK6ebK_yB~QE>6zI!9nVW4KSq1uX z*oDG_OS%q=9(2}Szwv-|7)TpSNlO? zwBhs4>l757*r|=&TXUs&tndGO9eHY^*axWEB=~1Sw&n@GauCY{AXKM96hh%@K$r7A z-XH#`*JoSm2^OoU0~Mrxb2%U0HJw7cvFU-Z=$|`h&z_C!uN}WKx2*Zz|DA(6H>X5` z*s9MZ^~-iMb3Y@n`mtV=$iq7?W4nV)z_2Pf_C|oC0IGu%bzwY3`2X4PkN# z)QTcfP%*$rsG(^uEOA(NV|hZ%%*`7u_ADZ;8>$W?c{C*rkS`V~?)#`M8_u+1Z3>a~!-0BIoDlxk6`YKl2|t9~{xEYIu*g+^0?xnDSd3UKeJp0(X*0s6q~3r3TKo@eD% zIjoGf57P3f<4H}L^zjd{%pJKkY<=4cBYj}EBg+3$Z|(q3goaq=6wa4?6HUPYxDDJWf--3(LZ9T)(Cd(f~15xJo{0#D#CfRxCbeA z^q@h>G^k}(%)58b!MGcoXeYDmf9`r!Z_ZsT4^=($wl<=MhjzKY@vJZV@!G)R(COOs z#qYU>o{o$b%ojV6?omD8X%2r&Y|pfaeSbpV{B@`v8} zkExfk1g;>rN{f3HqFxYRA%B-U-m}Da<|KzMO1AesVk=@}TJtHFl`hK8P< zfNgWrF!}Z3_|fGev2uFE$>S!z97K}q?00lf`U|RbfOcuPd3jq7cb5JUKtak{>Cq!z z2+XW{gEu;-2J0n1M{3&%q~A_GYxT5deSiy2ukRsuU4tRIf&eq z-UvYBiH7i?{m~}*RV|LipH4eC_(&@sM!=YB*u2&!1f1TVf;Iawblm{ISAnk$FhH_< zW$Dn6-W~}?L;}bCZGq(T=nwvoPl_{lW?{@dXYkM@Om5Pq2P#uif2vPQgwr?cY2SYu z!Dz={^a{=4aEyju|48E#@-0n~V18*yLr;1#RpmZL-w_u%7_-DH`nmR_diE)&xM>jl zU(UKX&u@fSeY$V-k!saC>~9Zf4z}GWk^f%k<<5bo`jcILupqX8 zWADLu*%dJN<28eW>i=u&%Hyfb-}ZBktjW@pXt7mODOt*r6v>hzjM9uPOO33@+IFlV zN|b4l2vJhjl%+T*iIOBCWNnfqBxL8kzUDVG@8^Ag^G{9ZJj?k$-{-!s`@XO1zAxXm zziV6F(^eadhM{j0(+d_(>ag!=6(tK4cVsx2a4`kN#M;`Y5Rru((BHm_$x*^O<(1?Y zsFD*{kUBE82wNtyUss6Y1cw8=Oc!@u5=V2b&Z&wId9h$`s}Rnm8@O9J-JeCb3V-9z zW|v8)&U#r>Ya}Jz5Agc)WoX-}hYvLISe;{Q?`YcxuPFGn@98{-S}Dwy5Ln>Lk+tyS z8cUkD&t%>XgE?^=XNBY5JYv7_KFN>DT9@ZS=gYYR|_xVI~&T=^#_kXbKA^5;BN<6N+rvbC0Lh} zyv6?x0g+!7q^X{Fmf6R#<`p}Isa4nQM>5k3!fxMnkKK^*T+3_GM~f@M6`$Jh`O3H> z>jEzITcoE2w;tO%=Y21Y0~p1xPkU}sXCf&a2NB#9IfAoj4t#cBsd~tCkXht>n-$(Q zGdDghCMal>T0(V;zsk@bJDo2joy=@8ztX*AeapR-DuIG(@%PMVs+-Qv1Ed@dtboSd z%$Uh=#A*Y#ijF&u?eP_ndUSdm?&l)k56397NlLZE`4a05mr-|i4)kBtt1Uh!7houL zYI+4ODz#h*sWaLgoA0H%ttsZ^VV9Lu ztZ?ZkkNXk%0sHi5u;^S=cUz6v)1tWJe_imiY?wMP2ODAuBzfDvd}%n=c;m+MSQLGd z`+&f|jXdI&*T0vywkJcMRGdT#}qY4ICJD zx4yo9;AiyU2_TjKXF=Rx3;!{3_2$i%w9{sPw7xMeiBeEd9$~f=1==!${|ZjB`5QS) zVE#HV`=%Vp#Sqw4(uW&E<99na^h&ES+e>Ijoi$DO*519S-0h zB%ofrM=j|7e?p!4vjG+WzjX}y&7pj$s=Cr(=foO9X6g2PqOE3TYI+_8E-nct(@a)$ zvL9`VUA=Z>FyAtEb}f*P^ARzMA0zLOiq$w(`j7#X4#Yy-_sBysTOMc#V?#+-5MhS0 zPTscBrsh$0@gLE%(o$$M_BfUDf57XH4VxbEb>2|Y*`&u3w#>jynh)AxT0BV+!&wq< ziitiYD;R|VAj{tUZPX#h6giKus2$hi<_dj#{r=uhI0uO} zPk<~sEVOx4x|8H}k+&b@wx#4;p5d~JQFP97Y}gzW9NghI`^As&K)k`0 zxh`jWRx27rn@9G>c~;gv@9qFLmLb$1dcCDO0i(U(0tuD!a_`lJH*ZD+6qx=N7Vo=7 zfA0H)8hm^GUWwl3H5bzoYmVW)N-#-Xdy{YWv-gJmhoyA#48=ymMxxSg%J9XNPiICX z>2Mx)@^!d=q#xcVXAN^^=GvCVi`3$T+QZEp+MR+WgAs1zek(*^>?o!an{i6U)1tyB zGyH@7^U?VG8*=#IrqSeO_1Tz%R1(FZ&7NSpUFKyIav6!&%BgNj&$#55aEeDFYsi&G zS?xVD%G^i{gDtEn)#YrprioK_V=-nOO4YomV*jK(Z(DoGS??Lp<-%vf`;>kU2FS$Dm_iioI!`Z$+qt<&Q_Z+@McYWZdzVSeV6~jf4vT`q$ zjj7ispO@kD)7(k{ii0!Ds#qi}h~;KWcwM*m5rs@Zcu4*j>~Q238(hA2NmfC)0d3;5 zx5%3%hnuG^+RX!`rMPxM5odxkW9ir|cB;E2ufM#VDZ5kUhIaT4v;F3DN^hXN=P+*6 zt`wI;i0`b-UMQ0(eDt8og40YZ!*v5Q1a&$IQ%46*Q;%BGUQ90cSAgc<1-V*&HR4aNhM9MhpCezaC3rnSQI(4G-|e^p;FmP zmyN-HNN<&Zb?W@Ruz5K5@co*al_h`%Oi%!=O?*c0?}f8{3LuI zA8;lqm^9@v{3@$6%pWhlxZ{WLUpXo3qPVE25ae6<(L*ONCMIU$w7Ge#6FtG6=fjNR zU4O>PnSCP5oh$#k-OE0dDri5m7+`CQ@9)9D9wdD^_(d z`$MS^gu&5kzaeQkJw3gq`_!<49nbY768yavXjEexM{a_!V=#__qGV)bNVl{PS=Ma# zQ&U$=$C{*;f%WwOR9Uc?6o1_efDG0oG!a>++G0|3MQE4)J`-n2lFr3MM596tlRx?w zBL5s48_S_KMob&xN|J>RJPKg_i?Q)gZ)&C_DlRD8sLwm~98>A7%frj|?Nur5ccxd> zz}iVVT=>eCV47ak6I}?yPD?SXFp38;%o;9W(f%pAI$SuJaZg5;eE{K<#LUuWx$RdE zS=xWw@~?NgZE=uUU|ceve@c8&v6FgIP>^*0{;SR#_HrR1A?5m?M^Ep-M0k>^nMMde zSY(KBI0B#g<7yqKQBwZ+f23hrrys*~gFe@e>a$O~5ECf_A@)Hp?seOVlCN3p) zzcm++#}zYQIHo!~I*b_ISI)oj=F1xW&kB2P%;xt;&Z-Q;K{s?Af^VTwicTN=vAaMt zV57iOdH|m@Eb0sIlb!O3HP%`RD#xY_WPn!7%D$a`C_r!Xosvd@aNWd->}&Q5-mhA13LncvT;&??xg*slmAA@Zd!NiNHT(Dq)6>2G5TwE!65nvn=lD1F- zao1$HAyI0e8Mha5{XSon4iYmTp@m|JbPKo6oxeS1 zM_-@g@MN)yIhEcT$~+ycQCFW{ldbjHbWO5z$Q$u*b6tG9;`h zaGr5D$TVCqadK~qGz-t7rP_{`Xm3x>vR%E3mWGEN}c%CoY~! zdD~mFQ7@Qz+O2OHu9_{%mY`RsD9=94)LmQud%g2?p_P-;`W0N~aAD0+Sm6ywr;h5; zWb~`gz7fa304DD_?nfsYh|PQo2X&=KL_JS!K?zdR;{zYou3v&ElN_oKk8P|Jx4=d+ zsN@gnyA(B67IKT3!U!9IYnu=G^rDktCutv}ErQ~!&4UY47gv8=+WgDE3+)$6R}^M{ zmmAB0{VvC2?dxos#=xon{D76}y|^yG`=%GIF{-koujl+aZBLh%e>p1noO>$(ScKV4 zzE-eNuSEpeigO2~8~<6WH9`41+0zc#3=i#7HZ$ig&ULxIE#G$GSOmGTRcr~o(a*%F z{Pq50nc=fldoP@g3US=$6^0K@xjEED8b=j-1I}%L- zXohD;8nh{kt2~7#oJSZh5+V$9yc}P;;5is=d`hj~o$TRXz2s0QVm?*#t9wM2w>)Fv zAtctH!I3~`B6l~lQKG^E0f=;^8xep=I%wgy?qLWhAO7WBY~@ndgHqqRT?eL!kIw~2 z*`33&`uLG$H0qD3;Gy@#A7^jCJ*rrw?E3N99S>uL8nSkRjf?TCoRzQeQ+vLCWGaoZLA-HH()eo3Z_jPqmFkeAcxA9(+4T1KV`Tiq0@Uy`I{4Er{F`Opk}%kH7qnMns8ajDKm@qGij$3G z#uhmJgfMq)({E=$osD_#_z$>-sc23cB-r%F)8aNhSvrW}+N6Ta#=%QbsNBO7Si#W2 z2Q2cA{5f3JGBn}0_T=65xw zS*DvT4A-_D!U{^dZ-tcyWke~w9ZIg~w$$qEqm`~b@75N=&nc##0KX5q%dSJ3nn73F z&R}u&>_mXXDlBwaZofsp=JctSLf!2BcS~WC2@9lfwBC%&dyI^W9E2)=S?N*WuwXX4urcvZ^W=vqh1Ecah38T>lM>CmQA8;6S|(){t0$ zzhFeIOR6P>q_2NSh|a@evM-GG{V^le4wK%IQ81ukVj@I(YuDDTpcr|USiHpgJwK``G=r{7eE?3x0uGK&WClwSzY?MN@D%DN zCx^_Th|!qvO!$sKb&GCvpO;znoPGbz#-^AIb8_4n4<{?fCpT z7@`nO9i2845r^woO(KUL={CyG&ld*=TUS?C>FRdRZUF?~9lgEhnS-olAn@m>%WG0P zl$joAM?^G2>SW2u9H2mviMd9g2EDUzJV+J^R}(^qgP-3EuhwMtVYa%vuSz9Y9tB42MUlL{lS^fGJa1XK)eMJnOC2Q=V0q9orsn8 z?jjB!A?0}s>1LWGYqLbS2#_uqd$J<=V3rQZ6OS3&P?Et%kl zmEMI7g{a_+eQh$yR^_eF^PX@gQY3bEcA_KzZVLeuSm`luWORZMnc#X31!Vj(i0SYP zG_Yb}!2da})uvI9(Q&aX8M7036(q&Q)oF`#;{yr<)#40F<)o3xf(ECw33KFt*eBp%AN6lwrY7Kb8c zy_8h;6J7-uaDeFk6KcnLhcN~5Tzk8f_15K84R8gksZh+Z{ng^^@)O_x)TODT&R62? zjNIe1mKFOI&;PDeaLoTQ9gJWIej{h%-SAb@ZBj_t>T&br+Y6 zx}zy>DD$d&dTs@>9>VKGir^oLdX$Dc;Ad^#yqRwfG2u|f z>WfxyVz-U=9iBT++FPT4B^M75-Egdcmz(>+No`drDISpMg~mEfj)uBCr#@%^Ofys} znmuK`pwHXqd9QAxv~<~(4aQ{3A@XB&-mC{quxISOu*0D@2uJf*Qiff0t%H@tpJTcR z!5$K3l4@#VT3T8}phk-H9wMy^r-%&3t9J>^9Q^4*F)=ZuCp!_sbjgp-#L-I1%kS1O zhsyEXJEhu%I{W( z=72qNz4Bv95z{SI{(U|~fi@%*sjS?MQY4Kc#a`GBIh*HP=%n(fb*^fm1Z1PjXT~}& zl64a-5qigBo&Y1w%)Ii=8*PX)I=Z^*HCPTeL5d_!FIXdBWMm{}cH`q)OgMx1Qw~=* zGBGh>M8oPvEBlt;SS}OHdZYAGi2!`5g{Ry&Zuz&_Q4usr{=&YL< z43rLa!3@v_Q?t>#>d}))P_F>c5J>`HEJ5jhYgDwN^Nlk4O2=1*pGY$tI2lQNT-Bhr z&>l+24X|(d`M;h#b?O|7;?b3=Q(qrSDl7kbEXOppQlKT2mKBU{yPz-k@lz_^iKf*aB1tvtp#|LppHv1@atQjO!!@8j zxq;t<`%bCclc?v%oG_O*p9 zRvEtPWHfNuV5eYQTwG@Wr>MZ?pY<1$zk?ME$0GR?7WUCs;oHOV!n`E>b@%WP6cITG z(_7lo!n#vXcORWel3Ncx0jSk-ch4@%0St>am;iZ9gH>%~YJ4`$1107oM~)CK3af_& zF45l~ugmz=`0Vnin3ymeL-O0mcxzx=F{Cbo4!(o=BLV*|tmdnV(V4`3yWlfr-)Uu3 z9o}XhRvQ^?n@g5&Y;5eBQb6Z~F#Au*S0w1ve1%qW9g0u?6?y#q@qAMA&m+PVf%>t$ zY~lopUM7XXyU8`jpb%&zAw%{?eBa%H(6I2jmt7m+5R9~tqZUWjretK~jz5Mj61sQ= z1qD)y1>u;NBXGh;Vgba@z3KasY7!v!rC=J2%*-}gl%ETABH+oCg|t5%epnM?Ujbp^ zP|%}AP1A*dj6Wc9Fv+weMQAcKSsBS1)Uzy6zeTh{%28ke?m;ty@O5_JK7ESR5hX1z z1Ox;qSR0sfS+2#AyRE1-i6;7hI-t;LfPr-X{(V;fs-U1CaX>9HfdD;ig3CpjuT|;7 zKm8O4Gz6A7TL{0HHbBhruO9+P=X4Oba#N-VwE$Mr2<0V65TWoR5=4hvjJ=vic3@>3 z>Oh&{0m26lnexxfl<7jB1}HS^&59r~1~*7lNZK^W-=Bi@mE5{@2@2b?$miG@9q)d7 zi^M5ui5|{OUuhSQM=a<^omB+rmgb}cDMvQU2AJ=?kq64Vi~qtdK232UjPT)7VrjH zOm%H-4w#ynf)fmiP|?t>+il?EHgL2`tEv`d7EMYK0y1Gh*u9A*dfOo&hK@T?mf0y& zgt-Bd(KS} z(ox*WPHx~Mq61f(o8Dq$WAm+S+2MA8P93yrQSt2dC-4>&ybGs1WdIYw8W7O1f}=tI zojtm`)0O*W> z3V-j|9Q>b%i_8lbHG6XxcOxe=#4{ro2OE1An^(rS-OQYvU)kI7az1##$<1-w(#6HW zS%izr_W%9`r@fN}S7b}NJzV9A!;_cJ2n2}{<_9ZFGV>JzkrDA!`jNUv!rHjI$2X1r z`mN2Mie8(6J>HwoM99@SIN0!6_w@(ckiO_-YZ={fJ@3u;Gb`BGcVw zpPZQR;7Hy0%X@EeM@)>wbMgK`Vr)mkn0GgdO-6VfSDUubBk_F7y)^)^9?d8bv;YNFG{4-HCd6eyNDl9DcIzKIO^& zx>Q%f>FB!Poi8gKjA|tMR=jEk&qeoJ z=>4WvS4Xp)PtQ*_#rB6xeD;Seq~+vFd{5k%l@k60kVyQ|(9)B6^5jWP_senj4pgms zmz~tJxS7{Fs@8`{TO!-62!TnQiq~ge#56)ZHj5WCVO$=E)4_1JmR>q#Hq$4Yb(t33 zNfUPR@g)}Bbi{OGe;P?7JJO@|+kU?4`*(0~;8qf+;q6sdeY6m->%CrjczDQdKOx46 zn!EA(Y){K;f34Lb*>|C66aGBrfeEfae0bp1TRg^1_(^`}p2vHuT8sLV$GQcKhp;G5 zpFMNM(>L(lBRfAoKb@t&n1UBA`mW$Vu`E5h!-d)ruL}&jN;;n@89Ed)}1;Xh|!b`cXY(^#!C80>@0LTC-1~r zBN-$mle;A^60)*b5oLDcZK*P0n7hEiCA`hc`}Oiw@`{M9y}fjua=VUr!HDaOvK8g_ z!^MGh=X(X!$1Az&>gxYsi9g51wZTDo?&Bktsg!68w@oAN^^H@n(qYo~K*KxPyd*Y4 z@;ru!T0mJ>SFzk~JcieTm{IOyUh(Gkd^>8bxLvGF11`1ILSF($QC>k|xi6EXeDbwu zqNqF4>69he=NJ4}n0)$7aXY8U`RS3yertRCY^UI)>1dg)5DhUd5mi%u`GmZ&v2o3) zu8K+n9=*?$oemnQhk|oSDdh0oJ6TKLGtj{AEYiOAC_`yISIO44_Tv0xyfFcGTatl+ z0aiHc_kp3_#^!24-2zohbSpBSVn;3^>@Ay`vTQd51;CFfxSSa^8;&Qe*U zk@Kj~SJ+QaPsPeyH^yR-dR4`M zgd*a2d#I$aRMzU9F44RfMcDb8?eozFT?xX@%Gv6r`kNh-0TB|%@9AG3zWMa&+QjP< zTZB@APy?L2##-MK<=lY}l)OQsc2)UpJ*)7o4&lIyOE_D@waF!pml%~2MPwWtxYaV1 z%o^TahEn!eEB8LIgO{7lqV;57zm`DjIuij{rBzf6ot?SD_CE03Hs!2ZPx}Z|&@yAJ8%| z+nlJm%fhm=losLTBP%$Ul&gk5&{ME3k*XI-{3u87OA6SFIU8va5^eCaLTrN=%-3mw zpICltaupR7T_`gOLRft)Sx|TB6)xjcw zRVY*`8yk+R0ArD@Tv&cHf?RT6?;!Fo@J^ zkK?x<8?8Ip5EZZ;k%qEC;9tG!ELjIT%!<}?r=g*%zVjeV(&(3cj&PJ42 zqd6Bk*3crfcyiq_v5T7%WJ{oy>Fvgpx+57IaKLtT{Du9nAllp z)aY@3v`8uWT1;@<6P39bD$YMXM1QudWnRwG2H`UeV;8E^NyHDhK9E> z+iPAjJnKELXkWdBYx4U8rq?)3KMo?I{*7tt-|ne#$12jDa2nKN!29$ni2;YP7!heZ5K- zBLE)`ow5&CxvD?GT_9_ZtwdZ`n#NGhFX1@CG29oj@ZCg-xcW|d2LAmmBQ4D;IN@PZ z8gcp3CDz*7+O~!Oyzx;Ea)t0k?MjzyY*svC8V7rYCr^~2BrDk#iSY52KhlaWOlYdB z|2RB4x_2<)UC>e+E_^=M`ZZKGO=SbMNEb0%2PFf$cJC&OQr?z+SGA^VcSA7!>nuc@ zmVxhl(FOD$_#GW;0&G^3mX8{1ZdG#BEfMqucbS;($)@$z)O`Q`FyzAr zbp#VTyMhX-Olw=4Dq{ZZV6woeW@g4XBH6%W`ZCkqyG^sc4y{bltdAZ&k~cTcXsKoX z+Uh$A>yef^U=<0}q17b0ovThaBs_d?NWkdVB_>Rd86hJhlZRFoDdBs}N*tWlWm`KF z%Kq)&KL;jJ(NUA+c>CIy@aZm+f_wkfj5*wsechQR);FN8NjpA!p3k~8H8nHdy?e*{ zTx{!|_vriUjNi`BPP9-#nzagXS~w-TFTw-qxS37WpUu_a0_bft6$q*_3H_ zdmfCtv-@u+Uz}zR`mTD5qj&zTm2`XA_${YLlRg|SG?L0kJ0{NB`<=vl$2S|RZ13zu ze*b>k3~Gb!Bswzko};5<87F*-w!Qt}K{!+8fYfzjEaY-6#kM(ubaKSaQZD0eHT_5%;pm-4M;F zv>hl-kvPa@&8&Nl0lW$G^3h0@G}(KJBCbw#8GF8VU1nP|&7tz?s%`D<;$_j_zIpgq zB&=5L!vWl|1zDkvFzfmLh;FhWUeI0>F(1ZNYuO{Ng$}B$-K^xiOPVNr8rT+(L@tD+0iwiQ9L|}7O-c^XlQc^%zZbO^QRjXQYI`z9a zF#tgUr?jM{$nUr>8Ms7NpX>MI#VMfTcR4wcZMvTT2d~l5ZEW0+mGBjTQzfoj;*!}>Vqn8fA_o?kF8cdQyZnAtyOne3$Vrs2-tk4Jt03^Sq)YsP+wVV+z zt+f-AUp^wdD1{C^{J<#C}2Hb{}rddV-od+8?#=_T)nzB@fTRZf4|jrbadeAb(@zs_B|8yw5i$~)KSS+2RO`ALW`cz00#lmrlPH_ZDz@P z`?fzjvf|g7=K);aq+~e9XQ3;WH&ed&tM#PlMn$8^3Gk*C5RpJN?Z-y{_Vo<|UI%!6 ziI;b^&FVg@#85Z=8ZVTeX70e4&rau$jErL2QGtk^!Fg2nGY5x4Z|(ZnNcy({0jqrO zPN#=kbZVZm5p?15>31+FBI+^s=d&eWoRwesic|MM_UcKO&d3@~edWsEbcIM;z!(e< z`1R}YM$Lgf$hMHWI!O$h2d(feGIGFcVs37ZZ4`v;N&>A`^sJhiTJE@3zGfd3l87E& zjvq0gbP(twpnaDTcI8c91l-Uc7QWuWc=&%Ba0;O4Pn`Es%9w?@h0Fv zLJm_1;^0O`#OWT|09KU>)UE|Im8O=Kv;nK}9TW$7n4E*F8@1knzTRl}1o@2{zX0)C zeGkUv9zVv$!6P>P`{OC}s20XtPA;y9&Uis*0G+Dx^dCRIv&tv(hy?@$0KD%EEwH`$ z5+AQ%YWm}3PqeD(^3-|Z)2B~U>?dnW%Z{L!ftX{yA7}Ny$D}e?2?ZLSp2Geu*Ie~R zv=WbhqL3@cabjCdH^olYN-!Lk<3(Y;IKw&Y*8ZV*0w@~4^POZ2-i`06=kqLHAirTV`Z#N~=FLv&RU)FjA#yspk9Bo^k?8wSTh-OoxCU1Z|4lV)TyVW8 z^apW~4Adj3^(%{(&fp?QD~su0fgfmuzkqi6JsT#-!V(Nc;I(GYM@8)-?&o*GHk|$D z%^PW1*)LzdsAjGn9UtGIre57TEHY_9cmQz&OyB4h@rR{VQ&#qGHO<*_&aCX#Mc4A5 zO(YEeo^Owy-P|;okC=;6*P~u>uH#%hR&*l@A6!IbcUF7uyeKgzf*YgvJ8Cze;58=% z&O0AOZI`9SyfZwRteqeA{rh*TIxVTkk8@7#5#;;N#eXXoZR;7$)nnL)^*Apqf4W#=H zWIvBzO)ER$r3x3jINcd@8@1I~xEBS@;*^GzvcXMEQd|x!HMn9cOfT>t6i66K_fci!vnNxrijTEGoGs zqb!(96OO!{-EJFmQ;5B`00HdXC3$fwaz=+5(bh}sd;9h+n;&bx#(#*DgsRD~MeYp1 zAqbC%Ai?-l82z?7n2%AY)rT`-m^(cM)xNvbJDboVxZvKN&Uv7l_&<#g&tD{wxN2O# zz(n`@`EZQ{+=5lH8-JitV-QwXNSy_-x4D@a_;#QR>Py1uC6fy3&f}o*Y8*97jzU}X z_}74U^skX*d7`H3gew_LzAZR1jzH)$6k}(4**`@`%SChQiA{__j{$i$knIcF?XHke z%%tB%O`8dHW8^+Xjs7Ox4X>FH779MgYn!zv$djwSN89s?Nn*pZSM$Kyl9rL#f`aqD zbdzWR{5OElT*be576n;KnLB@IM784eY};E~9WAa11Rs~7B)VMvn3$Mea73}y1%oY; z?-m(NZD0Kvj;DXRLUgg+xX9zjkHs`UW^L{ad^%9j8#tJtO1p=gr+O?diZTI#pzGL7 zw!4as7|7MqqV}m^W9^p%6(K}}Sx3;5gEh85^}txE$i?HE^RkG-7e*I>YlN53`~_BD z{$PK1*X8fuzhYkDx+mwys|9r8da`Ms^{U(+c^kW zn0kmYFu)R8@kJizw2NzHA~!|tU+p*}zJC2G{QA_R=A)zUCm(>94OAC zHF2OBG$}_Y9vEMO^>vLNaTKBv+wGAm#f|3#qybS722It|l*kVpJB`XE5?YZa9s8R3 z&o4DqRUbcn8X}rrmzw$(v%IkZX_~p7$IF>uj2VDHKc9YJa|p})H8D{yb3bW#1CTYD zj9v2|n9UXC1-hs&AP~MmbBQf1EEFkynbwOTtHr=@qBvg8Yy~R;*mO&r*whp+Q;jYh zXSJU-H#dKdiTMK^bo^v~VPQME?lfKg97oBugKpOF z%labsV4t*N4-Vn%?Z7tjI?hN(#QDLYUHGfOmHs?gBJX8M#>D2EV||hY@fw9Fj+BZD z3WxpTG51MdIJ2JLB6AABCgXKoQK$2m!irGzafp(2yex|p2?nuKQ8f;FS|*HK!;_P% za_J6e;1;##;`79VG{kr$V*e0e9&9+>W!KEB2lfI?svlJot>;Dwj!xo9HIRYu?v^%UYs z5V!7YH-YY48ZGAnh@A!bTd)@cEO%$fBx36iV+6NhJp%K^O1dT56}W2pvF{^A6O~#p zgjb!73~I#$tl!=B(P(fGZqU-|nZ^8&sC3`#g7?7TN`Wp!NGtLU@Z>rfSu-rl;#L?x zoLVpeL8#L0wE(pFxVN1SV@>gPi#38HK?$N3v^0aTaBO}3!-zT_>z#hJ=S85a&ASqw zUYws{d`D3FIjT7wty^^N;RC(dg}M zCs<yjii`eMvbux3qRm<`{km(T3m0x|Nv*K%p1Mik!v0}e0-=`wE-8eU0}4#sIy0 z_imxhFptF9t{QM8d?D{IE#cH!v)2q=lROtFfx%F48zRzV!!gYcZ0CZ8d3P%-Dc=pW z+4fxP#^w)@c0A@C6d2nEC>Q;KgsZRJ${pC#%p|W+j2ZHgwjK5?2D&?m_^xvJyj7ew z97|?b&q>cPc}G{zpGE-TYm;@!p`iqT)??${U>{rsrAap|Y5^i|cBwZFxYXYgi{~F? z8SBpWsn3r0oGsqjjrmrQNu6Gx|3jN!LV{@5#Q3rsi+3x9|xG?}EDt z#A_SyEpZ2xy)KMc?D+-q2cLi-)%##$peqHKJzij7AcRa^X=pRJxDd@pww)l|bqTjM z3QteZ-L>JbfBrndShw)LF{$52M@MTTrD5QY^}itH1waQT_cb9w5eWJdFi*jXRE*(n zNc)}z1RS^pw2w~-32R$eZnNQn#n9x~`~nkO%}a{hH}!!iz&`9RZDAxAd=}=7voULH zHv8+NE#UFwh}i>0S{p4Vkx_xlwJ&Y7ShU)S1=t8Cp=Sny4X&_=`^MT9-a{!M#v>yM z(a|j%<5k^9UIPc`aCJ~t^>*dFP>8!;;*cRdDnNVRCGmG=T?JfvnAWR)lH{Ddew34M zyXaMi2@0U0MXYLJ3Dcd}8wQIGCTs^?zSfQ6Yt9%0FSq+tLxXg6M|aU_=8?Y<6p27j@Y^$`o43Eb4w)Fq&_ z0UM}Ffr|clU-aJ*8N^U;f|%zQxbGdmivvHg?LUkYc1pR64npt4!e${@SSV_t+i`Q2 zW@p*F)vJ!7j=Rf!;AUot>eSpXpYAZsO0(=f7+d)IaHI;j()F7+XV1e@fBbj{HhiML zzrSo}$nujsP4?v1$FHhhv}^E5de*(q_zQ#xAZD?2s-X1eqn}DQ5M@r+uV2To1OO25 z;e|oGfs5_~wy_4mt*{kTv3OwCRm@wzBqZqCGTX{oOJS-ymI@u<2EgH-qZgsaM?{Hj z#|RcGs4s>)ciw`n)&I)K1(TC!_nRqs>aCAgq4ma7nOzgB#uDPTlXR%BAObPjx=4(G z0j?}2QGeVYamgQEd3TNW!`(N0ZyTpEffYDMv0qu>Uw>W?O;y&`miO_gZsEzG4Y}kW z{wX&0sjBLi@_5X<-{V5rSQjzPYs00f8%h;lfJhG@|8NTv;J5Qq5CZn`TcW!6A7j_c zIuM=U;^8SESTPrVK?|ZKtg)q~W%Su~xY&vecD?zG zgOHHt_Fby*ASgE+938JWu)|7ePl`_9+W)rR*vEy>ZbCIGpgU zr#Ck@*B9P1FDxzwD`he=F~NJ@78Dee$KS=QTC9r>AMY}yRoz@E*<<`(%~rvf|ArRu z7_q)v@&JoV0VUP>`h#FMJLYcjZXiOLO?YDebamP7n^b%1V>U_r6GE9U7Fs2^#(&pZ z{u^*`g!|X9foL#{v-17ioGHeq1_`^dbqEO`#`IQ*<}?EX076`Y<$jZzS^+{B-~bro zDw17Gps$2M`ow{)F5#x9*@RutwbaN@Jlyv?%-w$;@|VU{wj5!c4Co&J>303<7yt=O z+nsd~s(=XrL{?VT6wrg}?KbvPu=DRiFM&P+fVlWz&Fk==5k`)IO^R`~hl|awx{o>H z&Ckzo_;%6dxF&i--iZ-IU~@PFZ^pRvAZdsm*1bLh??2l60;s4nFwh++HOMJ?ev4^5 z{;9y6n>hLL7UCNHN^pVF>^%7uhU#b7_2i}{qK8&GUhAR)MY%yNgTnYeTg|sH>&I1l zcn1N%&CJ9UXp!Xkn-=l5gkl>k?k5p+;#OklndUG`ek)Q;_JgSL+B1e^tQz|IqD??5 zD`qSJ>=Yaf6^{galA>ySL;vl1hkg?#_SsuS@3gWcKS8ic^B2o2Zd_0+YF%@5w_s6|M>phzoSF(pbWsn8P^X1)}je`J#?eceRZs< z!NeSIpnvG%!Uy6EEbw~D+qDpCW5z1rbQqhM906znoU7+AlBY7Zv1L14)b*S07%NCW z8>Hzl8aTK4KWshJBpy|$hmZM7nhhotAYHu%V=;M7#asSfG{(gjxZ&UU!tR3nkNtW_z-qOGug0%8dzI%SE8tR+4@isj)8#z z5R?^HB%Qby#?FYawYV6&26baJQSGVw`e=T`7LGELm{@f$+*r*$9_;8UB0{p)(Gw+a z&@X=aX;uZ;mu1c>Pt9OCp4uCbhhl3HKFxA_;l7&v_~XL2UO|bNhNmeAQtJD8Bgx_8 zSkc6xjDNI>)#FFFf}LAA1X5H2#^1E;aK*KtYU@M^ma#|&RI}CJ1qW-5>MX9V>M$MR z^sMe_U?Ve=U&lesVB_Fmh$5!)L2^9{Z&7!*(;AL0Vfle~>C)8ZCdosv%0v%yv+qB4 z;S!B8|FFz4ZG)3a5)Tz?NMDX#+wUtf92{w*$b?*dA8Z8n-r*|dM z0w*8xY#HLhF8Qav1ReVT2pfE2ERPuhM&MzBqVjkq>EJ1<^Kg%@@xPklSW53|%F)Su* z&4k^@YqX)c2p5||=g`NW3ZnA9tSn;1<+*hTSd=*w7A$H7up>A)z9I^sh3e#&sm3$MR7|xZr*C&IUoHUQMY5a^i0SPZ;}{cpZQ1gP23d=j7gh!*qT;OEm-R zdw0z?W?&=Bt%5suNH~Jyj&elA;E~Fv{8SbauP|fUz=4?7dVtNwt(nn8gD)u;_q(-+ zgg_Hzo<(F#ocItYNBO_@X)(>U&KXOkSEVNjf7ngNQ*`Co^48k99XQI5&!k78!$LFx6y3ec^K_$n;!hkIGI{$0*t}zN*m2j1rE{(z2CNqU-F%)$&%+3% zv|q-~d?yL*W2%eZO)2$*YBDw=aS_dKm6nG|yT-32Ro+Xz>1pE+El*^-gYMy}`I_qa z^uJqD4{TQY+#4$O#vp>sL1=VXbk>2@lsX63|BZyUI$NReH@2Ff#TBee_#_T?TpZC< zuFqP@5V$A80nVk`GP+OZxg8vLaJ4T-I*Tyk_$ue#F75f#b~Zd09ecF?LgIvn5V0FZ zvXFXSbXV?hR@rd2*T;P()Upc0h29IaX>h;Ld&%(1TmE|0-_TYrUXv2`rBW+*Y&@ZW zFof^k4#JuQu~)zR{ShA#nx>w2mHl_1NWgxFIVaw%*9DK;rM6p@lG1u9PMI-e`-|}2# zw%+*`@Zjb8xA??G;++Eq9_8-9Gn1$I&ifK8d~D1IA2UWNWB+J}$L)AYPv@$snf}~9 z3HfFID&CS3*ph%P%w3H^IML~}Ar(yQ2m!xfJ1WqU0J-PMh`k5vWu%UFP-h!!7>jMJ z5PTypuus@F<=h$hs#*3jCpYzP@AzV0uEH{4MYj}9r2WI{{o$MH>AiZ`cF*N;N;*Qi& zzkSn7Hbo=1C(E&$NwjZSajNf;u5Dx8lrAl6DjE4ZiBGQ#-L`^w{P~1ZLw^J%&TPeZ1Dn#-vn1qYkII$~hmQ~E z6!Rb46w2foZdNuj*$H_oppn_*po#l0Rtb%hXBp+qmZi85lE;k53+uX$m8IUbScCF1 z2>U>u=XNPLqHbPUm&DuygYY&a% zBz%NmU}g^51%{oHl94_5-_S9_IVvh@8=M=*sd}tCjEpECI1rKBCmvwNND6B9sbGXd zoWmO?Nl+1;fBs+w$CzM*6eb=@fF$z8^%=a@%#8$me+!}2O~|z_-_ouB@${=0GC4W9 z8|Dq{ot&L1!3+Wa=2cFn`g`VRgQLrIbW;J^>qnOZVbW8WhHC{=Rq^3NL~n0z2N+I3O#6MiKsCZ_ zMFTWA`D6*-KW%NsFr)%wuE?$vm`>;c?G3B}MrVy7(sNlIByzz02rgfH8i?u!hx zB-G;4b(Qj1oKYdj;AyC*ecyirk)(8~=x3<(r)nPF&>2E2IrngcpHJ90^-g+so6;`PovmOTL+qV#yNfjPm-th<>4swZ$Q)gHSEFqloi<7zw6EM_Z zTngd;_ANFhxJK6OYa_sPe*E$!rKtNxQ+EMRqhjVP%%z!t@8mkdA|euZPc7pg96ryx z<}{*igkjCUKn!3+72jEMrJ)bF;?c^@^cgvhoa`It+p7~6_cPf$v8vj`achP8HMZdH+@aEOLf z>xH;{hev?*p`gf<=Zk+3p&!VJ%_EEFr5PU8iWHP@>XOO`n-ClBb$e&x`zeu8JZ0zO z`Ke}^DA{7|jGUM~eowSN|1hKBOoT6erY%WNlAgb|GDnS4diE(|=q+2G+p$DZPIH0x zRP5D%2ic4a8mQ|F9~wemI!r5-Sm;SNxLKED8yi+rfZYE)gBj z7a9V~{%gvey3ZV#O_uoBK9Gxgnwh5tp<@cG;vc54TQIC){d?so)zH@N6cV0|L~?d_c+RC5Og>`F$TAGj>c z&p&XQdlKObD24T>vyo~@LJi|$+hE?)!h$G{gqK-JiacbajZq|);iK5Vjo!UlKACxP&GqgK9hcjT zB7&#xYaK^^usrFi50E-{bN4OOtco3ls(uc1;fXn4sfhF1=d&WaV)Qzp&3zwRKo7Ab zkH`inwaX4Uqr@dP6~3VD;BnxoOIW%sKAwiHk~A3-h4AEE-SGK7H zza7ZPFffX6fWdPo%v3o9h`fG0w-VDZ}L2AH(Kajt`O6vbpL#;%uL4w;FasoX=OO zDC_N8c8;ucMC6?0@9_`6aOMu?$8#QARKVX$Gw|WYx$$@@nc|oKyH6r}V&s&1QuTjv zhIF;v`Tiov!!Ae4&p(LH6@Wn#ahsuDFc_m@Li`hSVw3Vwm_oyWIaQ~$E@Af#U5u~} zBBAes`A}h(rEBD2f#Bbut&?HI^DA^Wcp03p2sz3aXGo=p!S1`anbuAeF7k2CVHywyJsd zEvVj;Y^BR7DwmjjPtwOZ95ZO7Dh+Mo_ETDj{;I7EYn{q!8W|(>Sxd?5bFX-v!*73~ z2$6t+J-X<4TN|M-Eh{*}r#?dH@e|x0;a|y;L<)1EDIs^?Y2N3M5aqiPDIeIp@Lk6g zQT110C|c!LZO08&f)A#oTAx&O8=m7S;RQM})Dk|yH(HqT;9R;Dwvi`!r>&!lD%vWN z*LvK_U42-NPrnKuvF;`+dHN6M;{2fQXgM<(vKhNX0^AD-V=9wDfyb}L6BB4bj>L5t_#txz$rQ= zgHL&`2AV~AUG~Q-A^a9=L-Qcg@owgap=;vesR2*$_pDw1w#5>bnj(_3)!y+U6xn%r zI8ZCx|3K3~1&r6YPU*Izt+a;Ra^APrJbymua@l_xOGJRSb1`62sc70VsfCR#ac4dXkxO-;}7 zoZf>iGqGg4@L_FkLr>z1Ufce+JE{b2o{j@XNfkf2qKTBUvah7RfndS|<}onSP8b3~ z^Re>&9TG#0c78Vxf38l`lnZf(a%t25)n!^(?F~QdS8Hz&* zSdDnu9%SZVXK4w)hEXU&Iu%mkhYFbiMQ%vM)S z5b8CF&%4Y~-B8+wR}Uhw#<){j9anoGe_GoBsmhHsdO~k|CU5%=PY9HRwY*1|=eyG4eZf&~^&#c#1a?PLa;;B# z#>`bsivIeI{SprrIg0hPG^-kG^qp$9HKOPW^m8+ue@Kp} zVuOy%6aIwZ1wS7%KAk>C%u%oneb#RBu1lJGv9WA6_J#2@c7i2n+1G?3ibk^_OHR zM2iVWCuTP*uC9LgNu`ZAws}*ViBo?}>|E((rFyl!XoU9eyQ9z7R&tFLuzSS0+e+g+ufixjXHKpPs5PwT#x_@)3VqZUAL zEL4yUFkZh~)#N!*(MHCJy{nDO5}2ylP)isf`XGhbFM;hxhiTf6Uu}mQpZWDmDkHU& zAaxi=62gMEC+&WrDk$1l&M%)%>99%buwl&K=Et_E_gig3>WcEjeqw%7jK7CQEe0+` zqigh2^mB~{3#E}XarGbj?+DPeX2SXg5wH_q&e;9vRv>UEPCu9k;S53TB~MUz{1Uib zOwAn&eSWdjgh30oKdz-pf%k>AM!NCbU%wq73mRVt$(A#o%5@?|grhL;gYUJE{3A3w zn{j4Xd964g;6y&?Hy#YZ@Id|KaGh(|dhwSKF5+e+)RGHIaHaJqj9 z+QHqcsOnZ$*^ys5GyAAoD73erlwY#ypXj6l^9Q}vNt)tMD#-pbxitDt`&{+tAHjcT-xM8oHYf^!c z2!s0qRd1Ejm<3)ukBGVb_{>%M@=6H7-4XW`=BV`oL$IgwZT-#-TQ-okSF*O2PW8rG$ zYvgi483a)uK^RvKk21Yms_4?4XB4Xs1~mA%C=w8x_^Nq>Uzb|v_CW{Af~eI+1B_$5 z!)tU?js8v7K9Ezh@0**H3IDmzuXQCgf$3$!&c&$@pERB*&X93hBth7?38z6>gLHOl zknFmmx^Rq!yh|b1m6X>S3m37rZiDn)Che_{&xKz8Iq$g9rJEtd{NlNM%4h1|uEG}f zs$d`vFFedux$ddy+k8#(KCw*7k6+re*D`b6dj=Mug<$V#SIXgO4x=LxGn;AiC^9@x z=d&vaSvTUv=Z!aG``L3wZd5aM%qXtfZ_P*;}*p8lm9)s?I& z*6%K}?7ediv)NUC0u+RFu|Eb>NH@7+IOBq=%Tk5a%iH8G-d!upBz3GP*5b(fY+Zp( z*Gl+IWu<9SPQf^azGbKF>3u%UD`ngA;%LtOfmiq>J(EKeZ5iC_zTJ8UCcfKF4*rhsvw=MqOhys7JF|W(K#~*;aeQME zzJ(rpoYuQkRGV)p38OI&Ypj$ARH)s*v{2S4i>KlUC#bE^8Qa)k<3qEJF%-9Q?IX*I zAo%OdSN;L|U*lJCts~Z~YOYAC+VNN={|NFbsRosobzNlYk+HTv=Ayw%y+Jo6<`>I@~GfKqU`!wfPQ{e$)9kknK7BJRnAx^_)h_E%eGZ zli0&xsW(q+QdbhhX}_cYN;16Dd(~{opJSeFOR<*QI4Kv@pc3%XgJ>3E>)=9?It3w)0`AKp2L)b5Io$K1(i`> z22W;Unl@-PN^vhfm?#wg?@`0E{ZW{zuo$Xx=fdP!K&kD%5E_QdN?BTFRcZB3PS$B? zrrp}hWF^2npCnr(%h*Vox}1RQa})Wama9Sdl)!AZw{0r@jY56mQ;_JT&&91O)Y$~I zg}&*vO|Pi}$^UUnIP5IrmWHybQSK$)Je97WQCeHAw zSKfE0SfQ(vn_Y7!;CMdg?@M7OiStHn56P#NV6kJZfCgy{eM0>1cFOftzplS5yE$cl=S7U#B&R zpr&FW7t2n&aO~z!ZN9}bd`AVB9prJEOrKKnsV1(osL!sfdiv&-jQL|F{% zg{-u+VM*foJPa^V!f+18VndW_hwB%(>t|%Z~f$ zm_d-67%-ep)4^#5l3Pfjo0X33@9bXK5W8iNZ>??t@J0c&wwP-z zk<_K>1$zoJ0X?5xJYMqvdc7~Gj!+u)&qyD{Fhcr4^J$Y zuhaf9;M(Z>ZkiNy$-$~L^b!BvbiT;0&s}c^u)K)QZa!YRaeb=yD$QIj#GP{GSr5<4 z1;e22qzRkRVHM`$aVvTu;`OSoAllp7x{eNEKJ7uQm}JHA!Dcr+;To6!3@n+73Zc}r zv?A^NQu^B?go#Ql;(n>EiKsR?4}LR!=3Sf0j?PL}-qDJa652e`gvBE92OSX;MGY?D z1h?TgSlkWvhOi0a@?M@N|HYQ9MxQ^T7e;I- zXLUWeSbmvG!?|He*^j=TjSQHq$JD95Plgt+*!1Nq-|kKUa8BSJq#`u>l%J{pSQ#uNK^tfvkIiqFSLUxmE^@FF`EB>;-SQ zEMvplYpI$@Pp5|0Be(_Iz3PyFR!j%j(sb~AN9P>v>?Q%$r&-wa2-hWK?uKRzSvDIx zbEC9K)6JhmUY9Pf{OM_;BZ2dh<#N`+fZH|8g!L- z<5s4Na;XXPkQRgo&s%1Kw# zy@Rv2r=8KUr%RqxS{WMFYUSQ7DykJrktqAjaQ+{XU2ULQBbqz!b2Ccx2BemoFBXd( z@k$`bYCfx$KdXy^u?omtZy+yyT43!{(So>YI!93Os|j}>qsS-wO$sfON3(G*p$^DP zUo=gdtlTT=hPso`_+4}&n0>D*Q1f{BbYpWA zmmJS%I76=P{e`K98qH_1t+Lui&C7_M=SeM5xBvH}8KzbiE=u1;o)lLcrL9xkcLRZ8 zy1Z`kl%U}C%W~(CtNSvUDk?^f4tFz2TVA>nbu)lxKPIO*Jr(+wr^8aJzuK*pnWD41 zyk=daxn9Ka-4a|;%snbAZ{%E{i)-lX=-L+tBg##RL@ToVI0|(6vj%U_xn9>1CR}qu zp1`n$O9XMA+xv=p{rxyGs!JR%XlUnjGQElO^4OP@zyEOR9C>_DSVO2Ipk6R!s9RJ* zcu_`!89huTbI7+C{X$t^m&`hqK~ip1CLA-!632ul%+?B8M_Kl>-T0Nzn8Ox%u)zOo zIeiCm|DiSFzhNKp#-f{R2^atUw8pRGe9Rua7{-oM-xnBWHdLGf^zIA0_lL%s1gy!= zf8Je&qQNB&{snRitQgVYQWvUI-=7#1KCxP+xjsc)27?xN&{XxEV>mI^+*^%F9OqRm zUjcUziffe3)M#Sc?U8^)Mr@%-`#ksMsEmcpG}nSB+p`lK?nSow+A`fkx4op%;#+q+ z4CM5)V}W6DUaIg$Fd=Lbrdy{$*F620g`z08)c$W#Z^FDM|L5q1 z?_@7~CE$kC@(s#|pL^d*IU<#Nb=hU}#A6z(;*}r-$98WeD+3&c7RRO6($UjgDQ4qX#-hHlsBa}hrWA7CpaD;sP2D@%iD-#r;6idOz`<><)vI7;IU=%4?1u<}K3^oCb6uF=n-5RyG><*CIP{{>3WdA$2cW}Q(8W1n4m=~v@b7F@;x2&Nbg{07Qahmy=Ux6`{1Nj@*JGq~8 zwiwRTa=E3jI<(dc(V+_61FTL;U4gte5n1|hQ_W;brDKj3W$jq2CBM;Y&#HVQ6PY;HIz z=#kGsSg>+xCexkAB7PVDj`{ogRflX$j=paAiNv!StwTPaIFFt#(4u1zzeF40;jm4| z(`4Vq*rXXdCsbi>NBDxTb=B_DesaCbdFBp7g7F2WHv*%_o8v5e%FUikR(_KucRi9P z=HNr=uDttu*Je4dn(KX{SDZ--J9gjFhpsaind9SB#wC?46I*8)KFO}!nRtFUyy|ml zZeIGtG17Y2(V!GHo;nKpmfDMEeC*nXIt*>ZiHPztLX^wSF7OTUy+4d)?U$2?rxs!WM zQJ3PVa5$F$F6n=M!k5tK*_6_qbUAxLvcUMzwegOXdU0rFlwRppD@yo3yUG%-CY#7( z%2IaJruPZcL4}VVnCV-8`l-yXy}Q!6pUV7WTkdS%I57+0kuX}Z7YC`_(7kXTB!Vk+$Vu(P_PDXI+^frRlz#5vi$pwkL*~wmBMYKZCJE95JO? zgZ@{p2sba|)z6A-AClBzuigu}9g*;s>nRX%n4XE%alLEWneTRt|BKS(UeClRLgid9 zGptbiocE@jYyKtLKYE2b``leJrs@-&T#BucFfyMKr{-%D*cc4=J4y?09E@500#%Gi z>PhmVE|I@=PAB5D^5~%yKEE*zJq~3A?22c3PTQ-UvvMBu$fcm=aa>Vk@L8RsyWT0J zig=nVZ`>A@_3WC$rV;HU+Zqis?QmcF#I-oW*h@k}=giX0w(zwv66fT4S{fUqrC(;` zaAe4_d8N>km3!@;?V{V9(KDuj)V{8nM`t;h`Q#rGBCDaGCx2diL=00~h4t66W=4&Q zB;} zD>MvIm3Z~j^Fu`g<^s39&RDLQ?114;JpVc0weQ@*#5pTA&e`)vqqfVB?%(M*mx47+ z2dq{0KMavIJ7KTtEJiwUlbq&^wughK?OH=mn2IQ$mob1*_AML4LDv=yyD#JujZZ{M8(%RYVmmo3*Ml4KCop$Pt|mrrb9ImMi)@ZW--} z|MF;NHrYTs@5d*mxYdn2h}9ft@D+-@Rv3J`mQP*|lXss`^U98EZ}!^rq}A`Q(Swq&(~N)U+c!E@-sq`HN%}HZ|8bdy|1Nz7|J(0G!=4}}EGDo(e=T$44j*~G#s<#NcEY=~=z zzi#`de0Sft$+gtIi}NCtWR7mXWX{;rSp77k<|}J`P3MoXXv5<1gs#!WyxFwz-xK&9$yT$LtI0Vc)NfR%BMhSTfhz}pd;wriEa_BV3OaeGd zl3waHi<}JmDsy5}zmac%Iuu-cILtkLt_G@rHR*h|Y~`^w z!$CG#A3I{Xt-p~|Rp`06{7OCPy>trVjPz4`#LJrVYc?E?2=kgQ#7+j)cm9d5+3#U@ zG*}~*`@*{CK#~wtj>a3W`9|b5(&v;roJS><8~&~IvtJ+=t0n+cE491}!Cs$8>Js`FfJ56uW=ELd6SNyW&sQF~Ds>pA)u_qgP@ozNU z)pFTU3Qov%ehNqT9_pw3ufO{-mADWK${p$^77t4r`#b7RbZA{B8yc9b_-ruI{Wo@tv(4b2i5fR$KF`FB z)oZ*ecwLUWYO!%`3eRlYV~#1Y(3W>5xoEu`)Q7l%bd z=YGA(2OD?q(qbfHlno7c6WKA;kG*kUUo-D2$ls)WP=49wNW!!D<8SCCf8Dg}w%!+D zDQDCF)54VH!Z26qbGdCCT_>LYp>~Hj(z)WuxK@GjQnSd$8K2m1B}E^zd4P)3X~;rC zqN7#Loufrol+eJxn+ikPg23H`bh$0p{HAC@c@II^VKvWX8b`p&00FD4Xu)1b-D~+z zYJ|n6e%I2u9ltamy&V3URdRjEZ_8|{;;2q>{AJHmeV-L=Te~SG6~$G@^Cg;j2ECsD z-z#uK<+i-Myfx~5$eFfnD}`>o9O-tC@|*AG!a(VR3Wcb|B%M5Y5_Q-w{r&x4m}W7J zpSiI(+?8RGKzqXNWN62wZ9AU)xnZ}@Ff>do>_dR5w-5>0gs#My#!9Ijs*@eQawKWd z`~*sONKIp}Q+hynXAI$2;+2HKIRcgO@#CQ<+$Xfg#Q-y@Y;F#PIw}k@y9`tw>fW2Z z3WfSRR?|$TWYx1?&pR$%&JPq4bfB^nWNG0_n=;`RNLr1o-2Uw4Vt?A<1-sRex2%oQ z7V+Z74C?}(OGg)^XQz4)!dVX7OqSzd$~Y0-7O#+kikW~WVe%qqxPZx!&dPPGt*c9& z3-k1(Tw7``oCYa^fTLLEO`UO`pQu53;Pt+{-;EAaJuL2vVH)>}+qdGn51Izs{fQr5 zYG^2&F%Hy&MMQot6Qv0V7eH7lbjTA*CJ-CmiW*<|eJ|mKWx? zN3Xb@A~~o`RNQOWy|7L86W91IQseNQu$pK+&6JqClGigU33ObC%inykDx(223JwWD z%y1v-b4!gfuDX0Dpb1J!KFfNLJ~njvFzH?~{B-Gt4ar(G$?egz z|8oSd`^CsnN|byZ(g0KuK?peA^5W&oVYd&Gkk9r(mpUIt;Yf%uk-i6XQgd7k;vUqi zm92^#JeWLeDN8L2z4(69jI5+-@AoQ>cV7-uK6#@yuJU7oFDd} zIfK_lcdif@#rWoET{el_kAuQ*$Yw~|Hy7p;R$FyG8B!E-i4>_O^ekSZSQst8xAB6{ zj^Er9ggTEYRFfYz`*nb*QX(osu<9)S2~q7>26)0-%%CF8X~qaJm>NhXzeD3iFi~?* z?eq<*RICg=kgy2w@fG_y@XJ>tM25QL1_6kchy?*UlEb`Wlt^Ox&CJNa{z=-?qM`AI*G@K!hx6#OaP#fYwW+rxe!i)ABX^TK4}F1T zK&8C~DXfF8v=9bApd6=>LSeD4wR5$oW%{hJNqjLA+vJ;1exx6mt$J>YUWKdUR)l5% z6%sShG7>dZU*;kF(??w}CFQYE59P>X!CB5imGHLV{xKiO-|LBEP+uIxkGZc+)?=N91zF|1|HZ9PUbsM7LG!<+XF9X>X(qtRoFZVR1hJb4=r`t zS-l?;rpeFP^)Drwbn2UVbHa|zGN4MIGT3DSfI8tlORl>9-Ykfn-A`h8LMg~7C!ke zFbli!-5eav9^uZN1A6x=?%gZ%Uc#i_C(#b2KGK_&Mh=A5K-^mv;mqLs&U3e3Sidh) zvK$^BTYvj??L@FfMZ@}uBGl`U5TM9)ImgKAulz#y6rcQ;T{tOM`DdNQ;k#wRIPzgg zdG+1@H<{Z>Q`r@j`QE#<^Tw)YXl@DYK&Ee)Wyh8NmYW8%G`s=z`#ZW&!NUHSda}nc zI^)3iu$175KY_5x*k%K78Ec6t+Eoqh-1?)tr%SGtid*-y_le=!aIe8xpFdWivsPJm zAL5KhVR85{)LvcNBk;A^09xTVRdXg}?rrw9%LEP;3BLT|rF?9?ZqLa^#^f_z^}RaE zl#ws9)A^#u8%!Jhhj!K$l`-8JS=vn07D@c#>I=AAnbyYg;9jP*{aHOD#`Dj93d{P~ ztHQvNJf`u;>`t21^UBX>HhqMxg5U=dq)%(ZjU6N@a;9e1br9=DCM&W^qW2=Npi-R& z=KwD`eRza%rWC^FQ6D;D=!^aph^?$nuW`$D!>f$W^ppJocPYJZ?ejgl2+hFNO#C_1!fx+f5>wb#1GU70N#lWBBT=gw z9)aQ**vG-#xX?6csTs<1eHDYOX7e3?$5R{+y3LzZhUD`|XWhjcr2`k?MNke$%*F4< ze6#rtlYfTq6;0i^^*-rOcO=$-M?D7Y25vp-Kf(m03K6_z`AM-)e)9nL8vXm+d7+D` zdxRSo7hdLjr1W%MbibbQ{pET17_Vu(UvM#a6}o;2y(M+%N8;7IlSHfoE*0VSN{VWb z4UIfuMIU&dSs4T^LA(_!FGw+F-H?X3^NSWGPa|ORcglw_{LB+`J;_IJJ=| z>};=LmZeTb^umWhFuTz+P9`Wd>z9)~{FsUQ`$(Pjm{@W|@l$l{(bqC#)Cajk9ZMc`?2fb2p{1v zwv^v9)2Y@(F}7gpW)Dyd4gf)k5`F@~W^mZJ)^O-Ytgh)xretq~1@uND?J$`9q4No- z%FAr!+OBcT+dBTi2rG&FpAXIM{KS%cDl4;>>&98F*FFyHTfgSM(;GVcnCRA+ElcHJ z-*e-V=~JmZ_V3>h*2nf__4AW>{6%*dIE7VK-r$xhk9y z^6k}GZ|+K%;Guv$Pq}2eKZ%Z{UAj^TvBKI)lQ6P}4m%q+A8ZaSCK^4 z4IE5ej!mB?Qhr*=%~JecCYiKVHQc9ozU{ZTLK>=Cqfatsj6U}!&gBX(^ejSw^D05N zaN)>LqcCu$I#_y)!E2JlgGG4lQl|n+xr>t2G@!qSbrsUB>ZA21^f*Np40l38$>Ney zrKSgiYS*g?A`Tu;jzkIh`xiXqogup4o7;abx;Y5!c`nyNV*BUU(<(&8#G$#qj7xp; zH7U3mI)CCa=R52IB_jCblS1`!b*-SnM+ooQ9s#%^Vy`c2KCB(2C6!W)@)RwO9Et1_ zp;E9(X=-P-Phgpu9^r@hbFhLNsF(w1ZxNCcJL+`QQi((aEa@E0tP^%_#56A;3h5%AfxrhvQt{_E}RXZMR9!mx=tWLtM(-;_Nm z=WwP^#HltF=uZ-PPo!Qy>{)-k^j1Fuo+#PD%cZeYu!Z@6O(BZPXtoLDWIO!rj6!uT z^tRpQzi4{yK@JE_USeI9V*tb4o<=?In%K12D>tHQHFR2+*3m2<-;2_!KQP(ff^!ArFE#3#A&COIiOV_v!{~m=6xsMq z-sG@=$W4d$?5ID!^WnEM$oSAJP9H0@GJpP>$*<=0yKgT^KcC7KVI9lukGJ^qBAf`o zrJ8vk%F;IUyRHXT#Z_G%7c?B;Be+n2zVU+^R(>z=S$N&zNz%q9!3nEO?i@(bdb0JW^Dja zNr&@jGFWBPAWN}9S~UKarswJeDeXyVrrSx*+R?3#&(L!yuzL2i8&bs z2cAUGT)?tAV{b1$JUk3pdU-_6wh}W)?@*re{QVl4_WY2Hq}MXa!?XJ~X^z+SH|Yp@ zG~QCmjs0N1nNj$6P5Ta2^2uh7dkfY6C$E~a)55+G#;5@`Fsy?ioyM#62UrHK zLJukqJI$k+bo)3{=w};Zn;O@f@5qOWqEZy@mAUHv68O9W=SVar(R+TO?AmhGQL5VB z@ReGUqthI(W%Q5CYbks1Tx>AlD=I59Z2HcSh_W+qlZJGc4x$hdzyK?8Rq9k5`t>tZ zM?Yk%q&A6WMcCcz-saRlrXoa!G?kxj`#&09i19Z4wdfg?%Y`&0FJGTM=9_2Dl+*gKS*F;BCKuRY4k=V|`%-L=CWU78O5>l5~@j&62q)*Aza ze$rV>7eoql5SeZfM+XX#%rn$~s|Cf#m{3Vvmta$x3F|EV_byGul7YTBlz5w>2yp|a z;RJpXOfvV1D-2RwFoJ*Qag)f+0fPcM11LN>z(vBq^a38^pM8esr0<8SSyuzO@VD&F zL8(vP<;Q~p@tDC>C$RS=gCXa_jK&vIj^%|zSh7t&+7ZXo)m0`34DndagH2lqzkj$RH>0_2ul#wT1KIjn$A8?uA}?-` zUr?bWbi}sVSnBJ(lvn2sNmk#v+Fo5c3MNfnWl~HViY*a?3hiQM8sZszeDX~+poNEf4t@P=SBB`%sVcUs={50 zx#dq%RccDv{tYapM`>SYd;@yU=NVHHNIQlEdd#w5(Fj~-Rp3SeL_pMb3M)A?2gh*D z08M?I?YZy!XgwE(sefeqQr;_Qdr?t(ex4*MecYeTm@&@p-x3XB^qlwU*rhcplAlol$7t+unHAPzzB+U~y zko77@HR3M8uV22YE+0Av4T=S{VQ=RHdUAy}6KO`Kaeo+n&z^06#K7gNooo)x=Vrgu}s0fKMB%O}KXMnsBDSC} zw0MhkseJRy+}+ZtrlXbzZxTy!h{pOS5g{Q1G)+-vUdczTFCbtMKu8DRNgp=+%JeZK zqt59&&~OAi4kk`NqU*OxJZW5ke+;nnW178@e*CM*VTxMvADz>^?@Lj|w^z6H-gU8ViJP=VPTe!Z)8Hh4EVoyQC5Fd~^ zXD|sqqDuz2U7WwU`9}CF^-E&m?Y-a?*>t^Kg=KopYA>1NL=~BCj5n;mIH$}7rb#>p z5Hyc<>nymzIUoos;3)SF4jx}Qib72^0MZ&gerkE_@aMau1GT&7W@h>Tq8>!BzQp86 zFHpVXV%UX<7AzCoO8L5VSTed=w719U>Lj_Bxx8C}N@}p@jmyRDgt;v+`}8&-PxYOd zj--WF)6U=W*NDRa&K_9pdH$ znHU_Gbkin5lxL&e4yavm6{BG_MqoTI8$T?*Xx8p|jLln)FaIkCNx)NmRqoB61G@J- zw=MR|Zyt79=`GN`{ScGwMN=M7-K|@<2%-4$lKQC+1EZtWSPdP)WVi+~;2b(=e?X(#n zcq)JP?BiuUz`zju9rdMKXfbo4?Xyutly^aAfZY9Rs>;LpRu}wqVIq0XJDwov zd@|XJm%-f*_)Z<#y=V{Gp>#c9EBQ3gH-{Qbv|iv+i}QyfuR1pNuTJ3*(# zVv|;R3Ze)A?r5XP^b>qu@T}cKhWg3C3!?txGIH%xqu3=Txv>`lche6)0d=d+<~&mN z2SoBFA4vHm)ga-~^6{3RA`@YI9&%lud| z1mj+KdxKA;CSC!`hbZq$z~S$MrF3NY9<3Ue#$UbjjO*NAk65pVez~|k?3Cn7xQtq3 zZMYDv&8c&wM~@!ab{E|jY-dsEfnR_@*)%L|ni&p=E5WQyvuGD5CnraX5ut4Y7p(to zU{r_%@#%>g}52)j=4qaV;iyd14GiGY%*F-1yexahUzQMe&#(#EH+Fycg|_sZho0Ubo{+b7GNE zVG7ocU)4fn-OvjYZUaJ0P{(7z%^7*0lvlr<&(tt;qk4G%^L#hdJf68rvv=2zYiUk8 z^GdtO>BlY{96B~7k($UNtO6r;yF$k z?hUj7(v!26D2bsix_o$9EXBp}pdt-ywZD1HqzRxy0V`p4cXub4Aw;h;^Z*l(D~M}C znC>G&@{eeDn6e!f?4i|*-;WvISWypwkj(# zNG|hhdps9oZ-X|Zpr)C{|8Q?%mnvl5g@KO}gvTqd^1m(%#yTz{aKFV|oFM2io?0ow z9~q>00Zkr2N3tILfmz086>|3V_+``k!Ck7X`WZqCi-{b~`2+HdZ1Lq4kMnFHmVV#Z zczL@QXar|P-WSzXzNABv&ssN7>1jA0MNVQziC)3)YTtXUB=|~w&y%Qvck;RG)9_J# zotJPtzGdM8YTx=0zYrmcdVx?UFdP&5)~JF`Y|_>H^qSU*B2#3~8KKJQbH^jcbbJ(n31~e#e!hrRE$$8dl382*UcDUb20^m z+NW95N_)`vEB4ayLX+kX*W`eFCKB{8H7k0oFY4+}^sD>My?yold)vd@mYoUfYxRjB z1gZYb(Px&8IJxCSi$-NxwAxtRp&t?jw@+DL+T#D+Y1sif8K|uXGa?ivs!w3wFyVny z#z{woMiP}^&;a4C4~LbYtbrm(m@@>(O)EKN#+O&NvFZK+3glsYVxAy$829j>JmpBl zy~HDuEuljKwJSs>rXxE$$U?OK=pm0fOKxRzrRtP}2e1cPOpTO%#sCQ-SdBqJq#_U* ziS-FIM*(z(JE)!InBf!`B`DFZB=Vl5k7aHNrX1H;yTIT#uIhvRBM8d0>&IcZ>U9Vr zz%T35hWRfIxD8TTn|Kc%49LrqCT0K-mS{jihn6_=MlTiw*hPs6zE)xpaU0F>CO z>m;U?5)2`NxJbfLT%lwbx?|zssPah#Mb~7It`5~oTbTh!RkLF>vVlK3=4jAK8?Fq` z`*=E!W}G>~hK5XxYQp=|Eg(kFH4QMSv!xS&#OD(V5%?+ce@9ZGgtY?s6Z)bOo2XoK z>j$CQAalkYG@T+@gT(?YaiPjGk#R;R6LC8~c|{v=yOx{xK)hrzs(tOPI0}}s@8v~7 z#1|Y@x(L^y)AA`!F8;opqKHVF5OB00@;p_MBWhO_^5#l`JT!^fm zeHNv*^d?!rU3#@^b!W{%eo3Xe(PoCz3AbHNf54%B#g-SIjs^*qKmy}3h)8pBaWTQv zL4OdaD$d#1h#|iz+0)ZQ1X&LLmabRH9at;(T43&No*Q^EaaLpiHI5`?U=p9X0BTyl zPj_5a^Yfkk1owI{#=XELLM5TER_gC-fHy8tYaO9U`dw_JF&x^G)x3=qT z4d#G!b}ug}`@+x}9i{f<>xAV#J88-h26y}^0m4LkH$Y-yV`ITjVFD|dU>e!leuVqk zcK_2ZqBz<)IUK=iaC-CaEwu0dNh{<-^UJQiEQR3UA*)w1dY2RfP9l-A&N6Q$z^(w| z0&T#JeZ@*b`4h$FjL3ZV69x}{WTk&-MI9ehPjnv0}1wuxStB0z8_uWb){Kwz@G zmWbeOOQ!%h4=ISrrrUWP;Y-IOuU8Gazb2nt*mF-Usr^@n0^x&2z{Nw|{xm{V7uD2y zYK(mB6I)F9l3F~^ZOU)c9A<-V8QX@R+Eo@-^pZ`qOiwiicW&V2mGm0O3Q!HlJR&728L0z-mqfoCt=C$?NM@YZb z|HI7gL@N%W9Y?460~2p#evlmnu}JL;Wgu|C-#kT=TTuZp7luZILAW zh$$1f@MG$^W7;tb`XbqHC$=l}h;&Wt$taT_q;`)k_z<&!)Q#gZWAQ3S(~%;;L;#S#am@MOP|q9n$5|-Lfm%lgY8_Gc>k(RW)Kd(7fcS*(0VzE0)4=tYvNc zQ{Ac&1_P>ym?Q|1pv%ccb#)+w_wL^9=?=97&~lRBj)oD+;v`U6RV&MM)hvu!v-_NG z5y?vu_pw4Yl-%XFBLK!U9g*#A|i|c1sXLT zVBO-JAB}dTkzkc$!}?1cup6c80E!wo$lMI$32{+~ZO#gatAp5dOIKGF)?#F+^PFe( z_b(6|lmY@e2LuJNM3H*{xVr(zLYuUpkdVIQw~xhNp_U!9nMBAp^0GF1U=}wTjqMgQZ>}&r^M#B!JOzBp#46}mdL;ExPad&Emc^?Gi=}R7Vx}(r% z6WT>S&t}KF4BbdA0SDF3v%awTg!4aM!08FS5Y}Gnu@*5aaph08NTWkKB9i^u{@Nav z?`w5N>O5bI6_W;=%q5Mlij*nB|UkAWbVhhC~g z^Sn;;I1{h$;!>!d`>{k(bYi%?<6n=s?fDwiaZe7c^uV5+L6DS5_KtOOoR%fbE27KC zy3oFT`q(hxIM=i*Z%e*tlun~?A95(L#H=I|&J^yf?axxpGWaMt#ImhSs+r#EGK~;1 zaYV2>5HH-1O~eST6$t0_Y>2>Ahh3dbr_oT@#1ps+?E zU-w#$pYI=D#kk?}!?FeyQ9436DLK8g=mhZ%3_eh>=8Qt*g^V+#z6y$y1+o8UA7qkJ5IKoJ9j@A6|O`e{r-}= zSdBUc!en=o)m{a)mJH)SsbvQ=9Dqkk(Dtwll!LM}hybSu0BvwxPIl|`IXK#~n`Y7~ zs40oq{#rK!@)7bBlxPq%!IG7`t~u7b>ra2oN+nE%Z&($$96E~8HHB!P@$$%RW^~yR z1|fR)u3aS&HO#t(AKMoD{tU;iLs9kYistcD#obgPEEzR~uO+GUw_M%%(snPnI&~u6 zGen`a>aRH#Ov5Uent3R(CCJCZWHHvufI}HYJj9s5KDMwbPv-Q-NPVJO;Dc?g9u!3A z0a$(T#5mA5Q>`zqToGItjEtol-hCIbAlXlry7UB~y8ZQ_HsU_$W5SQFTL3?9MN^T4 zK5XM?Vj|7p{Sa$e-r4ruBNL9g9K#AMiC0D6no-^$J4v}b+~RnIQO=7#zWn$~M5FH` z_hzozeydYEN!=oBvo}x{y$Z3c9kCakv-OSyz_uITuK@3m&SrkjYhf5^y8~0P zwTpLPfwctv63d=YQrYj|p0&-JT!UWq&)XS8Ct``Vc!;44eJwIPN`tjg!+_!$W!O2T zf*(CowoMg4e655TqQws369Ak3(eN9y+tTn}0@j{C->E&CPJpb3f4(95?F4*gtG9+& zf6RX%AF- z)>e!=MO{C2GM*zY;q&xJwmRHnw11#XoPNW@&aMO-E2`EGPG{!jq?UJ=_u5Z%&^S_gY}&NRyd~{E#F)*)(xAmtZgyeV@yOFNhbO5POg5il{ciMZ zNV0Q@K|egA3&}bG7I*!SsEg7D`^~^W3~~QnI-juO7U$vMeuAb*NQ3dMqW{00M8?Pk zc8xHW0YZ#QbUi`)4)jwX6rTibjNrdxF}*9PdNX&zwZb{P{x?{BT~yZ`U_=c=XVmEcR=bU#A)wN#C)l+P)vbFVl{_>wpKD?Rns zBSzZ`jp`!6`lpGmTrQQ8#Y5=u9q<4 zb$g>7OAO!w$N{!JI_h^O{@t9Ub3S)|!R&Tk%TXj%p{wjw1q}d(m%aOX4=-jT0K8LQBQK@GCOB#ROX~Aj@1xsz?&A12uk_#j( z#*24au2}C7WN~$yF*)P#ytf}KmHL0txOH@YB05Qtm^e7jq6Ze|KUwsU^&$}aL{kJ% zcLT6B5j-+Ne?ET_F=L{YAWUP4t1}AxxsTkXvZs5xP(T7I4Vy2z`1)gUvdVSF_GCG`!2AHmEZ7!R0n}km0W`$}*p)P4!DkML6J^5<~ z=pH2oUE_NouLvBHft?uoUoVIw;V=>#8X8^#XM~p}jwRdN&g;&bExA2&8yqVc*F=#J z=O&A9C#@F#PF$E+bKQ&e2Nlzm9%W2c5@&I3{QuoLn~3fh1NkZ%S)g(4!aQ;e*qq`x zq69_Blcg4k5WwXwsnBhCcD4>gCRX;-4qYyC^tKa6F5%tO6nYwE>YK@*-@othWt3iC zO;VzsS*zkc>NMxRc|UMmsMD6(>yWxi!l;W2K$@ShuO(AUP=JPrv22)Ll4f(ZB#M8H zhv)8K>9727|6^kW;bSQjG|Bs6duc5Bb$unbS++@EELz_0A5Q?S5U@4o*yry?>Qvy2&Y50eiQ611fAjffT1Cbm!K3RzZ&*+@iQ!F6mO+g}IrUM>O^l zO+GjY8uLw*0IGj^ptULZezKKvf1r2*QG^02qH684%#D-k5hpbey+%g;uPN(uPZz2p z{4{vTx`X|kw{iU$CE7;7GFK#yMHCP{(C*3m3>|~~yVeR1Po@-(`fu$u#OcBbaB2B7 z^*O-3AyKjhUFOC3S5o)O>ZRD*xAH@X>%P2k-OWtaL8%&}fi7vST+#&{xgG6Ir6KG; z&zi0g(a&{g5f8pS%0TA+dC&8Q*Qf}ks%vcH$~H^`F%%1FdDcu6nWR%BCu|l)bJX*v zxTv~ObF;Oc_HYQXMh>7R%VaB6NXEQs>eara2FKi^Ds`#2-fw46=`ir*+?>4~#)l6p zVCg1X-z1x_bwPpyVgrLxuQ&ev3302t5Te&QO$D&wib45lQp(P!MQMNj3ln&nTqB-X zk1$ySEwjuoo^O5g+q|GsU0Ga--f+9A>wAe?h|7HDVRLMIwBGQA6-`lrmt|?cvIWwK zBw5FQAJdV!7fOW?clb|hBC_Lmk_GV?^AvFUF)UBw-Ve@gI_>;-7Hla7UET4q)h`y8 zB#<=8`^AbkQWAlq)YKv=p4c2WcQb3;So@Na&<8@5i=a>bFDR&(O4^Ct9D#cAr0b{O zJSbw-q7ufCEd0f_8AH;=Y0nHatez(0#AB|&n|jq8rGXA*1% zoeq;l03Jqb4ztVyt;G4i`Y-N_tSN2ketdo@)-v|hW#TYq#9`jP-n2~yVFK8NMX^O7 zn}O|=*P6PYxR_?a4XaOOYrh!8)Y%B%;^M-8TBt7o+pJ{ z*heQHSaNMx5Z>*zEHOGuOo=QNeCGgkK2?GgML|ZoR1@)Cmz4I4GPArMeDdvg#H<$a zVqJ&{#tNVYNuF})h}r%Z4-hs=K0#X~$M$d6#jcM+PjIzN7Qw{JHB^VVCf2RSIf}UF zMstFq>W;M2hh~IMpew-m3dxY#{_*?;QkjGS$#HkWvpS*b0%@mr&+ZYkVT4%2{@9*Z zZrMo-u~`X)YxuY%RLuTz_qQyU{}%v??l6KeD9HhfP4(Ky*X8L*yk2RS$ z6NhQzCr)Iy#{(4z;?;}rsdh?Ge?~2^*Mj_sv7$vrattR(Io5f zVx6ov+fk^W>tI@El>3MnjnTw-yW*U_)niCs?^F0&cb8T!T9FU7b8828HhZ-M4bU7S zmZ3Rx3aEd5$S(i6ic-%R4FowC3-gi{6n$76sw zdI-ErJMIj^)LEX8`uOo9TE%TfMcrXQ@D4U~+kZ984AC>93Qr(X@WxXk{G<-CcRTpj zYQB{C5ErPM>BlVt9RxwhL_eS!WK|c}=O&~Dt41d%797N>u2Hd5N4!d;RO?Xl*Y*u= zH1I$F+|*w{{(^ac)z8M=oXYR5Om`@cpS|!wJfY^2Sx8u7=IjZv^bx;Qm+eC80Uy8a z^4UUHN>^GWT77Sw*Iz|*r@poI!18h9C$)zQ2fsx*iO%$&tjlk{na;as&n9mMF4Ma) zdaENE3;iPQ1nm`RYw!)3SC{7%b#*)Q&2qeRW0Sm@WYS{D*RH4Ss_asE@k&P{Fp*c! z&_BR#aq6*;Po5V#TXp>QscnO10-!4IxVT-g3&}~)(gb#N=olIsXXmIw?sM~|W$Mlw z8LgsshAyHL5Cb$^_b;zs&({qEjTPz&Gy<+I3|{U?e{k-Zi9b7ga!Fc?ekixL@sU2o z!aCW^djD)=#)=NLd>v=kUAv~aSJvjx9|%p6ZlVG0+~j5wn#>deT$*qr5J)f?(9*5e~Qp(&&3kWVE)QSs&lytHMQklrj)||GAlU?B2>18u@Ls&|D>(=1xX&(~%_U(;h zKayh6)gj zn?A5jdE=vJ=iZ!e8$0_clm18ZHQo?%wbLnEJg7o8S&ipYk`_`QPhGdQ;=^@HO#5&b zL6Z}omc~Tb*kq(L@mm4WDuxp{7At(}6c6m)uXS~sNhXsRgVSAf< zq0p~Ja+ApAI>m|4Jnxj(BLX9ww>f(+^|aF5yKb*TJm0~sWY);M<39>wtYN&ugeNB< zabuENZ*rssEw@&GPKvlqZGl3esIHEYgM&j!RaMd1SrR>?`=4Z6cQMO$1DHK+WfPmS zrCvjjZehWsj}(2hfvQA<&#pC{7}8OSI^7tKD(@`dnLDU43j@=Xq`yKc_7+8tbGE&Y_e z=V>4F)~#y%fixa6eI0J6BD+!_YbBpSTeHN!qP{R+Zk6}> zXQS!Cc}DTMwHgkVzMuPV`S|z@iQ_9weoc=KS@iv>%fEhPY5tB4%M-nN8NLwxv!;3f zT~m!1>5{ijQp&?}0j6#tMNJPgflABI^M4cg4UP{V#tpOGB)w+XZ^^l`btJr)$N1cP z>rbzkZQoIzcPn#Q$7wz@Q}AYL=ePQfHl^gREO!=@lVqH2>25Zq>`;SrM4mXom*=+w z(r9?gRPVpy_Eq8eJ9hOT!{AjJ;ph6p@}0|y^74&M?4)%Zcaa0M0yIKpkMr5cue_f6TRlQrc#NJUpq;o2wosAO!ziw*Br{2)E1 z9O{4IGP~x8wtVQ3ylYZl{?!&O;`g=sq}>V6O*li{{4VbANea34BTa`L!3CCM>5 z-yPquEF~#9G#yzzZ@kxiZS?U?lK`WCG&7Y34|iR!KZ5BzLZXr}z5J%wQ!9kU_9dm- z=>o2kPl^qTV;I@UNxF`^xu;eB?ItG8;G}j~TVvxg+qR$amt)6kI}3;LcABLB_ZZL1 zO;KLk&{oLBv+82}x63bNTJw@398vx^jk6}r-% z=&k*B&SP&HTjj@1s1pakWP z6!N|xSX_}?8aqASvigu1QM2qM8u5rU)zw41=QiDz+H4WIzy4;^#0<$JRN#cqpH4nu zD}Le%87O#rOrLMf6cBpGr8zf#&Wo(h@&tWI`6ET<(y5iQ1!2=Y#MfwXBQEPpid0!< zxmnsrXTL5iZ2xrT@S_Tp%dicxak&a;T!>wd0e~m@21ucd) z>}&YNC)~)$bIac|CNOV{_BmW(N(pJGzd*=pY;}~4oAjn5_g2?;^&Qdc|GILll>@;A zG_SdETGQjB5V01^3zw0G%8yWOvm8;zlr2*leCsBrZQ;0xD(gs%``ok~C*6#;J9}sS zEjW#lY%8LhF>^CCMWS}OS*np|t?JAAzQ*tan$yFDHpf!Q551$*9tbS@(b6q!xp8-# zxbmOP5jL4s)J3=sLDLIgSE_GE7QU5Z^rDLxWUMSJn@q73Ach(lm5hjCdYkoI`7I3^Q0m0;-(pjI;$ho| z_4%s@quayjl`SZ4Hl0YjdxLiAWcP~64Pp+u;TK8@0W^x!LKm&FiZ%GkJvZ~nmOiV(T5ve(6&l6T9e1>=&op;$3o_Ggt=CCE2`*VNgoYR`SnVZWP5J zy5kPxF9+JjXD?ptl9JjX_?#B<#-je}&~zkl)Jt^~=WHbSC`W3<8($`iifdkM)?Z!w z8{qy+V)b@bv3X`}r@4Y>6`L%{#kR_3@eIB2^=AI{w`BC{5vw_ZddCO+{mWOpo#R#6 zHD-BXSKq>-nh7itpQo%BkSmvUgW(=N~e`oT;4hA#BQ?zP`RR<#*@$zSox)zV5#G_07evuZLoTiWP;ubOgL)1@GhkmxR3n zSLR|0XgNyApIuz6;-YfJ;kS};Gn3@xP-`--c~Z1nQz?_a%fvo0z2_W#_xi^<0$L7`0fgfNbA;<=iV?2KCkM* z{x5&05Z50T988w1?uSWJ-H~gjbm2l7hHGS}H-_BTZBFte ze>4t;k@}c^hdA$n19ZU1l*6M;M-IhB`TBJ(2&&aIGzR~j#PQ{$l~DdRVd zq+`d}A?jgBZE9|g&&gp&9Us!fcTHoy)Q`?m)6zbGK&M}ySRW}13r`#%b(*b^VZMG| zpImO26DHe+y9=ISC&5_u$-|~X{5A9j2}!?Q(}(Chh!g5QA`2oev|5xzJPRidDj9sb zON8ISfnvf~+0JBi)>$H(n9z|;|MJIc%x;L1>}8de=}Ele;=gJR5-Rh#_wU}FMw`no z5k0Irv?<$=tAloDD?2+iY?YqAp;>2mnsJ{#HJXLK9u{^K{>&KdH}P;VZn-SQhy&AFzWABdUFYlK6Az#k!)Ij^@ZmDetGDmqp)P1w#!<$qw&}t;wEnX z-syA%KD5tS?O z74Ul$k-HZ|2%nOYGUv-R?gY3=%kzJ|&%_r)&n#xqcI2z!A#cv4CSUY9CVWsIe}AIw z@K$E#pA($6Ps(o=Yg^@S%4qe^G;0=jxrd`2ySH=%`J+j6NZyWyt6cA6vyeI->&)MQ z30sarVf40pW^@#;ehGTmptortGM}-kF(>iOU#;fiu8_kYbC}p^c!=X^NJ#LD7r#CT zW066=^r4P$C34qKUcY|L(8NSGMs{aMe7(<9U!?(rYKf_-m2kj_zEUPfI2|Nv;^E;@ zp)Ff+YliU+QT9o6pxuQK1L!uo2ANt@Ee3%%7N`3~IRh5PGU`N4e()j({VC~DWVZ9H zDbZsV9-Ul9Gf{_QXk;Xt+T4efaxrQVpayA};5607lFiJ_oQA3zYQ9OdXSs<)CBxB; zHhZ;^Gy!KGB8kC@>>j*!QwRFYT61y!g9qtB$3BfAg=XtskUiX}jXch97t;!rA=?On zO?9Y<0rEpF1@~OOnE8xR=9VKWbFieO#1n3-EH&;!9*yeCAe!vxI8L zgj~j0siiorIB_;$*_D-*YB;u|z-ci0anh9V&?vI9!w=qQ?Ke84W8i`YO%M&EkD$S1vb^=E06gB#n*q zvM}x&6d{J7@gtTPqafwE7`AL(-=1h-WRwjDmf_;=Tni?Ss@h5>Aez~{zP{cPT2DXB zjD>7r2b|)!UDRcmtuH@dSSgSKgw1e8JN@|9kq1ipJXa@Y=d@nSzFX6x+X}=|z_&iX zK)QmPT|eBafFptcS(=D?)*@3DR?fyD5tV3#%;mLceeTj(d0k!IsD%kPeD&fp^O-DT z>b26+zxf~Z@Gu~_B*QqRdChK)A}AOeAJ>P~TaYh&UvM(~sHf*?sb_pMh!2{PksSEZ zx)Wj3etiQ2VhpTzA7qKntHeR{Qwv)FP&}n=`2+UH^`++*7K->Kw~FX7f8ngWO-5wH zQz#VzzUNT(C|SnG$4`RT!1d<%_P)6Kx(jXQYF)Rx6St*p#Gl$36sk!^Oa8Xo20aA=ZS+8w) zC7++}L`z18rNC#r0UvL;@9G6~++GjYD;$`b9_9GhX}Hzc`ZBBQhQdj4j0GeriNwQ> zj%1`8SjD6R?hORny+`AnD;yn>fO%K0kexz2rYF#0_?-=(nLzM-OZj&7(d0#7iyBTD zLHKb2A`}RCP|?hc#ih1_!!ZF^K8qtlR@CFUvREwQr@2#R#>VG5kJSx+ z%6YRo}{YOIXHEaHWDk z_xu=QP+NA&<{)#rSE!d$s>%bF00<_i-lq*LQY((8hxwYJB800mAc|J>HR>=F>5JkYWC|_2nMUN&y+K`azv+v$% z;6J%JNTSo&yBu@BHvBV9EG{kvV_E>s%*@@?|E~9204j=50irugruc_f_xidTQ05kj z-}_a0*S4%LzY2ICT2ng|9=!B=h-PB)B}wK7V>PY?{51)@;oZZQefB$K9Q4n}!N}ej zlf?idQ*qO(fgM)ry=>#lWUqolNJAxr+(*sJ%cJS(IgqTbk|j9+ifjzFx3{Z6i&u`a z313ZZnqM;Tjj1|0Qm@3bvJHB&HY|@boFMVS$nsUtS7|jhHF4rhqgHr8lD`9d+K2p} z?}~%9CQi=C@1gZ#ocX&zNDO=TwC{RLe*>rYq;uXFt^Tm6A0iwbH;{;=fDNW;>5zTt zzTy#aQ*KvZ4lHj@M#ArvymX!ZcBfzGa;{uLZFl=uan^1mLW$%I5N_R*4O+^3->Rf5 zZV^^ZUqa)Ib!VXHYfL&znQCFs8^sQ)Z6{&)FxH{ZYJb2hvBPQhm%T1*t4SK@q!(Hu~uJ9oA? zIlZIez46~;pU8M2n<{mzZVLjSys8Re@-h6v)?)Of6=j*(4}`B4v2zndc3TQGSo|;> zRbI9QLE$}E#Td6&?5TMwuXKEdjF^ zsp{&qUAritJs#iuPAy6DT=)5L#%f-ZoVmTd&UVi#R8ew~6A!oGrAI?Tf^ZVBJo)n_ zt&3~88;(FN&=XpZz0(vhSO&~lMQ$@caNFZi>Ww|BsHh0ED&Q3sDiR1Zl6jZiq}dnD zVY7Fv&t@t%15vbw4FIml~~LpK7mXoUwWBGBCn|ENih51B-|B#2~dwnkVNWc zw+Y3k(i|Vj%%pJJV-Q5`KU;4413+sF3_{Oi|E7KNNk@|HAYwjfYz8$Jb`mb2_L~V+ zhDPp%k#R}*6VN~F!zs1@L@Kxa`iIXb!od(JgaPTiAGH&pDkN+TFdR|@1Q^dzIXOcZ zV6uHXQrj$06*1f>Tfp70yuG;~(*vi6>&b0S>mp}e5|6P#T3&p=-!MW?5OiOb%qH3= zE_2Hd8(_$ikfIu&3w_ZHRE-Mr^Ye)QWB~S>&^vA*ARW{qfxWJ)d$Wg!eaPb~lvvP& z?-bx%4iJzYovuk@sU%aEIOC5a66ola^`(`x>Cy;b=WKO^?juez9#6_Q3WY**)UXJ~ zktc5Yv`}mR4P;;9Uk@?bDpaa8aQs;7RBkyl?xWlf&oct7#D96N`Ty@q^34(k%lBc) TR_lYc1b)77c6Z`C2B!QI0v;Hr literal 0 HcmV?d00001 diff --git a/training_rewards_margins.png b/training_rewards_margins.png new file mode 100644 index 0000000000000000000000000000000000000000..e9fa25cccf7bb7af0434ff3e74d529857c294dc8 GIT binary patch literal 45376 zcmeFZWkXeK)Gj>fPU#K_0SRfO1O+4nQIKvy>6R3bZVM!&#Go4~=~7ZeBqaruMpE*O zxu55p&+iX-Kd5UHbKUcvu+-Z1dI<6`Ui$kP2jqGjpn>geL>_|S^Y`@Xx!LlZ zZH6!C5@1u>|HjDIrMjj=PX3IW!<)R+{dUl(x6^^ujok^IYvfls3>4GYFu(cpG>)zZ zE**5+@{F%>kAJ`Et1#G}o0^d!E!r?1=rQdv&1qqnjKdyAu7v+bI4nRi7+$c4RS6Ix z1n3uK=>Go~|DQLZ(4gE3Ct1+6XL2X{L#}F~)yd(ul-CN?jMiMg$Dmx~@kT@9rtSBY zm61Y&de2MTT4`b13*DiXbWQ2s-+XFRahmgTSU=lN460fg{66W@%)I$&=hh3>gX7KS z?vsBzB9?8~pHBYv?)jCBJ9ZszFKmz8GasohW=~u7OIN;Q>S64n?9>q;nJu3zWKN3s ztQOa#Egp6!vPPPfF0cRVxZ~y~;=Mi*UQtnj%es&g$)fa1&~&Tgg0`4tuhBsMoe!>i zD|$`ow{!pgb$|Q*y;Wa|h|jNQs%%N>?Bw`|&ia*nmoIl_JerPP&h#hcREgUUZ>aE|kbv1Iy1BVI=i~8pZ^y}xBn^)?Rs8&9WV}|whH_P{ z_t(bB2?IB^xAp?M6PQEC9i5*$IFkAwY}~N1vB^!?Uay&%j}>ZaNmMw)&(VnzYCfU# zSRUw1cWH{AZuB2LKJ;#2Ztz}jgDr6Qsc+0^|BY&NQg@|(DdAhhL{&br_4yfRzu$>o zp?<4#&CY(nx80c7*zF-z);YN9Y{MmzeYkwv1F^q9;}}lQjyHMXzM9WZU3S;TUu-T_ zMP&t@(ZgywN6mx!AKhVC&pJQhNnnwS`SOCtx+98$mzTFCP26Fthre_dexwuLtu7GO zLs+aItIFbw9ZM_J^-kkendcwfBC|$@=JT_wC#R?By8+CtJXrylbtVHiX68Ys;zxU{ zk=-o*aWxWEc!c4Y=+D)At#&=SV^l0bjY!m-ogVKT!QwwUP2$2f7(3U6Z@w2Zm}v_9 z=d4uh?(U8tt*x!HHE$Ok$18B)DLB%Oo(u+^4KK*p_N9c3jTxM*nxD79mesAhxw(y1 zJ-lFLWmW5xpPx@B=O<*B-gO-OZYtosC?&bjjyrySv>jbYb9adWDws9c&)C2qZz3MnfSmfiiTY*zZhlFo7Z6Mgf^Um`*x zA__*vSYww)>KEKvf5#s6CSOK(9uo@-L+TDQ>*GWA$A@!xYd;%k%^&~cGDz-(W!EmB z?+$CD53A2sbfb2Gv@hf8=z_T4QmP&Fo)AR+9i^QAe#e^|u~TOgMSdk%c%&8!UGcnv zf?co{+!kq@*>*C8>$h%^`WaC8>)%{B}|H>~O&>aaqH7 z+IN|G<0xE-{mGLj!j5CYQ&0~kWW&8e&2jCKWY+MeSxmEM-2xWo=Q7BCcw`+>oS2@5=M#H4_S{f+l5oa z9#Ya=HoChY9rSOJHsJj9;B#-UvVj5J`&$_?e}+H!6UQI!jhb85Ou7Mv&v!&$@cH|N z$L-HIF12^M8=`yhlGDL=`8snGC-fN~l0feMal>Hl}eUMvU;FPzy zM?*`CqOH&FkSdDHpHBBD)wH!$b#*C|FB?bH*4EfYtVVXNsJ^cl>&PPfuH!WqVn`KljfzSJ2yp4n_Ly+qbVZF6Koh zb(9zw81ePCE&;wX;x!V(Gsl1roDvc=<>loDb?#jHB_`4Ldz0M~S>*%hR1;ayW3a60HnS40P0T1k?DALhiEM9WUI3s!geLfN!2fW|lIf~9@y_yK zu%Du ziE1L#de6C!bsL*KN&MwL+g7|u>QnB$mklayNoo>XEm~mrP{5PjYQg$F)2sk^6bXHl ziiXDOYxcFVGD|G<0YQN*q}pY+LWlX|mZ2^G?;^U0U%zaog3eEWkCw8^AI@T(EGwM5 zO%6IrSVMQLUH>>)>qJja4~wCl4m>bL`)Q?Zzmlh?m~-Qv{t18u+Ud*g_tK!S6&)R& zBI&{+e}3XovjE*bso@7Tzy5#Q;5Lt~tE=mJcH*1pQ4Ea<#T>Na0J@L?veq2sNDdwz zJUEBSCMHbiF@~06F_8N%@lAHc0`P~m*d zn@lC1Ask*Y0eH4R>65dtB+!f6ewQw{h3ott{y;{`EE6_fX=e>ZeF!J>YpJ;c^n3(i z3EaIs<+Bh!bzW*xSJ5@CZ$9b1(=XX@+LXW~P3iEXsP*?yZryRUcT85XO`gL_LMaIj%_+XIn ze~^M!&;&oiQrKl$)}+Ck1TaX|*;#O-epS$*Sidh_lFZlFmrmTC>LBg=fywmA$IP41W*#$!;*mw@7k0LV6a7cz_9qx`wf9(r>_OMOq$Hc*`}fyPeZHg$3JMBwGmQ}s-v+#(vwu89!GViO_ont0piA*nMvooL z1ZCYfOg3%szDyL{=)OqUTOrT@`=rlCUiN6p4ezQ|2mXfdqn}>1jI^}(?EC?*z8wAg zS56uk3cuFqI)_OV93LBNO@bS0%t$L_*4JZmMS`Ed*U4X9oscN_XQdrkjcKudZ}uGBge>K9vKl#$8pKAmiW-e3)su}2=@!g&(<$=fh_njmd zYZ|k&gZB;&>|6j!5?A|rdkeRH;vW+ARyYD*Cki%&X53pba7;%*(K`M3c-{G!S=Q$% z4hnY3_YIdfjnK8eeS7hT&6T?KtKMq{5?oyGrk#u{YzQWyCDb@gn{m2K2GmI;do?vt zMu(jOm#cHSfB$}wiJ+bT{@RzvaB`-+<5k-ElGOL3c`_e-tut8~%oz3_^ zz4$TU^N6o3Jo}q3xXY2TjH{1+)CC0&F4vQp2ks?J?&Goe1ShFobZ(v$cVk`vKJn|L zVX^)`w9O(#HjAvsM-OXGOU;`Hpp5o`<_n=u9grHf#K-%$S|WjR!bLXFeG z#!mrcfAN*M_v8UISSyTL)5sC~`&d|5bvw0h-@Yw_C+9J_q)MHZN?9dvmN1$Ea$ARZ-m4gPzTJ!}T2G9QKiP_cT60WLL7De;0 zu&`P$YmJMP$iU0Fd**@RaP-{n^O-b80u&bR)B>S#&esf441UI`>VE0Zd!I8<6SsAB zp8(V}$VqZ>g=;h(wN1*QY%5GDM>QrJ`Z1l9E89oMaZJR7@exp=7U^0AE-oBYdO>f< z9{$r(Apjj^(OVADF))Z4HS;GuLAZKNTKfoP`3jHu9yED zX}>)J*WHFTG5>MWxjl^F0@~?wva?%Oj~~vpg*%UW{`ySu>({SY;I3X8{+_EpNZKPv zc6=Udf!-2vnh>jT%2kPX_cyQ81)j8x)6?5qw{BHV_xSN+ah79fD6rU$z=NONBos*S z)|PAEYv~Kkr~8b=xS@ki#oER|$e}0_QQ3YR*a+;Gor2_YZCs5wg*I{_)e_$x(eC5Qc2ku@&Oo=$F>F&+(A53|WL0KP2A)vNcd4+^r zw*2!i`8X&CmW)NUC!x`!`Qt6HQSiLnIhrDu)py$ z7JLNjo|l)lc6Jsp>CJmSdTvaOTN|sXMU8G8M##@lU({oMad+?E$ne$bjKU+iTE9I$ z&>#owJrx26LYFVcr&}_B>H<_+8!N{GxFvsle)>o=MHoYJ+J_UKDJ+_tmNv4jO{oUi z0uipJrF8=s4~>vn+~J`QP;B(~U`ac*-2?;#&I(WuFJHd&aXk1aG<)*gyw;Wd`HL4r z#m16xEOHFPAG9B7$Xy{0b(;J**NVrw>z7q9V>eoR(Ph#w`35*HZ{EB?5JpMoj!(Wj z!v6b?XtM=f16s#tyOUP#iK)w|&ZxusssW$NAQ=Hch)QnAh<*57z8e6o+igTbvw%fi zpc`UBu<)#4Whn|l^6>r+vL6fM^@dLbp__&ObO!3;+-N)YZz36-7)Ildj;((ed)<03 z*R;&cu!3ql-e33d7y1d3%b?nx`bVjGB3KcWxS<%R5dq|^Kd`o;r_6Dz38(Is zH)GwnaRYg6Z4^nyx^ZXn?CjX(*W#l1p~mE>1J>*w*{j)E3t{4g?W-(IOns)>$^$qp zPLAVnlPIT~@)|V-p>ZH{br%kE=gy!);(vZt<3Z-6^`Ad~fXv=2K4=@=>Fn(EeLb^x zb@9lgXf*&R4vY1TQnNTCy9b~f8R!# z_Tlf`#HpAHzvDM0(S!qh7h4+-fg8?jYZk`(HR{rr_ zB~=q#pWk~jjZW#pmY7#WMcqLBocvqPI)p#}DQoZ>rf7$NPTkhg35Nas>A+af%v~b% zJ?-PYz+&(%q)|$J2weH+e&GJNU1Mh9(VoPJgX!>bfuBD}K0^WXCMJ{!f*y%3Z9ZcF ziqb}=a1wm!&U+s@Zzrek_SMeE-&IYW>U_32B%CI~fO@?sJSLFhaT{}#sIlha;<5x@ zatK@VA5Oy}!f$a5jrb2wM@NT`X6@FEK+x*{_VyNc z-Zm{4+!B1XfSNW?y0NccGj()z)ytg$_E?Ws+)uf3pRnod$f3r}szv&t3uq~?%anJYN}Ib~1L#if?M#G*U_@M7St#HpV`w=Qvmiy6-g8)c9p$gv!L67Y@x5 z?g&U0>qxA%oi5EK_kek|wOIb5_opv+bNboUNwPQgis zvwtlhKo*oTQzj*NEO7AYWPMyi2PJ`%2Y?d9Cm|{JO6kwO7P^Jn z!=N&py#&cvWIyjs-Tiq0&!`og<+_g;1LM1(+ol}9Lnr3o7!6_Q6b>lo(f`V~u>|(46gVv*&CPo09I(bs_+j3UW z^s*a?xbIdg9tA6FqVLX}vSb4isUn^KS_~iz1aOTKCZT~uBNQJYGO4mmJ13zp9 z(2Od#ZY4~vjlfRTm=!)k59|l+EN}jtN|zaV=j8XXASoS68<)Ht3rAv3P6DpqxZxI5 zF1{37F9^Tf1&2E3`EyDn_=`=OGMU^j@sUj}O-*9kf!EPMZDual2JMa9OFt=X20<_f zyXbbDaY;ZRY}~O#JUBKXq3gA@#}*s{i}SP7sr^LxBYeGtp!xO$bbwCSi|&O)8?zBW8^0iMhnic6woWyR6f)+P)BJCRBw5E~cQ3aA1;DX9wBdO#gRVc}sB z5%X|NypMaO!BSU_AP(ub^+?yvN=u6g4n_dF6OpaCNY<{Zhr_~mE(OQH$MgZyCP`z zY0MF07Iqe|&LjcEp%oZjzkd`na%*Rrls@SPhg2kjgfW6$IRdp6(C=VlVyGmt{LCAz zuLtP^j(Ms->$~^w-#pr!Mj_uUV7t>O>loH()fGoiC+W;|w7(t;J0`n7X6-W7ju~ z?Pk+4IWR1R!bbc==>8B13aYwH;*vQ#H0-^T|s7b-h z93RQzhkt(9tuPgXm9EJRd>fB663eJKIo)9X=%59Q?C`sU`QS1o)DIvChqN?3Z2q+x z=bvmZzLa^b{!lqB$-B#kI{pA6zsDOE=xWG}r;!T~AU_J-LqR40R0+D1!BUjY|6w zKGaI)<>UK%_ypCFpjt%0gQ+2_EGiN}_3gq$MP;Si_WX@Fa4@f=_N||QWfW#sstWve zc5^ckTs|dO=i$~|b!K6~>S!saq$KUnhDWMCK2pxjr{1sS0~w%KF7HbR9*M=NDOoN0 z6L>pA$Z6=0XDygmHdp8YCa@q+W%J32cpCqFu+ z$of`v?~t;}6X)Mu+4GpPubu}>pPVopHPt(;%DY$p_+_B!YM`M0jQ%~wfW~R48DN_8 zs6OFLlzkExM+_3<4HQ*%3BAd1V}2=gm$&cUvGelcgQ@Pk$?kH{3LYxkQkD047CS-E<`O6xbb=%9ruAMq8=~A*v6hM zK^|2(e!|}=sy;Y4-+7@p(I9F!kPVx+Is(jV$|pLlCzV_qdP%bbbJ!#Ulp;ZDYO0CM zPv;uz&KT;?U%uqK5y-Z&!t+7WhWKUM1nRENx^)!gAB)*LHNaIqS+M>Hhj zzgNP>&5a9i^hE7q8^~p2M-yd#9WNR$2Wm>nCy?h@f)^7N8`};*)FMnQ5Bnf7be6!) z%Ns?L%%k-NjHLj{9KEX6bTCrL9zJ|ny-^8#+K9)HeC9S`Ej1s+>A(*_F+r2tI(wBZT8h~^78OuU!koUM_#_Dj^4-{q%0MR3Jwr-SBR>b(v{OvlyZWvb6itV z!G+}Fm%H?g76)89K;$gpi*TjQmvT?UJaVcl)hX2T@Dw1By0O=do-XM4Hvj zg{}mP5V`q6B)$Lh;GoO?@|Ld&x^Z&Z$WyUYf(zVioSeDiS?G2>?aD!(`ap&%>|D1< z1A(nI7+8>&#ZNAv5(PkT3yz-U=cnvZ2?^+Q2t>1q(5z|#YapwJ%FltLm?9r2gPIke zKdWtQuMD~|`$IfMchy^f^1=m(?uc#d>^zQN%Xkrj-w6`sItZVxMAk&Ku2VN~*~7$| zcdf7le?9!?tP-!jOJlH3Jk!sn71h&HCESp^7!=aMF|%;8yX%SSWFJWUwtpDA%z=N0 zQUs`FnB^fvgi|$9)SQNSgHKSwQHhDF5Y<9Zv6}4N2r&?v>wU=dBZN_dR&-q9t1?-u zg|O@KUG0(jgwuhmn-(JldeHrRe&V`Z3!#Xm0*|UDKdvZ9cEDj0d9-0N1xd=(M-*74q-uw{xx=0&+g9k~8sNra zsT4A+KV1Fi=S_r==zHc^2CplvCa9>z`a^=h4XW81ws6F#U z*nn^H-WwNFCr%Po3^q4WpDl}kqdy;j<(^@Hvkm6~4*b~soP#((Zv?39 zl=q|)8cWK4Yunp{j8yp|B|C80v$L~9n5=^2@Vg503v#8yc|ye0gFj~1mc@8sV9CNF zU-#_Y)PwL`t2V-ilh{QL7S#EY#rj0mMkMhnp@6wH-7x+F9OCKIr?bO8bw48R8@^0R zYMq&x;j|D<@BeCFjZa4QXwtddK*!81Au0;LW*w%&V9Eo`eV^rwN3a3*5bO4@dVFG@ zbgs#*t%VGW!ntyg7#9mT=u34jpsKJbFpJ~hq;bc7wN!-tt=E`GIk_)`s7(Ii=iwBJ zqURP?o3{caiI8lOiLISfS+(n!_&AsbYsAhg)FCB?M z^ItE1(Ywgf%8CGONeo^Mr!`ab^_4z3IdMHXbVE-i@V=65>FI=ZzGL0S-C*^1pgXaV z!{cL*R&y;U0L~wu#R)D7cKq|zx2ifJI!K&Q??rS?9m1o#+neHW~(cO}n;gHC|-+2uSt%DC_#7g-2JsTFaTtBFEDcVkKgbm_& zzZn|oA$iYllUevHU$Xed!F$LVMy_45TWY`?d{^LlO0$QfsY5FMd>Y0Y&jn6{MPkIu z_Nsuls*^US)Bp5Hd~HqYKjz`z4Q+d=5t`Lv3!_#?W4TwDG}iOW zJ+sNWqh38Mw)b`PIiFgxF+FzRc`4wSg81WJjfr{uD;=Z>hG!UTV$m19> z>a%7r7{m$Ys99&HzGTmUH}>&1qBarN*QW`FeaNOQFpd`%h94`4<2vL%7iePb&?5Er zi2gbTHeWYJ^46HdH=im>{Ov7pXDuPu0Q^9YGw@>!so`Qq3C9*l;m~Hx&dG@d21A?N z!BnWjXo)4v$no;?{};SL&RoZQ2Ut5O?aqHY%M=U@F=)~Np4YB#7C@QB-pU9JXqg!8 zCmTD@Wv0J)5gN}Z$pJ1sT%{eZi1jS*FV=`{KDQ(J2&UXFgD8~A$Gpgo(G6n3$j&0B%~|l`h|1xRD}G)dNtmN&i&-hKT7K*5 zL&iM3r?rMKpS9GV9@)~O2wYm2pa3@_6qrXg><{ufWC3Or zU;+t1D%dV7kOt=a780Dw4NxJA4iJH`dXkmJ3i(Pr%EzbVWim)nR}Q9;P-zZg&-(1- zU%y`|0sDGydEAu~9}Ya*beBRKS1yaUO8DU$*IpLll}$Ye?Qa!xQV#s(M9el@q{mAm z<3Me%B}VbK_zg=7O-F@*|#XT4V~FdGa6o#xv0lLOfcb8r~QQ?-jeYvtXpE8j0= z?GuoZb%Xxg2A`{5s}B{!z#>sT0h|p{1V)PHXW|Y&5Leu4zeX0-1f~#!wSeA425~|( z0|AzU4&FgK$3no8!GcHBJLb1bVESgz#` zzPovfh16Zg&Nsj>%m^8p4>lUFI2HHC!>a7p!}{772$pv%-z7pXnwN9}I{aLhCnUa! z0hzwWosK1!^>ccDS?+wk-7ei&RJG~fcKvlF#llhniW@_0AgAf&_zLcW3t457Mf zYnH<#wCTDmF!jhZGh~v8){t394%$>%1H)jT3+%R|Ds3&W4^XNCjvKfLFm6UpMHL1i z3O(p%)JQQ%#`%xy!-+t-V+1L4Plh>1{s~*UxC0HU7_uJpdyg>>1eCOP|K&~UZSg%1 z&{w}PfPA%$WVp;|Q)iFF+`#G!)vzu^McC-mxO7&IVfWgW~=kdhi(ml_G;4)Y`?F$}F)3Bw=#6deovJ4>{D*Z^#8-R%54_JBgLtaW^ynvgj_m_x+B~O8y5Oefe8yv4rU85Vea1)$h&0Yk-{V=g0dtHe$a6!pP6) zi@mc%S@kmdhh{Ysa3%NRW_vOY-`L-z3Qep&E)c@Hmr-HW5FLqpP0B2hKO5|Yy3HHXbd*tb9yTrSdI#xn#z7#&Fd`}ePk=>hl<<-R+% zCe4qTgFRF>03_pK(A%T&QPbK5CMM$CA^gg^$0OTdha^JAYY7qEltl7X?%v~#Y7RLAn$MRcM^=6HVmXfMl_DG} z)U@P+OOWJ57RAOwY)ulUJ6}3<)WR(cv%inY?jhnTjD%ITSv(_8k8)TP=V1>;edeQi z&}>zTi4^r6U_eqOH$fUaVstc(PV50W_^I*Gj6e|1gTyEul}F8Dh;z`dgI`jc6q4U> z`simk5D=@szrLU@7_c9hHh2i0CoX&y7lB!0T6A3a=wLGuDq{{PhKXMa`M1AfDvW2h zgl@RMZPvcPS5R;CoA~6fxUDC_&dxtyqsn-VnPf&Md4<8&GG0mOJ4KrUv-P?ymlcLT zzNc@|3(vFp{4q`EO%2DCx!J;F60d5tM2&wk7a#rY4zA7SR(Pz6(#{>Qx#v++8YBUH z-~f#s*sffmM4qOl_4F5c(L=#b`>kHCaY7wIn0`E{RAg&;W&SuCoi-LfgS#Y2)zmKy zq$0$D0~`s*JSQ(NDm_@YQ47o$w7|i28+7sqgMAxDb{1fw7(#eDVGG2{+Pbd$1_uQU z+IKM@|8GPK*};#fhMV{g@ssbnZTS(Xljs|)Yc^skW{h{?xENJ#USmS29`IEXF}&Cu zyew+eS~fs%!5fb#He>tJ<(|t}Jo&zq_$}Im2Ik##iY=+Q1A?MCwW(bgD|}`O=SCBX z3<(>2+vF4!A>b4HIclq^ZSf|&hNb`>ca77RFJHi9+V^=3v+MB8n~erdN9BRp!sPIC z)rJB>Qqp~yX(2v7LTF{B+hc%%=)BORiUY=lZ@WFj`iH%p;<#$Bh<164>F#_G83+Cv zASnLaR6n(TByDYv@2*L9F|o}q%~d91qGx3r%k|%y=gzKBtq1_qqAMcJqZY>t28cE8 zESgL6Ly}}~VdgtP?-9@^`5vS-s~bwqbEWsIB=^(8N5A9w@%LWcNljf+v_?NNRF%S! zfzzDX-@WgFW7h2r2l#c5AReODIZ&DxryDxhUCMw=(EnJTjlOUA%b{QIF>aOoK4!gb zTg1_qT0PMf^+^W)5>o*x*HOcaPgaysodYdH!Kq(J7A*`?iUt^h#pAWHgV~a(FhfKY z_r$gOD+JDN@m~x1@q{0zp5efnj>fN&A9>qUu%w7OFHdO}82I7-x4IWO#tMtw-DGo_ zyzyem6)xd+UF{CMpUe;_^KpD>Hu=^Ijo0QbP47c`<0QZ(=-|MRY#$jFD|5hgjmmn- zpJp;DrFe&V;T*9;ey?0~in)O;rjiav!NiNWQwf7M%#V|TfFjRzf8gH)QHq|uQhv?` zRpZbS(vHbtxqglJq11mLqpC_N2+@q5jyb&-TUYNdy~u5o%)m~LD9hk+%IIJ``@v8I$^#+)Ghnv6-9b3uLDfmBF?kqVFzpJ5p4xz(hw7+I1%rg zZ?E|l7hFM#8l6ZZZj|--mc|7B#`pw{e%dioQy@$cbh~4GNHKrje(tVIV&pzmI`Fc9=&qF`IV zY;kAJTvZQ@D0tl%(UgEuRD@yRA3RKT;aZ&j)hqm%52DqAbwf!aht(aXW~e{uXJPbJ z2!O4$eKuW~@~_qW_gPT0)tsH`)^I-4iB~mUgpuDa7&CSr;z;oHkiFp6$jBBGbNso3 z_xk)m=G8}}qPBf4V5OkPACeZCENfvpVcR}BRB1yH&Fut3*ILCd5oJ_F7bzo zp4;|i^XnO}ZojE{qaDZavrR7wf2)XHjmsj&ZBrj(NG6F2eZt#=l zmX{+zK%hwuIzp9x5uu8{j!#Vd>qogBUy@it4ytgV8Hb05!&k%9u4BEtc?{Kk_)n9? z#)|#@`|IMpcFBc!U#m|HmvyK?Vswl4lCu_F*L>>VuMn*km8XbPp`NjT@%m_dytTU%9A>EUQJormc%-UdYqLXy8t$^+UAuRg1YEtQg@A z+%R19A+hujHnCj$b?XeD?5VZRGTTXpe#G!NLmo9{qD-uw1CmT%lyd%OM(V}FTH_0i zFuG}RD(mO%Zpx$NCPG&%7IKJR_wlLLeTg`|7gK(&UaswQHB~RcUtS@`?!#_JUx*owX9D9QgMjEjFNPu{0uzFk(365 zP~;6(#sRm;6zif2qaf{Xw=E-r6B{dRy*iaq0gKq5AzZAiot**9PxN#@Ni>py9qQqq zQ6KS-okKA~besX!lEP$F|r1zGmIQ=?DPNu@Qjk_5+#(9-u zzQ}`*BCaGENqU8W_l$d_`E*Fjb&$}`5X#1IjhcFBhR}R@-ztUOC9wHU7%hs3P1*}c zIaZ6B2$|U=-L=WC01O3N#5`NKjXI8o5JyM-hOhzCSK~D^EZOAyb^fNtgta;jOS)s? zNg-~MI>;nS5$t zL;43=5>w}$A|^r-Y<=bt@v(P?U4u45wIY<>W< zAADwDI{Rh8?DFk0Mf|y>!tXI<$w`+@8a)u5yz1|V;WIiVY$}2jKPD1ZI;bDc_UUq7 z(THcku<*`z*e^ZSNk_uzeA6a)o=~mySr{%m4j0_l4oD?1adc%pUw-p4#m%L&Yye^r z)8GL>$VBE%W%5uF3d@R6;gu$_X%TvSXQiqSsTRE}Ui(>Yka zw@6rD&E23{e`=sY&lKlzlEZ(96^zu0K46*P!tU*U)b3$CXg#yY0q{ph#~OyzVV}-p ziUb)fGYo1ld}zlFhH+5%q=nn0zR4O>4LJ?X(w?-o+#VH6(23iIU9tY^$4mhrR{E2J zi|qqtDN`Tr#JAoXakIVQS2-HUkb4B$CW`E~JBG!1Et~Vz-U^e`<}v$)j(|%z3k>I@ zH`nDUT3;bwN3iI0FW)G79-|YMrqNpat!@Nst}tAtXgrWwA*1KUNVtOcYoV4plgme4 z*Z{}JZ{rKr`M(*KttzoQYZ68(@wNSvwM#BAu4RR%A(eJJA|Rfg;e|(|P5c+!;xD)_ z`bl#~FkXycTy0l!_}J=bP0m=<@+vm+M;%S23CEKx6XL+m>&*B5WcE>VR`hC;6Sh$A zl^iiet0C#3H=e4;cpVU{)D7WQD?M?z;m34SNZFHIE8FoFvjoC)#ReZHv9Ka6*{Eb1 z`d~Iq8^$zX*c-fEh_Y=e(nc>|L|s!ykL~eo^(v$pmvNxOFzd4C*K0wOer?wEc zzllpn<{wYj$6UL23vt^3x^UvqYv_1%^@YZ>nG~uB)h=$1+>R(aiL4v9>IjC_6T5vTr z1<`SgWQuw=66oE`k(|6;@>CDt@XcNTGC*3V5j!ujj@jkBaGP-=7tw)B9>dBJK~j7wGSojnP8`-A(u_AdV$v zo<-R>l6#jdDfl7%`qBnBH+LJj{V>Y_Q<4y{t9-bX;kq?@4H+O{f)CM6U4&T1-~{9! zI-zgozb>BAZ;KA`z)1a-tXJ3Y*|kdSwO@`K?GTceuqY<=Nk`}CI9wYQZe}sqW+ulZi}%V>lln02!`VeniX4=HLYQ~*liyT;0#*K%UH%`0xSJ;XYi zQ+ap)DR_Fk@2sxlO7U2wtdqW6DTZ6e=IyAhyLVB=n@D+v&Z~078=G%!u>y+3uUxeSH<`9HCPVczbqL28b@wi&pZ&ytfPAY68vwyl zr$+GI^p%HQ1t#yTKT&hwzJ551S$vS%!bN?+ZNTL*nQUl(U8yrHwjQ&k{oy-<>QhQ& zHua|5C)}W5Q5`CLY`XEw#0Lp#ilBysgXlYyFq)*(NRSkHwlt!xB5z#Km$O2zvhD5$ zk6KGqv%RC@$k~~~E0yjZ<+*Xh`Mq?>@=giMM8T@KC^3=TyI|w%4RsALQB^H3_~Of_ zWN!+5?7O}3WCEUzZag$k2U-RBb&e9;Br(ipJ?lV6jqY!d73|h zF^Fs#J;UJU$4b(~t{e#&XJu`hp>|j$#A(^%z$&4oFFQ4nFQHixv9=(-$iWU)z}5Eo ztvy{wsh5D_R=QbgCl2m|M)yo_|0rv6tt+n}wR9j~5n9k)P`>cQ!BmONHF=r>A87~; z|FROS#5dn{o^NAiBv+UU=>#04*}LA-B~((crgYW9@ef{cPMJrjRlhzc*VMbyvc%wr zm@b@SW7;L^rZh9b?SO%c-p*D^*ZW|`He;a+vqjZ-h-tw{jRwEOY|Dt%b(|gw#<$q* z6~KAQr0IatBgawI8W%Lz-*fBdl~=p zUzF?+FSecDuYFmnob&Nv7e*StuD@dM`{0qD9yi+(r5=^S4CAxQ@*V%`Q;JAG)hzSL zPdy@$P+jzKFINi|R-k_@{Q|GCGvSl_1$AQmvBJJK<`Fq!p_%D)|9DzbZADNl`(|h} zzWgnQgq#4IoB+q7wavGvb7;3eu_v>o* zo5$HdY?QADzgBOlVykb584qj|bCV1Hs%=XaI&Ul4K1_vCHd3p8)1Y8sE4*hI|K6tH zxs2EdIik;+wQMA#WnIzg=piQKw7TN^GA5j5(ID+b)?MNpq)b#GP9N{?6_Iaze&=l` z_qSeYlpR}PWd3wd;OG4*BtZ_{Y&4dnY=VASot|N^ZS1zaw7#Zhm(%GR*>6c_?jrT7 zhYR~>L(Z$Tte^CsR9Rs?=Qs^Cv)49s+gvAJm3aR(=?CcpF1cXEb^d;z3)xTEYNq;5 z&vXbid- z5t6`Ltu7O}_qL8>?5W0ee4VHq@$uVlE5+*ZD!F)q$C!u*mL8B7J?G$7BM7SNs9Omi zUm`|giNB^ef~Y(Qa-#x?i@4IHKXz6ZnwsLr1lCU)(OGKe;dba}*lBQ$p0JuG42&0l z9RaFp>`PO%jeMdZ@F5iEI?>N@`Q3c9R?nXD+gVr00Pz6%IHk@R67$})vW~0Hp0{3i z_b%r9MVPz6XODkde8siVo-9g@x8-S=1v>fRa0AzqRByz<{cT+>=GD|%cgiPUmV$$- z;R7nz@vcGARorqhyISOk`@*?>7Ts5aWsmB^?wSv-Iac&y`D#%Bv(S>5KAFW~7US4? zh&kuGmg@xjt6sGDQ|s)!iV+)zc~KQt(ZQXKLlL)l95>Y*3H6uum{A?t$567WGTGr1%z}p2QoA@5lp4Ju8uiyJb zgPllm&nNv!3LlxmY)Q_`nAyCP@z-~pm4IX|yH`)0VPZU`TZ)t)vY%3@=YRf*>Nzgo za3K!$fg;z19E}G*JIj-(3q$T^)TQ4UI;LH`Kk{5Ak%w9ut0g8_*V=vHqh8JP?I4mx zKh~9g@81I6d>F$|&?Nb(ihI0y!9xLkbxk&CrhxoXuL`ftq_ogDq(d03#1}CJ(5fi3 zfSBIME`0yMbOGs&(|4wER2H|TudO%f8J&xE(Vl~x0&%@Fi2q5pm`v%e?yr~WTcg!h zYYisESKHYX1+S$v6N}H%q!oB zi2OmIXfR{Jiv49@>T2qIY|UPnvqI}V33LAk7QPgZJaG(J*BO7OR2B?smVH|$K;reh z#zh=%%+43nRn>_2@uj91)07yvT;uUN#iHFfEI}%x{k;1m@Bl+Pehm8_o|<43kuKL) z3QhkYx^st*=Y9t+zla&boCK+^AjOf%gbFv!HFj!uuk(OEryd!~ya?S7Ul&8EP>B%a zH8Yu0 z+gz3I)OXQ0H~gecF5pm6QoQnmTQQKv{o43SsLvcXv@?psloP9k`!`0FG#zYPSn&t< z?c;x#HQQbb&)c_qcIC~w4fHot*O>|m?h#6S*N!OCz2J8vKk#v;B3p39o34yjd)3rd z`m*qU;*JtN_mSTLrEVA&M5pXSuTK`OU>E{s8EUg`?&LOT!ZDk*FmUc4t@rysY@K&J zmH!|2FMH3jB}ewkh|EYrMkITW>`gK%j!;HcNU}rOBRgbM$;>EZCL$|DGVb@)_xH#B zc-;4Y-^VxSoa=nfb$veX@p?aB!i2t*N^i#=!v^@p?j?O8h2v}K$(K(eF-64f&J;-T z?qK-e-UJI**BzLF!& zf;pMtr9^&|DmL{s(>N7HFDfeA<`u6u&?xrx_K#k@k)SJSd`4uFb*e~6Vppb)t4tx? zEdRe>`rqY2$kO&2tISy--dvazHN>SC-b)Y&r2-*Z#6SzDu|0Q%&#EzWF6wM=@$U6- zBB>r6`c)x|@tWP_FDvq`C6Qh0tuH%L_rE(z_AlvQpC;Z-v{sK2UtT@Svg{L=Zh{FJ zT2ai_eZa1N6xjET_C{!+LPoxoAnbN#$k#z+P@inj(bsd~>92hy=CZr*(nCKZix=M~mDdAPp zjP8r%mVpRpw&W`27-Q{{a6F%SGtG#ziW7EQ>D5&b63EZth<$VVxXdis@?vvsp}NrUb3x3g z1(QEtar&zRZ_m+aMMDOLlFl!zLa)_hC_sgT^U8>~z=wP53oFIb5``$U7$!J@jzx21 z;rKD%uxMNfR3>ESR{Qdz%HBNR%B=UNMD-q(=UYh*%&ZmmFiQX0!~wZgN>Q*J2?6ZZ z`PD~nZ9$9%g`8N0^3y)ed=&W-qw+X;{0+)s?D@sD=}W(CwBActEArDT3DSBudq9uK zG})+%EpUZ1p^>m|;jWs!Fbp5Tb|%*9eWirH>j5&~GL-R;Dia3Z4B{k$tODaBXq3u&Op z%Ho^;fmY;gFw-N$k9tCm4=!vrm{Cw#p2z8Z%@(JB=7dO!=SsxY%zUerq9KNYq;^Z; zhoLxiNyhg_Byhs4jhY%3XxWZ`Nqv+ggffZsc1Oq1=p&i?rK!b4)SiTMIlE>@xiaHN zK3(f;`9#zOntzA)Tb`min!FBc$xMnQqZ_qGNU106jr}ctZG8CL-El5L;Mu zzN)W{ATDT^*L?1|adEM=KBc8O-=Not<%>N{yR>?w;~?RYs7$`(5+eiFGtSN*P& z1HYL0BIV$BE6>t*tw%rI1an=;v+LLtJ@{r<;FuxRy*6j4!Mv||T^hnYsmvRM552Ti z4K0a2-}0UP(dXcK!q5XH&K$qnNUhMB5GFiZ=ayy30`1#qR!x0sWdDhRzGcsEvEzZO z!ZbOmudwzRr>{<-0s0Tm*S+aDmV3lYj8#+KRjPyY(FfO&!Xj^0s}9^&h{1kR(wEg& zb-EzS#<<<1(Rva{30wAP-pdP~sclic1pS!`P`UA{xqW+7^kFKOil*^4&s({45~My@ zkKu6BYVz!cVPdDJ0{I$kdujVHqxv;FZQ*?NYqtMBTnEa`)!edSxYYn{I*4>y{183x0JUJ#DhT?I{vi7uxSUp^Dh3{Pv%_f$kt?EqzZ3fq9-< zusfk$>QFPoU@~qQvy?vzo{=FFV~SPsY5r8=I}iT_c#Q_PAfY9NKZo)-B6qVBL?{8w zr`V=E$q7uzo^Tvi?her~W-^+TudXjo_>exUmP6BuHTA-_D391%qejzQuQ&#y3mKC( z4m_^oeMocE+BGG}<1aLN*LP2_#NqsG{ym2c%W)Ap$k&wkSH9_I5Zlxk3U3%pGAb5l z%zcP@cYisu_&K5EB&$@W@k8%iI?9J_P@6Rq9?Vg5n0ug2)G=?8!E*WZx(}?9^DGi$iMJk3Uk;1EvuKjQcIROilmu;{WmcxE4EJ1iJ%^e% z#fLb(UJR|w-Fc7&j9mI%B0}D~J0-zMK#stACoz}s4nDtcVSUA+)~ng$EB{jovfqgu z&7I4Vl!J7$*Ob?bJ?aDT%*B0**A0C+$T}*do>)YczVg|c{DKQR!+vikRJJ`U1i#tP zKyQY?M7(YyBHDN7O*tyKBk91-50a5?j4?g#bUrngCxd5<4v6leqJj{$N4!e=`KP2FnqMX zRafZfE=D`rBhG$dNxXqAyh!7xK@#KaW$3F4D@Q(q!oxS`8+moJjw(#C1|^GR$k+Cx z&93G`of`xCxjM6|&q#xyaecqSaGTB)f&l=hDy}(^GJD*xc1MS}S!;A%lf}UuH{%(eod|GJRZj{X3Yc$Eb z!~aPa-_xVQ;=<1^G>!;$bQmhBls0hteRtI5`KV-W{FfBqu$E+@4N(a$$6?SM3Cr0SuZ===8p63bJw8|b;OQ$$kh6^ zOm=*fRjst=th1<@KuKx|xiH;wJu;+^`%+ZH@S3s`esLcB-Hif?j`CPtUZ~}NW)*}u z?zXOBY|bfESE;6BU!4QhQ86R4eB$b*PRejS{IvJdE}xTeFL{| zPN z!FtGvkAw6tIX5s>y&){Y`Kc8~wTjEIDkSA!ir*ui!8f{2bIew#X!sY>h?r3WoImi& z+RP8(P@YXEw(%vz{uO4JtHSG_^*FBZzxT#Uq#0B$|BtNn#Q4j3 zW$8w?wW1)W@_qUY<+g$nIjowDyExR80@V~i;VC2|v|{@nri_lMzNhF_u({2H)4UQ! z2{+vzykAj#+l>oJU_zudWWrwgig9AO6p&&;n*zV|%P8LG`naJ8gsFc?=2M?A=s}`0 zE<=bcKoD4`e~AP4)-vsPX=~0-Z4YWL>^QtdZSWZHa7&r89ZI#((hPg0zlb%w;9D z-WQOG4GY)fwk|8~vAsR^3VA0i4s{ev3Ng(J&+hNr`1~1HV=3qzRxXH64U}Hc;Hkk) zaAx`?LC>mnKD=u^U2fjs7C!b}URWd%_LZ}>@b|i`N z+n3nlj#o)hQ_epnMmEcG;9kMdkgz94u%9AZl@so$`0P_iy-H<|{%mk4LLCl@@#*gk z=07QX@+?#&O3=X?zS?Umxm<~0+cH9F=Faz22xCA_4+jQM+Xde!Nq(K!7yJZed<2?m ztN)_aK7m1FD+eP`tK%2S-Q7n!xnhbI4%EZ4CKTbysCYnGX+Tl5Q~TjQHJ6xr`Yt}p zB2J{Se%XIl@u{+&Tbg%F-&#CA^asKSF`v=_x z3Hr|X9g;zZmgcPF(T{2IpdIZgYWWD{YlmJ95gK$v?|_ZSNqMCae?j*x8`RFcxJ^TC znhE$*8TVq;H;Iq2AFMtmuM;8x6yiZF{5pK$y8I7@R2!JTJ8JP#sW4cj<-8 zv$@Hn!$n$7KhoAeWm)g1$$7kF>4+7SZpr=Ik66ye|M}O7QQentB&mme-Bmt08VXK%bgKylx3D=MzQwIT zY4c6^-*X@ac%N{r7D>^Wz0Y2bliZ?74qZIMNW<_>_{cKCc{$bXJO^8-slp3e9!Dvj z8lFJU-h+t!2!gLO^g-b!Q` zE))y~rIo|`G3rqEl0H$;3$M4z9~kEXo&P+~)wkW!f0Ve2r7Lc#cMa+#y}qHA#v{)H zJ(P$}9sD9#*1Q@RK%;IihCU_Kmp{Zv=5^w~5fb=LCVXVtyRYze(dDE6ug067gYy{? zkrEAJ6`t@MjRI2h_Csohk}$og3zv;5)Vm3=(@#TuZm5M1O4%-PpFJ_uH;dSN6CFk! zgvPOR`U%s_@C3BIj+(@icaIjPq*lDzwXK=6RsTSx|G`dNjMdhF~Bp z{yV5KF<}?`eO+)W)u6n8HF6raF?7p`)d~u5Fr%bfNu6OjBqa_a*n7#d8w!3qiw1L! zd?2nsdS8qU3$Np_k1n6f%gvbyR3i2;`!VxOkswKzhLN6E)aZWTdNS_P2L|&Fz1>Wy zVKcL~85y=vg;r^n`m#4czxc(2(QTpUlguRv5QOViPBS47|MXI?pT`5SWuNaQZQIwF za+|docbenA@zy}t!q2yL_JlW@6VJx)Ufk^vgH1?uQn2nfQIb86SU zu!j8I$5)B?W|ul>J%r|JW`xmOP9U_Ut@PqPUivBJ!*4dk1pUd1FiWbjy8n$c?6%Y* zHwz>}v&HM`Hn+p1?r}}$pAF~ggD)WWBO=#+ISH592!6ci(g&qd>S%m8s3n5Wxj->}Hgh0W(V@~-O-aO}IhQJ57q(XwkR<{7 zD->0PgM1I23oQfAQ|?d%49<`5rvn>d4k(!&sPqlKnpwRk4ho0?EWzLdA)Y*2F{7W* z_@O4AN)aY2Ud9m|Go7`PySsIMQTFc1n}>xac?I5Dng&GcropE{R|%)v=G;_Byu?D_ z8>m8#Ok73ktvd+ODO8YBBM3~j$w3!*AI1-?#ZsFtslNJz0Z>L|WpZc@@Q^4nu8(uL zap#@$fo5)!Zryt}IE}p{sVND0hZQ`H$y%&a_%rMSc047(*6Ro`@Q?;uiGb| z)8T7_F3h38YjkL3(!G%a zCVx@JFiKfu966QgpT4M&~=+@ZY0{wjDiuvhmN3Of=RR&xw&6!!(q}P zE+E&S7^UQ)RN#00{VEm~Y;SJ=cmTkIG5<_p3euf#+EhxcNsEt-0v*JXbo51N;XS53 z2g3B7Sc6b&qr-rFM#v8!{{`V;wUO)^C85V*5YyRXFN(6qw{^o5=;Jh7M}lr7{pJd* zHeTaElGO8Ix)}si3L5#-H^ouxv_Yu}ii_reNkze48x;5i0Gu+j2HaH5?_25UTrG;f z+p97t_SL|gQd+UE5$C=51*z9Yyu5Y~l9x+Cq!9Zu<%Nzzh!JP&^18K9tuverkMq;6 z&u;AKBCYS-bByF(ld1TU<-ccxL$BN%9}BD#l;t{E3jl$2Q4au8M6!4^C6LWR>kjCX zaj0wp=&*{QzLv{82OVX?hhfw+$&7+l#?WK9jM*jsZnl8*NfJIPOJUFLBo09!sgF{$ z>wR1^8JtfXci)$mi%CV|IfZHxwq-^$4QbB;|gUxTpo^B37MUsn@Iv~X?x!WuK+djVRbM=dMu0`_($Y0t-uqVLrDjD z*AgpSzlZ_WhY-d81_6KCJqw*+1K^$%;E-TaB?=wsUmnZ>VM~)2b_neCk(!5NjWAXqM*Vx{aTYAX3di*T|jZ^Y@Rt)jlvv z>0HCi97BkM(>HVFvYO8aehC{;>>x1X*tv5&r1kdtPpBJTcW{9>_v*neoABHeA)oxY zI`Z8~(`f6f)B2l7z9el$srPA4<++Y+(<<#>otatVB+w*wlGEz?Xx1uy^P;wk`>>Z^ z!ymyG^m}GSNML6QagF4=F-O zAd)^SHc1PF?@7}9TYXfk9|QHY#B&+FC3Y!kR(=$uC0C#*oi29DySHzDQIkzfgMZa~ z;tUA5`5yMQadc`&;douvn%NH=Om#DATIc;2Q59_MKFK+KNTVbJgaQ%_`~VYChzLfH z03-*Ep^IbFr5c&t4c}{FRGn4uxXI*k2MEpmM4)64<(*3bTWao`@XMXHQKM}Y{y&Qo zA$(U=#*&}yJF9$39!_D}4V+n+i~lgXApn$!sRkdEdxtXcfHe| zsT8fL%+~>>y0^ZQB7^CRu{K)%*pG-*s8eN|U@ljv<31#So~}ifscS{6^FPtw3XfaD z?}L@qbE!see&GKkkDffZIv4CiH2ByO#-HKxc@xws+`r1ea-jP)438sNu;3s-hsd(D z&gFFsrV7|2(fDix=?nbBtxR0gc&$y|h6jcgOCQ*ToFF;hU)pnMt!Pajk!q4IKFi55 z9nA(SQ#{14Kw~GybWsxO2Te^eCq8q-ttMn2$PMCp%y&;@3Qe`8lgp3$J3&ZCgiI+E zky*TLzF1yE1o9J!d3nUF&ixEJ(FO6~3y^ZVpP+Qaw{T}R8k!=@FneA0g7YIZS)nE? z4^)At!A?R8C)XWP7QP5AAxK=TR_6!PC#L!XoKP*IZ@N=;1b9e)K+|mjyvnLSU79*_ zs%HsB5N18384ektM{rwVnBbd}CKLj^3Kbu*Wu%8^nl}fx@n0)uG&OXuo^PY*vG$eX zxhHsbCgXtuEFMld&MaIWY7>C^)!dT|ji)S~`lh)yb{gT&CQ*ITiqq6pRYj(RWmC=zzU}U%=KPMQ&fA@Eh4yMFN=MS zr--PL?}3|&9TBHQV4Uj?%2orR z?OYX8*liSzU{HPkzC?P*d}&7&5!)bickP0tTB# z9*>{igu$|ejEorIEoED_1nKZj-K9mRZ2_E@`f7}3__(3_gkXQr_B%+|palc*;DSkl zk1zGx-WJe&R{ShJ1(jPk2%m|HJglpQo58f*1z`lL7_d%9_WgBqbjWHS#>e*1A%q9d z#I&G`WM7!0|M9qwUt+#2jxuM;@k*AXL}uD>;(xF1fQQWIyC!gp69>4dhjRil6+d%XbG)yN*i)uC1hztx#7(GBokM37U z6TUfgE7lK|sX?I&;k@;y`&VezX97uYz>#e_IFB1#^_zoV9q=Wwa(eLCak!4kH9S4MEv``dyJ|1DxCxZTZ{J#BZ$$6L}{hC3$GO> z5?gPHVPJ-hyaWDYwBAEcPmin?wsknjLQ0?ElqA(2-%@mMAlV*cQ-O?WD1`K0fTeRW z?`6QtxFulijBD4wMqK>Aj%>Za2h~DQAwKji#m@->nSsEQjqf8XdIr+;qM)iNiX=pw2!R1<2I`J1gnVddNa(Aa(nMZMS@LX(_#fVpRF^59x~V^mmI48KJ+B2X9WF3`4-RCsqtj?~ zyMG(seVO@#-zOkln9oZPGy$oOoK=dt?&}>E)cFX=#JBA1<^bQ0i=f}CKCoe z|G4sF+;BT8ct>PH8>=}&#~<{OcW_uv2I4A0(_~>Ly&alN2o~C?o5O3(PEHr0v#-+h z8{y{RS(t4Lg)+NQtt%5s{9&;0#{quM=aygv7&wIq(n`M#i-@iZ`)ToSpot~LxOC!> zlG-YgX?H1lmmWrIAlP`Ie>i{y`R(aLajiFI&r~A!JTy$Ghd=tq6u|^B^{G=G$qy?zZ+$%Jz)LHkbU*vH=cM^pFF_t1 z3pEpaPm9NDpNlDcXzrW@V%Fp@`u6Cz=^>CXftPeoGCW=~&d#`uNJM)0EJS$*vK?Cc z2!C%2elcfLY}F)`kXb10a1o2FRNR`^zM~ujg zKc9B5W;YU@y+;lCW!csi48GI5QefOnjl1yU74uKSKDpJV4$8E1#Ul}zj8Kpd29zNp z@mV|I5a4gW&2;*QARI9r3OwA~!<1l;x9m@Wa&TtsaTv^J+iH5dvHs zn@|WJxKzsa&g%+2()s*r(Q;rXURx7^x z)FA&G*!W}5Ik?00y!+NmO{S!w;|ThoTPaL)=l!l%&)Oc&ED;S?IRE8BT0bQ|@$z%N z7hM+u=MEP<;$&oG2~VCp0J`=$0Rb|weG(NFmGb^Ze1Vw)z`1{1*)VPor)?fVIhhy1 zrArof?l??$vPuhG)a?{9KVF>7HTDl$4M19lD

id>>Iv#6CKcp!vEQS<2j2;33o5!LDF)1~8cdP$P1p4K{ zk4|H?)X(M`Js9*?y6Q9@a05uNX>QKCIqj6X@Y058OvrWGS#YdSp zaN;BQWjD?FX4%i>mdKG~qt5HNcqwfGTL^>^Z&?F;dkR;?uy4U;)n4*Ea8*lX-UvB(koy z>;;lIc|~yZZ_%ydU3_(AT*GtY%{l03KHi`S8TH$JWTZU$623#tTn$l0Aoim7H?@`B zb9v8w8cZO61NrFfxXm7j-Rhr}U)>`PjtIjQJ}Nd)^QWi)lN?&FJUIGdqg+hq%&pUU;>yoHveteWP z_6qF|AL4t=0FIi)LCP);YftTc};l>##xZdKHK z3$4Qe5>gJbJ}ocfunUnerzuiWb;lAKcN{s$`ve>WOBP@P_18*#GmTHCKkHATZ6R4l zN4n5+nQI!pZSsNy!6C#2R)2miqNZCwc_GdjlxI70!7*OD2dK0jo{(+9;pFAC2>t^o zz8i?@RpU!2?GQ$tdr-;<%={7|o zJ9@JR+EY*hv8tAFAlgpAJ)VtQg@VB)P7a*umb>ijN2Yg@Ay30lKzPc?%uM>!j^%zj zfIm>KyIXW*E5Ppm z5ClcDU=UUTo=}J2rWQkrUuqz5nsg7h4onE|eq@2tGq6wR8kRCUAo~`D@#`k=WC9Zk zlbEFdpkl-G)DS!xdR^&xRPjd*-CIbK?tp^YH(HuEVSl_7>UQ>9N_5Y$ef?&(xX^#O z@|iei+0_AUxCgxa*Ki&K($L#m3?L&wg6l6Oo&N=%ae;Y`%_QXH%1%y&leH+6TTv%| z&muBAn?332QxuU)OhST#++LfYL-9-yUZWhpxTSwQ6#$?%WI@7C5R&&E(1140+f*r^ zv!5HTtHtj0j4H_+)!Kb($tM&*>)*_Y6nvE-=-E;Ife5lZ(I!GHYQqH7p+~^WXt
;5@yK2u3)ISaj$FXFHk>#>7Gn>jId)cI9MOt$T~!aJ23#iFzkXv=@&`> z@PKwwqGCHmV^C;{YCM`eqKr$&RUM{PzTf|K5tJL$D?A-U|4X8sLjARHvcOyp^*KY) z!YCRXCf_~(j)RwCR;)M>z(yGXX*qluC|ro!YDvZ`_~(WWS#6#IyLPI_T71PSD$Y-&IoD zG$n&V8lOwjVIWO@fk(Ih>+J}=u}Lf(yxY_jTA~znA@CU@?o(3tAn|4tx7UoR^0==L z++HBL0uzuC*d@MqHFJk%A?8FeEh8%*jFVv#MOnM*`AQJk%W)@;s1%PXl^R^h9n$&3 zID8AnMjk;)?ObCxhosSaKOblsx2DHYVPJaoUIeY>^u^OdAtT!$uxMQVo3@0&2cPYP z-3A}VDrqC-a9gP^?W5kC-(GoL%DzbL0)bJ$oUMW-L zT+ruwDLNV)y;Z23)(-7m9N?S%f5NOopVF0_Cz1YC$Iv&2Vm!O0iwfx0-kOM=&I!6e z5`~gPEpP$UObnb;h^PYdoJoGXGdrc&ZgM$$_xnZ)sOD*5r2L+g2m8OBEOt|j%pdv# zsEb@?;0hnBlqW*ou{lJpWRmd$YK~z`Rxab=xG+$|jLg=^9&m_GWuc`gVkeU(d@O1w zh#EZs4$B6zE;Nxr8A`A(!1`?taVq&klA+E|s`yt1uU`6AGIQnOY9fLq=$IFk;EF=C zZDJ=jcpo6!Ka=+1M!8o2+ecGjV9WS}%NUI9K7<|u4f;V)9_UovCY}o~C&*4q{PMju zlqK%6OKmR9I%cL$C8pd#-_4?l{sAEZ5MDr?&Y>PJr~xmK>(Pe}iL8uG~c4G#uWY3`p-A;!xvjyX!}V)%*BY6(9CG`_@%KD-TFQynrUU0KaS);Qpaj z@pa`l&9KF29di4oY+`8}z!(s$pZ(q|6Ey3H-8x=65+9HY{psrP6(#aw0P_pq4|NmF z*5MTa=Q(ml5$uuy?eL*GIa*xNME-2tSrUt^+ly{5ShsGfMnlP7Nb9EF_zLuADa1W{ z#)z~kocz(A0?P)}N^uj=L_Q%H%v#21fA*9kUaK}zf1*xh_d5#gvfp;gGPT&&|%mMVW2TZK$XXE34mvqi*p8UFjJcr)X(nW`jnXiRg zr8a-0;gRlxM_LhFW6*sSwI@S?`S5bkmv@4BF%z-2nubqu@LVpkGvM&cQ&N=-YQ|6u zbN%o010cr(K0+UAK?Lm4wGdC73Gmt|I1NEsjt>N2=f9+^ti1U}PRRs6iy*t@(vwIi zM=KrW8Oe#|TpiGY;9db2?9|?}3>i4pn80we;{|4XeEiL?tivi!nv#e2WT-$F2om{f zBML>(nGY5J&NlMsf($G?phKqaT>zA)Ja&%yu8@9)bJM=+Pj$JO@FSzC6?Hn=d2yl+ zB|TNe9z&evn&6i?MjlsTJE(fpS@Riv*=Bjy%~r5h5CPul{ewM7zv^yp6FZ3kw`%`D zjUE^$E?>`AbrNU8@v`JCVN|umkIY7j2DTwQvymi{AzR_$;B`! z;S6$(lwX~ADKWV@*u4N@=@d*^Lp#0Z-&d?=6JkTUdwR|R`ySZ@J7;SM9sgNx03fyl z#Q{T`mHqsADwwAi`l_tNEL3Vlm6(i!R0yK#LiZnE-@Cb)mwtJ;zyu!-4UvN6C-xo; zy|0b7)|{X|M+4%Kw5o%xT6BJi`grsCp0wY3`ncURu$ECTU8uHh4e~27Ke9GT@AZ9o z|8I8z>~K~UQl1x@N8GYP$JIf^1cJwS)*mw*ZhwC&$^^-#Pysq-Z=DUxPN%R+3Ag$j zLphEW(DLBmz|S38u9X)O`e%;~|4UowT;80RdJOcrp#y{->=fo#AS*?6KXfbz0`(M7 zLV_4eq*_BQ`n0?PD0~fr8W67ME1`WU`+z`0fwreD>bVY$cK;g8~hZn_Yu*1 z{ryBjP~2$i9sDHXg4}yQ!U!(jcK`3gnjzRBCnpE)Ezc&H0Oi7Q354zkI=r3WxE2CM z*QWz7X@=R2^SK?h?f^dZHd(pm>hCC0MHqtu2?UgTuy!G!>XLa>^t@RMid|H}0jyA~ zq*c=QUyHp|{gDH3-k$Juf}Q3m=pD3!CuSvJ4KJlBMGU}wRBa;Nd)pGhU5qr(MCwfn zmV&MeNLo$)Fk>AM>_~M5VK+#+-f>NbHePooa9^j3^b8KDs{Q2bu({d20IEA;D5PWw zvpyaX#`FbVhds}Ys9YY4#)<;vO%K3HoE!osWh<-f$pz>hU4@)RA?92sED>JG9YUBo zeh8h(!V+(YrR$%)!b2j$6umiHnqA?bf7Buuo54VeIYm}^r_G9dRlN;lEAi_8Hl^!t z!Rr;;IJMn?1KziVZLyxfR8OJ$+3lY8*MiWa3GH|7ferzu{>XZ-(8al12GY zckI=tP+Kk;7wki;z&a2D9n=YeP?6UxM>JQ7G5ToS07xqva3(3<@@g=ntb8_p{e#I6 zOM&fsVR4(8MH{$Xrlu7p+>Xou*)H*gCYyR&rsMbCHbK3|(G5sFOUy-xZJ)FUxRAk5 zXaM`452+D%;$`k_v$M(ZW6Qd4#rx72*O%xIar%wl3RNbVx>eh=9B=f9qmv}3{sC-t z&sp${a#em@`d7O`m}!h+902RL^DMve-M zzkY8dYG0ab375TZ^#=GPj%YK^26LG~H31VRit`0x<@G2nlixYiO_d zgAZ3Fc#eX*MXq7F1!^A*5DR!HI~}%(aS#{@zLg|3zUixV=%@u_dImwk%!mk&1m%^& zDfpW4GEm{GhZZ3kt7^+_;e(oEsLDYbJ*?2?`LFHm8(=s2@2x=dA7UK>)hVSTlbL6u zb$2XO0wZZapkLC&mAdgAjY06BqE%H@1=}?hf^BJ0VA%Wv{^<`{+|go9fa{qb1x8On z9ER<7ypl8akuK=Edw6rO!)u9s{~2GTwYP5XG9t7MwD?XUIKP=5hNyjGEgpfO1tn6T zR|n>{*E8iJ0Ti1y@I8T2#kP8`wFaFX)jJ=X_aqWVmSpc*W9=>q5=VKB(j zV2}&Oj~Sm(e{{LuvI11JkEVYw0HiSAGj;Ud8kK$5w~)^$_~XGu#DB$d z@`K~=(gcT4)K=n1n1!Xo>J}=)qem}n_Rb+ujYzMgZWd5zh)BJUXEB?qL#=eht)m<0 zJHgl;Mf6QRl%uTc0qds?D}@Syz!VaNa~^M;98<~qt%nUceycLh!>g2Kgoz~Frvx&O zcxf1h14H>5L)(V6c+fbxAdll-&_KL_X%ZTataiH~`y)5Cb6_)uNU|F?XRqZ!OdWO; zjJ(iQLtee^%@Lo>i6<4U@S&dRD;!0k9kJU4@loOX{>SWamV9fx2BoG6-szMJK!HWC z2elhRQSe|J)4DQR>^0kpWA^qQ6Bzj}HAd!T@DD!s;+rv^=aRsH#%0x9egS6oOJtwn zApU!0$MqP|q$PSN3OMz`EeGuXC=`|o2C!`q`h!8bC?MkHwm*tPE<_&qJ1;dRF90Zf z01(4LI3NDS@K^XI`xgT0%C^g|Kl##kikP0hW{v=N8u&SD(Xug$JOLS76qrq00iY8# z;Lhs9oO$=Y#2WzEAS{NSQ6}8Ti1D0?8X3&}SC9LM?kOzOQZ8^SSu$q)aZ0L8sUsU__>vB| zAPva#KQgE^DMj&mV`b*iK}QFdd0nR%#5zP!0x}eX4v$t1*)Iaf8TjhZaB|XPQCqzQ z5{@JT(pKr!i@IL}Z?-@)RXgY|cqIfI$vyO?m}|I--aRaEVSw_x_@xrn8BKwz3e;aB zjO1vNzXf2tOXX_1H4n^5yyusk_n07G&7R^ziGsMVV-T1`M}S`Z}MFfoZjvD9EM;}0zR z)qC!ct*rmJj{*`LloQFByhA8h_Q zao?6=t^e^dZS&o^IIFdZ8mYU#1reye&q08@^G6EpPK-E9WZwIA4ON8n^!W5te{q$# z1l#j z)Q_6yA)%^vIt6ujP)J6hs)wChEN9Dcvi11G zRdTluJ_AO)fxS!^wV)k!sWHI;WX}=RKlt00I2nPXoOePeL1A*;4Jj0=o zP{TgD1u^wq`GK3-@&w>neboEm!>>Ok*Lq>z!gD#$t|4WN?J$|8w0>{<+@SGKMrwwL zzpB2A|F%*Y#NriWEV%w?JQchQr9o&Kq7Q|jX)QUj*>`cKbzorN)dC9QMfHy0O<;Jk z0mZt@z-tH7K&no8ObuFx;piA-u&C$g%NcUElkca|LvC z;{Oe-fiNP7XjX2^fT>gte09{+4*1Jo*;*g~5dqJQAZFDGD93qmHj`t0#ylb{SJU$r zNRNYnK@J^6G>N47dQZRy_6VrP!qy5U^_}G*Jf!KR1H9eWVJ!}~kNLP~V6qnC7hM}u z2maA@s|pzG`)opU*c`lvXf8u+RRu4X4Y{R%TeshXeTOq5zV<|Wv51DQ*RzNF!N+xuuvx2_+ z?cWF?zo{YO4-a=R8vkz2J}W~fKmYBIVfEk;QGJaZFmv97*vsmC1EqzxYNgSF0iX~W zhou=$o(*PfaHAavHuQR)jJe`<;6hK9pJ_wG#3%FQ2dnV+Rq7W{=D$iGVd#g-8Q}&Q zd-OI#Eln@=*iF7Uc;;+xx1s85c4}nf<9b{Kvaxy{jpFb9`(QhjCH(j?v13$Nf3mk= zjI_S?`s#@GpfIJ(;O(HrztnxQbrwZ?qAE#ENg@@_hx0>~U-u#UJeir!cy!hG>j_@) zj4`7pqa=;;RUI#!P6`Q?m>5f~5}K5v8@9SJ&+{s4BSpKpq6_U)S+l*r z@`TatS1I?H#EnEpk%C#=`g0tz;;pSB;(Le3iZ4@1--(fZY_c5aIMuM7dY8(K++(0& ziIw9;peUkSoYx|b&$_%cjj^iI?|x9KFsG70lkwnabI$fCN3Xg`f+R8`A}AIo-Xuf4 zimsbq0NE?Y+5g_sztGql?zoWK`SJ@M%?mf_0Zv*Pn$d9hyE8`_bC#tlBxjTV28GpS z)`#@XSi%^DLi5?cn!Wxb&d7*@U27!I;FUdLh3xo=tXDp@z}te%oyz?=HpY&OOA!$T zbpQUnvrimbrNJ+9a#o>@gN$=Gvh_iNsJjyp4b6?4=#}3zt0K&1;l{pu-AX2VJ-48V zv{{yL_G{sN%(e8L%gV~7WO(c~{7Q!oWcBQ&t9Ox;z(fA)7D7raXSptArV=Zh&F`I5 zR8}4_Bgc*uB|R6cc!$d$j-L@-hwXhQ)Fu0O7zZim>dNt%loW2hL_?F1D*_*?TXk%S z&6>!+Qm#+WbpEGQ41e_FlOJ>snL;_t@3?VraH!hCck41YZFQ4Miu9=?Cw9;6p5P<7 z2lq>ai3Fjdv;I^i{zvVLQI%Vp(0yOAabk<4sD7;%bON<_rFR7Rw*tMGzpLaJ$02}kZ%uPS{N<9q__YAx3E&tia?5U=WA z#Ihv)^CZ_eCkKbOyDv+6~Q*OyUzAkn(9C90qT4$Ku_# z117kEJ>N5MaQqTX$5(Q{Y5#imAS05E<58-Fu{NsH$vaq?+bDj} zPIBe760zXXp`f}JJ*Nu6Lf4}}sY7Nc2@4V6u{T^*apx0!tr%et^E+gZ&0e3Eb0>z} z+vIL-W|Q^Z{>>BliMp{lM_6U;wi)kl-uA_hA5V!Pie}2$X{LC$QuM6)rlIx8WgCc* z(Odma4?0z826)@4#X~VY<6F!3^lKgdPF*DqvCGQ3n)?1h$c;9CZ^vrWN%Yc5Vaau0 z3wnyaIt^Ez6Uy1(7nwZp#ADvk9_Io-!F1|G58nU-Jn=Ob(7zlf?X@m>-9DfiBAj#V z?xqp@7Pt7=7izKd9rAFS-2L~S{ODgYtnVD}5|20dhS*{7EvA#BbQ1}VI6_4{{0-}B z!ePNj8IkvP;J(sJ8KHT+_umJ?n5h{A8n%(C@*heh! z(4A)I7kRSLpWx9eEdz1uvFmf|6uGdFW!;FHaH5L{j$-K8kqnKL$vFlTodzKD9n;Y8=U>VXRUPHxjkDG&|ymKb#8*P`0c#)u( zo;r!!>gT=jFQmPi{ztt&&2A-E!HV9`*{r#msEg~7+ZZ2!h$BWXZlMQnW z@16i?0!2ZF34M->;s=5kJ)nuk?XPn{N$bi36pV31rge8^pEU^e0PqcdhF8G!17YXmBgxOt-v@z&^L=fw5rSE6qX3pz7f?q&XJ`quASNU-qdn){UnMK|Hj7bZo+IwIj|(gNTcX4MMf6 z5#`at-V3#M=Rs)@bH;+!2er-h9ebw9%}7qzNL7^Owr}{#>x)FM7QNu4FO-8;k9o;| zOpMu$!+qyWA;$rqtpYvpMq3H2?nRM9|WsYG~2$Cx* zDyjf4qy7DnX3h6tqM9?l>UP%H*tpNVk*D~A=?$9;c%EPJ`NMWa@}kP2pO6c-eX-``s;5_>cjb7YjOByt znseaEgUJH(*N5uKS8MwYG9)Wbu`N&c|3FVH=NP#cM4r%zmGWC>jXfhvh=5hj{&v>M z<4W6}i9iHAFJj@on?KlHna=s}K^?U)hLI_$+so7wHMT~c7bdrZg_)0!zD@SN`zUb5 zw3Nysh;!`UVff!$LrVztHjGb73d_sm1bre6_n-#?UaPtzvU`K`LoD!>? zKQ;8-J0Zh#^93O)3_9hoyd@o2_&|_dPM@^Uab@&WkcCE+PjBowxP?o@Rq++G1Fe_9 zWe@dtM$L`DKNdGQICyduUXCV7;1NuLpz(d+?wh+0U^fUWe*SZ4M@9UDmH{uF;xjnG z$S|89*7abAmK&5med@2T=gKbJrY5p+M#K~5_3^j9_J18-(0s~v=E1!!s{xT$7OUGg zFK*2{IAq`8+uUGKVJ|8jD;z%uzj#bbi~KhxMdyIm(E*T?3)fBCW8l|CA?ThRZQe+VGt^sGWw3$K2^+K*gJ>|gT<&_Z^I5`4HVZW{a`DA6f zg}Rh#Vqa=Q^b;JrR!fCx@tm`z?@4q7{w!$1=0<%ObB%H-YHkLC#q%@9+Z$VdWzLE6 ze|8#&gX$N0Sm@9fyPBSq=bm~LtRQonWSlgH_>)upR~Crs&WR#Vt}H%%Zk0e#&CKufk36_p{?e< zyRXb1!8wu$@6|z!@zk(9Ifkw4jsOT4)GDTdbZev-efjU4AS@BiM43EoQ6I)IM9 z=vF}zZM$#m%(2k8PNd)4H^hj)lcx5o^P=d9SP18mwX^-n9par(rMb_U(ir^X%|&Sl z8<$y_!YpUbt_^O(rW|kz7V6pa-IMgn!(JjHu`T@xH(om0vFq2d!)-W;aA9e%{a;B+ z7339tj=83&9B=z5_+&4w*C<%z6jH&#M_EZT-QaQVf5F$45%QCVKQ0UwBvHz4Jl!a_ z?#oy@etP(t$DS(Y&gTXQ&707r=GAA9}xNAM*j zCf)9Hc~fw!Jy{q#ne>q)(zug}gM4J7k6}2wJ{P|YhdB-WRiZxq{+0<1lC4^=aGUaT z@`9!T3H`bn#Gw%3R&wygt{$P01U39=Z#XNSx_}Uz3-N=Z1z(mvvGf^L?D9M-#ii;B zx7{tLWju!8iuEy0{PU8Jx7r#^1Cds2f7|8_iH)9X#35a>1GDyC1RPfmH>Y#&H%yVi zcRmFnb|ROhzyp24cDxG_l%tY=?*&WWq5C_q)UI0C+9Q67W_kQ@?iSokZ&=_Gu0iBg zr_P@fj|~~Z^j)(25Mxu)Ts75Oe63P#`SjtU=5?Bxt~-@RgSk>HI&HU1=ay zUEAI=bTX?*W{a^?d)nKd(Q2*!Es~?X~W857%{H#vE(z-zs=u8{O+;9=TCOG*vLtQQ%|%Llcvk z#g9pGAZcdpUvawAc;2)k6t( zN=8FjRN3`Q*zwXU|EZ7U2_CmpF7h9uIMz8WU5b(BNMoc=U*#=)JkMP^%kb7)?dJ6z zQ}qFrT0~medFjXUFU^1OQ7Bah#S2 z<@6mkhd-6}INj~aFg=lNcp8O1>r+Wa`%J&YB$HS77o|R4JubK|G?RmRmRZIBQ*7ti z7FU$O>l0tB+D$gsK24z#>--lLHPFNt%w%+nL7613?*$yAe zHv7cuvuG^8$zblMTMmacdeGRmNQ<6yoc0~7wI<(kFBZrZOiHv)y#De)Uhm0kEya7P zx=g~d7ic*DoM||I*hCwx&(9GFG2hMFN%Y0z@OKC@T7XXU1>;qf93;L*7g(m%W-^^CV674# zDh~uWETz)-FI(XL?w9%I zzHd0!&!bH%X1VfEl?t`!!2Ck^@8KPL}M~%)yp_eB% zW1v>Byyl1iVz_zWE8Ek>OTTV*@KA90@s&5xO@u-#gOTXvCl2|${oZj1XctfxzQu2E z4J%L)@LR_%duBgI_-Rhw{_x_3l2Y!mLc7TGi~2P}1&EUjt6EQ$vFsm|o?R=$A^73eqps}>$D7^=6?m^EW|3k~U-DEXpMn2`sih1GX_DVf zxZ2kb+t4EIH@FUvqt(`dle(arz6^eeNXAdG)Y40MEr}?$XYq^AT|6DKJxKy#je#s1 zd!~`#qM>k`{8!3*{XF@#C96D#6+TN1CG9*Lve&eubfwQ)^2n4%RgTc<&$~`Reiuw> zOG``AE#SByfA}`9Wli(``p$jy?3twSw5E-T)eE_^LvD`ER7;L>hsSKv)c-cUI&9(} zXWg2)HF(kS?JBpwrdAcbFQ5P0a_dHze5FK$g`JU1gud9qQs169)Q_NjC=7oX+;C>+ z5j&n;B9GPbA0*J1`HI-o?gJP)nS)W*el4gG{Z(^WGioaf>7LA~k_eAiArj511{a^q zqi9oT12mgCF%x>FHKm~ni%ZIAq13Z?cfqR6+f%*}Irs622{wwrZlQs?sJNsg!=k&V z_0>7nkF`;C5up5mbj!i9#C`fUE>Q`(D61ZWk99iAgD&U1b|2bMt+hBM=jX%fn#ra zMs3l5pQ0dbUZC|Kt#^7LZz-OAGF@KhW-^(i}#hTw0S{lC3rKhKfjj)Fb z34J)hA6flDaPUN8U07@a%^*GPwJhBGkQt1h`zo)C@q!gq@wo`cFqw3RjG^y04+pXhpL!7`CSm;+%h=wg9q8 zyoeedREtC@y*R+n1Y0)zs`RmCp~Pa5y<;7EBt-SX9b*ih)ODe)gUTg%Hw|N9EFBP) zWdV@o5m6fMdy@4_%Pj(gkeNiPZy9~K=Dso)- z>*VS^OUsvfYFlcE^7{HNz+bd>G>`eHzvdlT$s5sZVQ0rpp`AnE!Odi9Zg1MWSx8j$ z!>HT6Xqyqv&+f&l1AvY~X8E*y_LKLx2d-sUTc>o4nsr)@JKT||T%tCAY-3a1kv>s6 z4JF`fh^s7=D!+KFo2Im*=otpkvyfm`Lm>NSw6E-8bvyny@hMTPYwzAxx$FCle9P^- zavRx>*vIi2|Myn4B0$-`1=96|ai)LJ_DZSW_iqjO^SD7JB+Y)mZzucz``&%)BYb!4 z+!?)X!`x!Xu*Js3)!*@W0SwI8s9W%5Qep*CRY_Hqfe7(Yk~F%#c-ZW{Ye%Rkq|gB< zGhtmEi;5DrH{wHIlku0k{p!563DYsCsv4v@!WpCS^FIPzFAgJDY`2($1}$^!4TN}o zot~u|iUM+AuVs=bQHKUGJo(n~D2WmwCi9$(iYLXVP!r_d|Ig(};4WNT=>GpKzf&Gf-xb8c)iRsbahqG_U(>Ex07p-N9{5HqC~LYj}j&0 z&z)NgsqsESu>tNAj*bY5ZG_k5!NFV-Nknr@s+te#I*spl&WpMwAO#3eFY`Tk#mR-pU0=S+MX(!i@K=|h24cPg7g&EuG{!x+?1S} zT7I3@jv6397f}6>jxOE%>&N>I(Md^3kDHr?>9mQmnmKa-cY!+a%qI&reobvrKGNI!ela|yt2aR zG=dlbGNl1P2S+b+``-P))o5yp?=hOv37(Y47oCUI4gR$=!6Y0WPq#NWHs-2ej&PeL zdpCMkk3sE*ycO!YecQsnFCvh6Kp&*Bjn`P`*+yb2q-i`n>=tuXgbLN8*^k_XMQ%Hj z)$gFi*nneQ@!h+3K|X`_B^q~I-2+X|>N>z)-`sj74k$(!Ae>7Frh4K*X6EX!n0s?% zOb`6Zx6n?_FNtB*Yhed(QCvg>hS6eY@csL}Nc9i_TW_t(B?Yogt5@#17xDbL6;RHA zQe>dSzeL^PPJ7#QC>M2QtIb%|%$V4P{_@E zakz(U;0E8GifCY$2w0wjBEAj`?ZY46zG!%NuG-z)(#}*L-Dxz{Reo?eu@bO0gsD!A z!&dEmTN_ClCO}+o+%9}5S`dhqsh@vFyjLLo5_Y_to*qv8kdXBihlaWC+Kt?_4pxLi z1BkLgvOL6l#|pv~Iu5C$%D#}HjgY@ia`2~iChNYqA z!{7BmT>1(s09l0Ktx&ZvOg@cVd}17C$p=0@SD@N^-(!r1DXzQCn^}6=+NJ+4SNO*D zBB1j?NfV82AU03s)TF`-iK%lcYA5(Dk@$zB4&Avij}v#N8GLntfN>;@u?Y0-P|!rK zmw^N40n&v%-K$$%R*60U{_z1G4p@;{z7}lG63@GK`}Xal$>!`gRg{c+P#6^SLKm%$wjY-_>j&*j7?XB4 z^vB#-cv<`7VpR~ki3{)m4Mo&Iky?(=r-+5po+aja`SrYXLAoxh`=H#qb+*t+wgD+% z3*3=cYTKSa6U*rZxshRD5OG0se3vVAl1ieR4$Ltj}0GjJN-kYI24 zuh2}dEMJlMjigsCJ7JP8Ca*oHs&EA6(eB@k~%Ma zJMU>|F(|~Izg>)V3yu@tr0IY2xOgKNgY7s@pEfo1^zh2brK0>ISE!A~7i6E0`f>@K z*$i*zOb5=2qS;Ec6L2e8dj9-*B_$;TLqoPa>)eq;vK$a;_tZmZjyH6BgQ zj=@P;24o$fM}swbs`tmx+ES@n&}dZcD;Ce^m#76P$O-52%(yd-TA}c7O^%=csq*R4 z*8Mp%ptN$O@up4Ogw_YgsLR}Og^*#cXOB-w`u!24J$mNd3O7gg;6^|YJJMm<*e}G4 z6S&Hj%j<+t=y-rd1F3l{uTa=K*nGE^t9)k3pB>^86H8|+{d%jJX{_N60UWYqyax^x z8P)KkeC{HE8L3p;T}tXo1h0t|dkmE;q}0n_zW)1J5MH^f=s`^F?` zq8JX2i{zZEpwM5)YY7G4kq(<-+kSIP9Y9R}Uxv&Hq3q+wkAz=F$$$z4vRy5lBQ#|} zr=*1QDmMN3WpCSqUoIH;5)$0%zaSE^M9ih`AG5w&)I-x-$CZ$c8Y%8rglx8&kbY6Pd zV=gP_xrUz&8S6js%{4`$hzrnOkY;S`-^Yz=u`L-6F?tbye*X!G{`c)kZZh;s)0!m6Z zN(<7l&#CwO?ql!Y-_P$jd>*}txvqI#XN+@S}?gnz}pNJGtB2n6cioaCNhBaug8|78VfVW3_g7 zcXpE$6m9GWz{|lWBOUh2AHS?u2ncj6wqIIl|N3=!U6Z=)BOg%!EBp!L3M{MQmZ8Fzg+D#~ z90>8>FF&XMzyJC_w+E_at}`SW8XC^4kqtOe1<%D zsyXHiCntf`*W}EVOdX4nPaaCwugh9kWau|{eECva*m)%){5Ur|{79+O*gfmLnYIM; z)@Nsn1>8>DWXgNz+$?+{9+P z+Sug2nIaF1avb?I6TkB;KHjW9*RZ9t)3ePhKKY^>;n}liCH(fwhMIG8bDQ7-&g-+P zrBOSrym{k|bjA$>1?Fq}>z(G~H4hz6SET(OeXuf7(9Dcya^StXAvUSj+Sy z<&LP+7xL};1*}CG-ZgjG7Sl`nUG_UV@I-Le(rd?S16}sFT`q5QUGrlVqHTaAfn zN;vVZj}~paDNhtlb!lJu{0^_DoDEU3wB+*MTny*c&NZ2Ci7lH;dB7TXL-^jJPJ8mj z@Ae~|(npLAKZ+n@xh?6(RuqY0dIIOh^R+stut3LEU+&QLS>Zq`{xrCX| zN$JlsZjKPF3L`$w#R`Xg<;oQg$Ht(%JG@_J*(t(EWz2_X_PMoYLa*EdC- z7QX-cZfO+Vi4*c;g~YnLxRJ)0s=(O>owV)j{;Re3I&sZ}u9a`+s3 z`hugph6atK`#d6Zq>oj9SIymaQIz&av0W%^S?`u8gQ$@?X1Lgn?r{Cp5rQ1e);zOau z^jE&SbS7U63?`*Bs|zCbnu*g^*U*^kTf%&fSWb_*QU}3>#*+PL<*CNTM)bl?)d!Ya zjDwesA?kPT1fx4&XxUM>y*9PhaQx=@{?7XTW`*a}`9x(gwyA=8! ztoR?*8+wj39(6Q^LI#`kyuXzw?!YkWx3|Qwyt*~!&mv;kj zkxz3pQ`z2f1-k#0@VEN8IIS2lUS86?&zlVBPyPJ<&iu<0PA$Wg%*;$BRaLPEIyWH% zSp2rx9z{f~?Jne*Pd0?3*F4%8^FN9TW%eeTYKp3_yuY6Bci^4R*XHjiSd~@cpc=E@ zt;o_CM0|V|PR$HrWqwQ08*R%-lRSIoV+E zx~ObR0cN(qNimwS_Vd@kWvk(zY0R*H%E|cowpFTDB7?D2Oe_DNkU$2PBsdA0*=mxH%_BLsy!erZB+Z+ojS5bI`6 znV}I5HI8I`uCp0Jb*<<2%?bG1azQ7eTIA(Qg0WvXY>!!O0D*+ZuM^0D)Jj%fRb7$I zcOeMs#lgbn8S|2mu7$7Py`qrCp3LL3Utf|UiC26jjl3oZDp%`B=Z8uKk<|Qrs)~C{ zbt~0J(QwIAS3@ZjI#Z->!DiId$oL)58F^vQ;`QOf2O*Ohq%brL63cOzU%zBLPTQy! zwp!Tc8;8%IUTxU4%0WiM5u@~OH1>5q-X#tpI~7o|{E4)B|2OHCgN@sZKZ@H_5_RiG zFSdO7A`2h0cDT1<4qeb|{NXWm_(-GA-lprb9SE*3N8cQ3dL=yu2Oou&_iYIEjsXAa z!(BTevihTuYJdO3{VVJ3BJ`K;@rm0H;NW+YMtTGd%5VpJTjpz%jS~Kcmo3{9G35pn z$o9tfo5J23)-89>5BqM7nCQ|%W`9^q{o2|p2kUTI9hX&kDH&HSKuFFI^ym>up~nTs z;jqV#smM;94>B%s8oRKasTV)j_2u5$P30mOU}^6((U zqAlJOy77E}9t$nMUXbVLeYEp5e#=lslZcE-@`PaZ{&_UQ-fdb$ef)SnTc-fq@!~== zbl#nrlB#~Uxvv<6ot>RglBIYl20df1^^ObZFGsRSGmrVKlkaXW@$!g2zLaoU+}O6CWP!guf9H5skEZ#`Oh(Xun8qq;@X z&C%8znv70~{V75U#xUqPuVJgaHo6r%QVjbhSITw{=cJEh@7)uh?RXIi0Y=7rnLa_l zunrBO_I8!_mzU_s>PM!S}bSQ_?JAwkICUz4ZJ@6CN~Dd0zx(h8MB1wOA9Vd2SW!X9WeV@UYkcPUZMS zrU=b*7GwA4miYfFlFzbAIsaf!;6361xn^$Z+FT=tf;vM@4=sK@p`1gaNrfl89 z0RViz{RQ<)A_;1YKDmFf|D1L;^!dTt;1t0$H)UmIk)ddd9AnD9cw#A7LP-HKU|Jti zKvuun2C(nCxP(OF=k>3bI+i)n4!p3i&=wyTcd=41I!C|s;~B;1yL($JorHvhAD?pH zv@9$vv}1Bw8U2i|4ce`(VSo35%UqgqwO_VY)=YwN#l5Jw8ySnxqHZntl?g-s*olYe z$-DSm@iAdSam~e&Ip_IXQWb3(GI4 zP^V9yZi`PySZ_PW%R6Y<@w@^o{>r(Rz26yS}!F-Uo3yT*RFbksY7pazn(C)3S52J(v* zfzG2>I73#S4=wp#%>Cuz@@y3@bLqWB5x=Bs>89ppW&>(3B@58wt2W5${pjN2vIyI6 z8_BkjnA0IU@1afS6-A)V1L+*BX-nqt?8{wbYd$uR~lk6E9c>{2QkHzqgRZ=hK`cYfWPsV0_%S>K8uS(dr_i@6$Sg5 zGj{E~f`XKAB`gxjAVvZU4^Vq|)x$&V@LGl;d?XTwln(*0T? zQOFc~Es7x+a01Rk*PzU~)?O+{%g$0a_RHM?$e|uvFyl+aw$wB57!@0F&)0U{sL5dzS-Bk3-4w`&;Q$Cr?^jNY$Ay z0kn2aMTKm+YHyjroap*Fs!y-R{PxJNU%$TZ(d07byVd)N5*f%h#iOC25rVc|I1?ka zNv{*1BgRFA1;s?#LF0mj^tlAl73%>l|lZwvOz5g#9awe4Vk-+ATp*5t;|?@G$b zQwdJPWz@&HRD|{f78u$tO1M@s>gAL)`Mw}sn5a6V*cm0Ye{cY+ScO3>F|LI=Tz zmRT={mXwxn{3!lL#{5Xd1p$LHlY9QplsM4#|20Kwp+{K%jG*AnE)Q*O(N7$Y8yXrI z+Mt|-Ow@;-xp?sugxpmF1ID}OPxG!G2O`cwrEy*ErOQ6{cyJGavG;`ko~Kq zBpb27Z{689+T0$;#}md|0M4Koc4=nXSB}VNeLs2;tq(4L|#$xZ!?B3#tRs>M#zTCn{nkrZDw=B+n{X!ySlw#u^{Htp)*o}%4GS)!=fCu z-M%mdvIz)K;I3RN0T}Ex9jl1KsP-2Z@|p^!r>D_j`sB%z+j}e3b_Tpq0nYCYowsR? zJsA8%0aFgeOSNO+@)`?=e9dKk2a<>hj96t}Yp(~TVo8sEX>FbKe^)YVLgGnj2cuDx z2Lvv;jNo(qV%y;CY`)~n_i6Gff8U7mSRk>30gR=jn5@g#KfaFl@@2+{4kR$yY-ps5OGxO?*MQFQLbv&i##yaggK%gI2+Y$>hX;FWFq=+{ zc#btf7IYVwDG<*%i63KOVS&4yNU};P@Qz+=lpr4I>+kP(d?N24@sY)@ zKdQ^_OJA{$t}b!Bg+o)|V7hs8G>ZKp*&+b&t`kc`5#$GkfuKMq5}mkAO-%<%98R;G zCaJN-{Xs#x^x-z1eu@1=<2Vfa9Y)w7G*)Y}ZL*ibHf=OHU&WUs zYD2?(f0~*R@J9%1TW4o8uywI7UPM6qe(isBC{|LMy^!$i+4RPtyE z*y+3o{OLPDqrXM5oMN)8k@fv&s^+}PvhZ2A2z1-p3l;tRuILq6n{pk}htz(3d1*va zTKi{j79BcJ!H83Mfm&O&j!Dv82F9M>zkl2E8`Cf{Mov%P-9OkG1F{0;Uy#o)&a$#1 zP&k=i-RZccp@EIMcDsJkeZGsW)-3da+a;gv{6T#aBO_)=(XMpG7=|JFYuC&mYSH0` zR?sLCiohfQ-6nLT{_x=(3>bJoaHORk;O%lef!m?}^5qLfzt{0kOEnMi3S4Jy+_kb= zr=?O}G@O&$`VLse9tt(2re!>{GTpn+OE9s=ynfAI_~gXV;hx}8c_H-8lZF-d8qH&* zLi&v!kSoXY)&5!NkA3zmXn)_Q$bRsfO3}RgCk9$(1Z5|vSXg490#ayXo&YWk9nIVO zTsAHhUnqt2K@dQTb3HDXTqTk=6T#JoPQX*TDnK?t?n0 zU)$BELTaH_wdcwzZuMv0<_-!9VwIL2TP}e~ZFPOU9s+)CK0T%{G2txiGw#(Z779iQ z9Li=a7UCVFkV#WtrQ8Be(+p;V0EL?{wmL5k2n&&!&z`@RaW0zSA{(d^x^d@M7Yd`Gr(jYswfl9GGiCdOw5!Sy7AWGZo z4jJp*ZhoXkW)z%l@)h6bF{S3Zw1S^Eo-~u%OSS^G!~h*(^~yKif1%7}ituoIiZY=I zV5iqYPHDbrJt3cQ)$n4}TVNBMs&?M$dTiZFzcvAB0aKPJ%N+O9FG4WBqBH??7y65? z9Myhua#-Mf3V@`#lJXlS0x$Tc!y`szlqQ9Vtr8lIPcuc-wLpjr=C!po%Y|IyYG$Yx z;`&WVBjskDm+mdf004vGg~$2`Sp`n{D%Vp}z;~7ki9nV2K@dRtS5z*!bxIuzmU{>@ zaN_6BuYjTUKlnq3?Ddy-9b5*?|2{jrL8S9?z5keYo>7h%-ZPXu0Or^WhQ=McGnX!% zhAw(puf*PFQ--z`M%|82*Yf!yUR-dhYiOXe9`BHoAb2S#k#t>Rbc4XUO}B3 z|M~9KHG6wL<8GPxa_Tz3e5+8(lNy)l=;&ZbZ+B=sw7dGhp%#ZkhKJWelL&*wQsWVl z31#6~$7mbfCjbgj0p^@;VA6}MyRm$2KMr313WR~d(yGe){TF3?Q2{&y`W78#n5pw02eq9H*gi2FN}!X!Q!csSfOD z@bWwO2_1kn09-@2x4kx&M@|EMIJ*$pdo6}p3eCgCp;AhilKw8Z$R-fb5L&6l%&dc` zPMipWDKza)mKMs*KfmA<4I6F>{7PjU3a}N?tuM5?xv|hs31B+ZK%n%j#0qe(^X`(6 zThcyeVIpJ74sN$IHMfB;GB|g*IA2g6(B&)UG|C7CRTd@>LNa=sfZ?Z9fb~GJJ=j_n zi`er9eg_p@0G5~nlPyLg7*r(Se%GH7stb+L{h5>K=7oocdrd`MSgk$Ak{FyOQ4g^h z4NMXZdR;)n=yjn)XplIagZr3OYZM?=U28U96{)C?vaT06IzxfH@W*O{CG2flpxP=5EfW%{nviBJfNz z={&y+pl-Q5qt9KXPR3|VmY0{q+*YW&9rf7lOwjziHRDBBe00A@KVL!@+0Y=5-VU$} znN!^L#6ise;Mc>j;)K~=nJ+CZHBidEO3eY~-_q0!g8BY6Fi_%I?_r832M~D;bRFtb zr@|v6$qYVwpR5ld57a!TaR2_rXvT{Hz=5sh66sHUq9cA&LysjK54V*a+eeatS|I|xvAA)&{4g+%jXAJvj2 z9+s6!T>1Ldbre`BY`xI@k7C|w*NYS^SK3*Qr3&&H>gZU1_rRaGBZ!ZWe+@h(5d{TW z^=gDv$iI8vxWB;S*%P;bt(UP}sGBVge{U9bLwjTUw5yf%{+x0j$76WYnm58WP z|0UcXKZr6QZq215EYTubYz8Xrh* zK*Mf*BEz5A1gU6$@+D4+@eOOEtELrVhy+tmF2x$Afhh9|C-L69rH=U&xf2V}nk z{RKzHZ{NS$ad5`P#Z5pXMUR{1wzWf2mpLy~NZ{eSva|&Y>3H<3ot8aqmbQaanqd?* zD0d|Q5e16(HFtOSsP%;B&uvRroE+xHPO$A2UZ#YtmNPYF1G17`LcYGQTr}8}-r$ov zv4Vm^SVTmj_f7nb_*NiFIJmgj+1S#W*6W`Er3y3xhOh1SmM}V9vx|rvhiU9)l<#nr z?`hEIu8vjt+Hr6oyH>`aEIxVigzETl^FMnks;UZ(j=8!7NSnpx?0C!C*B2KkA)Ojw zaR4V>HWzhUW?bDD`Z_G{6@GS`BD#@51B#P+rsm&+uxt5ozsz|83!0O#br)-)hl3O> z{u7FxMC?k>G}}8+Fv{g!x;Yt#&Cgu(Kicxwsq_*SFs@R`all^%y1)!rehJUzWJRnk z(Bu(t@aAwhTK)s_Q&SV6EKTqQCIKB~s<)7xfDR|2zLz8=POG{JoxG|V+~nSFG=p^{ z0q&=XZ)gGLb1#@VK~0gHyvYh`OAQ>}<#<((+4fUmjgxvJr^B1-q3p$=d06#M*6X5e zF~dTC-i53?gD2)>M9C`8k(QlJ)ynElyLt=;@YGMA7_@T@Y5}hlc>npeoASKBD_d8j zV$J*Olb0`}K!cltxd0V%2)N6rMq|=_{fX-s{QUg>q#O)V&6-3(AWppW94)B$3aV9G z=^=+fs6h=mRk2=_U4L#GfFjssuC#6$K+F>N7U_Q!*<2kXmZef<)))5p`uN2QeLJfh zn4Kkt>1#*I))N;_)8PI(FsM|?9$`5CS~IN89wYzrFLjzQQX#TH7$QK%?Xy|C_SdA5 z9BQHaEFs~HfWTK!Et@EaW$0SIe%(|mIg6S(s8Z&DEcWP=%T1HTb`g}_Sc0i7yZC_g z?>ETvwueGv3DhmWGv716Nf!W{R zr#gKaAdJ!2ZJWpcZt*!ISv{+i6chY1lvdE0@ABJnRaoa)J=>Xi$1-AWjiq?12z7 zCc|YeW$r&|q%C2T0}=*ZKXgA+AWU>B?l~~MWRm02Bn*M0iFM(~A<_#`SQnDsZsq(V z#gr$PmGvOujVAjrE%3?#Kw+D~#RfiFkb=DZKMD&v)*-&(FW~N{U;?j&86X5oF&pp_ zpnr?HRnUU{0@b>K>#f?JBsHk=IfaU0va%RK9)82(;QuhT741y$HwB`Ia-tu`n_>`K{;Sw7OpzpEHDmRi zxxJU&mt^ya_F*zZ5iTfGv@oloTG`RzmNZHvdV$DB&B)lER{=^h*=h0iSsi1)9Zq0! z3*ZZ3jb=qoW6Z!bL78&NS>OJZmDly|CJR#Y!l^18C}%c6{V;RDumXoP(eD7*4Za#2 z$E*DWv6lfw^|H^l5ZX2K^M%j@f?T=RFUZf|2s{iL-q7A6>4ocT<2)6cIf(+STi&bk z=`fJwJGm!IJ)niLBvjMZ$A=R1vU71HP-iQ7@NfWh2bdOs*aUU$mG0+CkVA-`E51{E zxqTG#=n*!xl&7h=84uCQ(F=xxiY^|?$@>o<;5pV9EHoss(_#>W^>% z{RifyiAEz`-BZ9g1wrDN0SZuyQHHeb5-vpgu3mmoIu%Br^%sn*z7S91zjXgMhdetq z^f^Wb-m_e$! zQJ^v>O8s|tcT+?agYt{IpN#zv#OOn0uU#Vq=Z8bW+yFEZ6eNPS29Ox$Fu-)D4VV+0 z1<8#N(2j^fPZ81YtMYvSI9o*4Dh8ZGFfokriPt5$fLa4~sP;o@s3{zxl6}99jzq{>Z2UdbMomv22LG7~m>%7DCgv>I6yStdR=+6=vH>Xr<5dl43m76#0)2F>wH_+r z2WW&MFjUIjTpU!3QS=HST)_$m3M#h6^LNAt2L-LZ>J0&01-FA%lV;`z?HMkpoL9Nl zbUI*8jSBx(|6_vuH4)U01RD&J8-zo!T$<2crPEjyX#1Jec-A@Z*CCdLt-dm9YH6{< zo5b~>8S%a*3Q9^v*g}|}5Cr&5piX$7-QaYWWI{*KJ9h{&G;BNtI1KP?Dc`BLwC+Ri*eo*h6z zq6HTo4$MwR!(u1nN@nGH_{m4H1G$Em7%$yxw;u%hh>a$E(Q?6cas?{&0I*QxcCSRH z&Yd91k`@OiWk^741NJ>9DeEm#)W4M~8>p_Xj{J3CT!BQ{eR<**x2PBCICwf-e)XIM zUOvUR1h_3!L{CdgLvYE-j6N_B`7AKJR0{<$dkPxFK%o_-Ua{>=PZ@Od(U5Y|L_S=Q zFRFC`OazWPwX%{C^em~~dIxs&;vmz(%t{6$Ga>3Dfvcca2N)7#jJeO8!Rx%T$A>x| zfS{-ZnhP2RKT2%wgDqp<8+tFW>(S$AVW=c`qZ86ah)okil&Dn$37s(bIFQsP!BhwX zN@E!H8MLGWe2hA}3=}#lYl5(gAgDPG+>PYY($dqjv%il>NJ*K{oT?iVDn@LtL$fr+ zqi%~^=3;ycYCeb$JpBBePcO<+kq0=;xvCpvV33C3Z4;e}_ueVD>fZoP0|7xvMJ2n~ zoN(ghz+Uvvoh43M6j{j8zkMmwf>ojl;{Vr!+1m|jp5e<;1(E;zZyKF=G3EW#^FsKt z0|EG~vQ+YCWF2m8CmGbp`?~%4b%#$UA7O}US~8!TnK1?O2K5u}4X9%N^&$M*TY@q# zWx_tq0Q;wtZ-M~;vuyzrTT^QsZ`${t!&TL&+rglm21W!&mWs17*vDwktts~}U)Jj( zO?sSS<6+xJNH*Nvw-&h)=GyLR^K~B)onL}?t)r%h`4iR7_ zYsoG?*YnwBssvjP?xEu`?DMu zPU_Uz+)!55MeM=4251%z>$7)7^1+%jVZ{Zp7{dn~f#|>WZ{=jJ*oY}X`FgN6si2jq z`MZri#FY2WbIGG-p~&(3oi8rL_ySAS9uG~X0L%%fjf50;uv9v>-FXGf6QF~GY;1Ec# zq&R*)zPq~d7XG_Gxy9Mo9_GA%Ki*#s2gyqtF$j7w_y9lhYGs=Q1_ZP>83EHriu-(j z{cW$C#nPqO)VT|7Pe>F0hN~_zLnHi#Mz}{WZ@i-`>dp?&OR121_tNf8g25P2$v6l zmPv+6>)@eS188Xm7ENGM-Mx4zAo50wDT5QMX=H@mMK|XDqY>W_w1P2(5g-KH$ntch_b|P-GEufRoXYW6#0rx+` zF-8#2JO()Naj@Lff+G_qZDUq(aaxqm0MCUG(6-1feH}3PCS9qrC~C|#`m9&asUi^) zW})jX<^BYUFaEJ(=|x2+0E)wG6Ttdh!r!n(!8Dj5@F}~qR5f;xvv>X}eTeui%pa*@ zLPbyxfYOOgOthwbHA@bqZwg`<=nk06j;#cAw6)a($tvuB=%d8pUFr&}M}=>ZEn6T} z4tM5Q0D<(|5BKzFqM{1`7&ITi4PdueQR1O_?j+Drp~J%lC}jw$&U<0*xEsOHFU`Ka zxo+v=18lH_^Ee{PKn`^*1ctbtfg|v$>`3B(2SxoEU|Tf3gAAeVO%>b4Ige#0dd*g_ zV=vzNOz(|*SY2-=$=wrLY1$F$MG?f=E16;vmAVK`9V^C~31H2Z{oA0ZQ+tKSBYk(z3mMR&4L;yK@xSoKU3*u$5iW0V ziavJG75eM#e;2`)ZA&M~+ix1XVunJ0vz`{*82J(Uubax`h;ZSMRF21bQ0fsJG)V6h z;)%0mEAe}|#BT4YMA4Ruqr-(vQ{KQ9#K^PDDk%|-HTQLPcK+0|l&^=x*SvFw4Gb@k z>^=vwb&UU7FY;a78DSMG!<{AU5;x!`R>P->iU4coFIux>|NTTdfx6SuxPI*|+I&@* z20&K=IgkKk$g%Hi!(l31XWESU|8fh~`1DU@HtJ%IOyTl!W)H1h)oF;(rPZ7# z4l<|#bP)LOeri6Fk*#3g@}ZmcubWfX#67sRN-OgjxvPU?yC5V>Mf=}XdwB5q#Yabr zQNko2_uqb)Q{(Z_MwqN(Z*#$qiv6otMC!Ud7<`qAhmQ#WAh`Xvt9*tvZ;x(fm=Fcz z2cf?mlu-YX&uQj%q7G6nPt}UgMN~)g_g;;nGb8$Yuq|-`-2?f^a(Qy-f%b2yOBZ2w z|4J&*ipyWA$iiHW$>$6wU z;D?WPz=#$F6gp!H`RugzllXA3-qq(uHPG-;Q#FWOC^^$|_oH4ZJc&~Sy|26Sz8gTY zn#DpOiR_`_HHmu;yBvc#W?0+_(&T1+Hw0xm8vP~AjVoF|vw zn^n$0D|0$$T$9%0D7%-KgXp!(_i=)8;Nn+*w+WiVgo!$$QMZrtxD20BB|XsNg}n{{ zPe3Dz0(F+~_FI*LONZLVzQK@1TQ`%T@l$jO^Szp}JB4SRbu!t8+8R-}`$C{Xr5Z&j zh@hB)gOd~W{UQi>F)sgZIfIIYkl;}5was5Z?*e9F)6y73SIC;I&s5mEGM%|1*S`1EY^}*`N;v0bNurUV0w@0z3=Ueq`5|o%DT= zn<&8fSjmqXj5jIkJ7U!wpI$<^wt+2u;NOS>Dx(X;2h?xS*4oy#)0v#1TWD!LRwZ@h z333rC+M&ilxGc0Wco3oWr~;tY|6JAx%VmgVorc+E z>-)Glf_j3K69oQ3fN^OzZh$j9JUsb3<#K5_xisg6D=?55)M~MqP$bEdMX6cE6Sp@a zgglWk2!DNF7#scuL3(L&$2FW>$eLk}whl*Mq_-LOGX12B33giwKE6$X(0HWy%4B?3Qak+Swv zmc1qDQsjE5!XBd6HV}y?xo9drQ?Il=3G(7^Hx8n! z*PXXj#!lcfYh$mSqm?~Jy*@NZgL@m!GSdr9>UF`t;v13qnT)KTLd|J&YU=2&S^eBB zt(^W8o=or~G}Lwe70<@^>M`9j{(99kc$B6te^xgfZeilQqw=$o99*33 zRk=|4yCQ_@wk_B`dVJP?f`(=j%=8uQ{wDlx?P znS6N?e zzqJiA9>%Cd#xlL8x|=V!w>{KoeF@(52^k ztnK6eYUUHJXukeiV4Q z(aPwr`QvONSrXt*Fyal!jgG<~RbdZOH~#S!DC1FhG&uRd^!GQSCeM+-p`pHZFYH== z9vL!j7pBWjC)7P4?9u$=!9=EJuOnufMAj{5oR1%O-lap!g)w{M>=mNlv1@JR65O0{fU)Mb_Y3LpbTX(-FehHo2N`>}wy$~|*CbIdiV=EN~2DkC&nWNSb2{cih1Tk~FqrLYsG6Va1=IW8rW z2%wo)+4t!3qlK$3hbuJoxx5t)h!+#z5qC>QG~sZ=njlbL%ie<1xz;SlMa|Z8({l3^ zH*%KnvGt-({M~}hZ|TBku}fCX*cRf;$oum|*S;Ru?UZMn?E2X0oXWu1_!siRQiYNwpE7dt6t^ge!gx?IoBNN8mv1N)2U?UPlKhlKfj%{k+`NxkGh}NI#8-`{P=%~`l zyrza&FE{JxGxFLNcRr87cBzxR{T4#d^--s2=CTB7YK%%J~MZh!nkFLRaJT471RM6JkWN=FY4$i;zHrbd(+#kpQ0 zXf)ty9|@lC`m{%f_{{7o$D2W>kkLiZnY9F!GUMqypthz69~ge3Q;%&a4J>3sRQo7j z|8K66862a6;77)Jr}%Iit85H{3{At>_ZB);!KaT|brkj!Mh8Y3e3P*VJBnB>wZgnH>yn>RtS>crNmQi>CyP<*FlEDzLeS#_sAJyZ&!i4{!i}Ma{|r+96_W zCy&!%*%BVzU$dnATGz}5O!7B|qcH>I*WB&Q*BV0j6CG%!!cQg;YE{D$nG_+m?)K!K zXw8)9&r&%TQvKR;NqPC`0AJ?_F_$)>(6=yA@xN`b|4Nhnd|~U0_<+o!C&`e{o{-P) zJzGDBsed@7)F9)9^TqHy4co!pgVT*VIZD7sdzv4|C7`WHkZO}95v*yD-oeg2ud;xA z*pX;>9z*<3Yk3mB~Pg5h_vVxQYU+W3vY_FArvw>aUWt_ z=PH{t%!P@FXa}}r_FJ6pPkh)&y#hqzEPcSLAMF008?wP9ap#yg%vjlLykYwBB26Vl z^Mk+SWm|1V^7(ho0O)JNg}&O(@jjK|`$p$7n|ptGMo|f7k6{A)K|-}^!CW$x4n7k* z+8X2+q1?aXWK^D_jX|twXSv@e6PQFkaBU>;;m^Z1-eGt%8-GcPP}U2Zj`SQc!=&o; zXZE9G`RgvZM=~#>33N&k*YGlR;4LR05@g%*i8f-{Kg46Z-qM>RFCVNv)3Q;2E9$7P zlj&;97_f>DNku?LU*VfrmCu7u`;f3*zg9O2BYG+{LRNF|EFK>HNT((#oaAxzBwaej z4;_|pe<+2(V9m{sOa2p+{$69LM*@F>I6KaG?KTW^aTJyap3w0}eXTW04eZVgu@QJh z?h5*KoB^8ed8mU}E2+^dsT*WoyOqIUM%{Jp+gO?dRM==2HGEgB(C}k-4J9Z&GR}>O zstPZvual)dX+vle5iFFL98$%q(_ys)4tZo`Cg%`zrW_3$xzqxB;^VkDPU}>7+=3lk z68ulu8KnEy|MXP{sY_=GU*CKjrl79WsBUvg)6Sj3!B{UtHd6zyfN1_XRisqH`YlbM zOspl|dx#makEE$2=RxyU|PEKyE=&0mD9 z{ut24_nizUo91 z7I}hQ2)bs;JMW7s6#`j*9gm9JePHlWG2_OZGqtshld1~QpWt{?FVat(y9YnL`tv@Y z7sA=_%fR?N5jEg}@drmO_*mgj3q0luX2Vs~m;=u)qoyg)uhs_4V@%;S4Cp%te%XEv zN^mRGA&!a;u9gd+KlVggWnvOx>cFqk&8EY3)bF!WM^H_^6SR`ml6jqGqD#bpjFHP{ zSZq(W$qm)GklCCLr(R08+rZ3@i#+t;qYs%e?C$%B!=xh|q)_O&1I&^BY~4WAOB2qW zA_Lk@;W;9CQAj4nRr2)%>Uqzc5Jpq-)0n<{ByQ9~X9SD@p=tC2X*HjZZ z@Vxp5e0+RlpdC5BIMMBO_Kxji@Ow+ij>|+PRXi}h|`TE=XRQqyN3!7tE_znHORQr+5?xFEpzguOoIG) z2Hbu!4_Z5EYds&MyeLqmsAum-sZ-4As`GH={o{j!gQz>ZtK7}%=GUjz9K%8!{zc)g z*_*F8uTXr#sg6_=6K)A2_&Y7ECnHjO3wUnZQrm|SPnSJ^=XBDuBKy#=;r`6Id_Lz{ z%d^jHnY@dMJbnbLi5e7X8Pwp)8*j3meDPPojXGv7M0;!gw< z(c)lyL)GrvH>HA6uc5Rw3rb7F>jB^;7|N7tvDSR=i^)ES?H-FL{KCTMBW)6ue=J4} z78KUV9<E~U8-~g$m6V|=b$o4RpsJ(q zE&0dBPgA8ez7Bs&&TZl|LRGnZ=J-{PZx_=mv2LsT5()vV^4(Z;d}f~xJ(uy zSueo=0@ivV^w~r7p=KX&VM@5ok|FTe0s0Dx)dBqQCOo=4t1POVGho8;Oa7oY8S@)n zqtPN0d`J0IKTU3#26;%gzVYwYtXsEof;HLY?DIzr4c}%<^M+>p5k1#(EM4;2RkoAq zDwzt7HXfflqMTWhVc=G;zp-pJx#`iY{ERbsyyy9|hXw9e_2p2+^njWVf!CB+p^s7V z^OJ);Wio-AoBL{p#{EhP6Yy)I4?O_qK|J~vG+xw~2r9|2q`(AYa+pgff*(m)`{VpW zQr-=$P@VdE=Mx#0Q_~v4^t3#;e&zVs?07F2gR3csfiKA7k2OZ~)Yq3bLlsog7wgC- zPyt4)7!(} z!M_8>fX1b#Q`?}pQp58giY&e-P~{PXPI$z{%m zXvBlI(h9yEOT2ncxNl^AU4|yCfQ*c{j4V=zZ}Pat-#jO+#j3N%g1$fe%L=Ry@PZb% zp*Je!UTf^ke%q#~vmZTVkTg)IFZ%e%tT-@VVUHfwfslrJ)Jvn3%dQolHmt!3Q?wch zTNlU6X3CZgenhZM0bRjyw!?f{a#`lo<7X5!Qz-*{{v_4@vB78pUc!zmKXi^iQ&%BO zBC}9Bn@e14eQG(B$bYE+W1;hPZoO+>v}l2RavDM&R_P3qFuG~6Nl9Py5itgGqX$c3 z;Oj*lY0OFE@Op#T$B%KqzhDvc(N44n0U7l^w}g4?Sz=-s=zFx()YOhl3C`r66*%9! z#T7VGa{f`Q&l|CZr)PZ>AKwuBM!M1XL0@71QXKxyJVB~PM~^-?MXpbD-tay*uh`|H zFW3QzF6$h+hqFqLC>n6$)Ww#cFX7Rxyz6GT^pJ=K7a~zZf;P!JL=+sS&popZVp>vhAHAk$d|`phn9_N=9&BGBKrjGY^ZRqnesVDIB{XGo*Jjzm6QirmKgV**E`X(4CsK5lu z`1o8#-$4P+A1_-!@F`palURGai&S_-M8tyoFlvv7N1#K#@7ezvpb`Gc{)WXFlYr1z z8yD?-$*63>!_Bh>>vmMj1e4t;Cb8)K;Z2R}J%KmCF}|?Ud)3A1c0uz21!Dp7w}_!9 z3buXpg%!&{@iD}UeD55NG7t#W$Q0Grx^t(|Un^k>oB$D)!U3=i)+mGOW_`ojgN)_f zY!$ss;7pnxX-;&(^NU}&aXn_>8xis+_}H^+$KGvnFh%q`jxEpNj#D^mZ*c=^2oWcd zpmX+h_lylwpo&1gD_;+zntAfq*D)GAUZDc&8wj*He(@KfK>;tL!o~VAcz7tngXG$0IC3Ai&brsPzph6X~PoO?AWN!-8HE5 zEgOP5Pb`+(pLdpE#(T>tv06^O%coFCx`l(iD263l?C;FI60`kv_5{f= z@Y?jCJ}Poa*!A)Kwc~NAB%;NE1kge~aFOV{X<-G-WW^!a?OG(TBN(AnZF@f+cqEle&qh9@EH7V&}8o%b0=95l7Y zYzj#l5jWx}9)=`vf|w;R5yx_!ql%&KFP+eX9GG|0cHuD5n z2eld8^xK9AJX=#xzYkKBM$Z)A23 zL|{}s>WGIrZ7dL@Tt?}+i4j-eph?qB6x49zbuMh-L5d|qoEErxusTD2Sl_#Vd{eVO zITEBwEo4GBAg*bW@vXqA{y&7BcRbd6{P({XE}LvJGBV1h?7a(RW^c(zW~8i(?5#pk zW<*A0Q$|+V%E}%^$O@5pzpr!Of84*net(^F9_R5mr|Y`D-_LlB=R5q(#fpXy;>%vT zS136fRii%^{kulE*O63{yphhWMB&zw)7TqB%Lf-7hnn9Y_d{SL(ws-_s=TYudk+E& z=DE@ZUU|Zgh5BTvBV)w7-UhRVg5>38S3=gS2lL?BM=#^}8s|RCdrqvQv1C(B)BD|= z3t6p=C0C*tr938?g#en-JF9r;l2rc0eky4CCS_%9{{2E3PoPte0l3zf26u#d*Me`o zJdXrzgK?%Uu+}il5kJzB8(dK#EI9IMM>E^xGhH)^rcz6J zG_PU0iZ`@H0sk-1?;&kvZ2!>4h7A_n7>GTOl~P}1q~F-Ub&Z)JE2+h~L$_KPQcupd z;c@0QoQ5u+NbtkH!RRp;T_bBc#Uju~t&sE&%&!`6b)P9%X8qs)a++qo7|3HasnmFp zjYo+2SN><-xO}a`B^9_)pm$jG6gT)fdRm?@=|uE-lGJf~-golbc*+qeR@@b|Nl69i zkf9{l<<#5d)-U<1()ea9uXH~7Kp73%D&!DC!cw+`!3seT06SrWC}4$jXL7lI66Sv^ zhEKVOq8CO~(Y)D7F*#pFuL+f?R!4-G;DsI53z+zI82iOA$l8t_?q;yu8797r1B1l`|mlFmc04J17czKE8ZglDLeAs*%BGIn{ZN%nzo#8x1*#|4)m03esWIs-1gJP>ikq~j-?}Xn(^Hn!a^pLlLX1Q z>X!3)Ixi}W70DQZ3IE$HBM;0LXVT``jjkts^a3>_W4HnK-_WNL1D=A#G_eK~kA9=e zi?Y9p7861cFai`8J_05vTRUB;rlgt47 zpP=%lIp5AcS~!zjy-1$)4%exgG;W(m+s$S(!uxDA?Eu$B2p9Zw`2)Tb`rvK$rhwxt z_DrnHl}}G)8Suw1mAsh975!*b!AC zwEr$>wuVG$je+i+t88Lc!fhNRljR$EBKcji zgFuYHP-95^E5)f7s9wD>I>no^VE$(aN)d5|UL}@9{kry#_QAz!TkzI>`~udmAK&Ms z=AbO!?H4q;`hm=SX#c6!5H~N<*LFgAzEH98Ior(ig38{2#LEhlI<*C-KGL zX$f*1+-wsj#cm*2P6PzaiTYnk;UWNj?1FfythmyrqisW0o4Z#@c1AX}1bww?$s=q% zIr12~+-TVI%AeHs58vVzPLqYd1+8vck&%G$-U%#d9XyU?!>bIk<$ok=GJC=;I657@ zAKBfUT@tGy6TbaLt6i~coGs|#jz=(O*r9Sy`N7Gsz&Tc>#m=i4>6&X4WgO#ZY&{WM z!ho&W?{MYKzn|~}LX<}mpm9LMSxdeSS^-b2qB#}oLhOY;6^hm6hP`)n`tfgqq~hg@ zmMXM}ix`yTMUNj!Grd}TJR~Jg_-Y}PlD5#pKQ51ATN~2fN`d<*{N4_pwDP^9BK~9V zY9z>us3~)n>G2be5;rE6Uypr7P*H@s&re44?I@p^hs_&#(v7k-Mu$H(*ZceS>GLk+ z2|CGxtQBVqnnYM*KQuJd<=F4(lP4ZOyJ@K~VYg&Q2*w#9*u|nEFEa;sexl>JUHJ`D|M_p|F=@7L3E985UX z4;Cw>2m2@j#xj^+G;j0*x6^lZYbs;=_l-577T z;;W2k@5|-=P_e?{YxUK9kNbXnhm1kvRz(7 zxA$)$Ep001Z8{qsLxf0Y(1^W^hW*h$3s5S}C>a^$LK516P>_#f{hP<-~ zeWPBjrd%jwb-2!aD*H5k>b*;VTr<70OSDEWUvX!BiT>_&(&BC1s^2)!)*8*K3zs?dWPg>--sbr%_u}* zpKK|(B4tE4ZwOWwdT?k5HI zYMsB4iZ^PO|LrFdrhdBv0{@DQ@f%L(=^jt0&eduV*aV%WisO!$s~#wEQ|1)vKekN! z;}=4LTzMqX7UO@!rpw+jw9BD=w7~ZD58v{dlWJhwKFSTj(Jgf-pQ1S0|6D#QXu4V7 zP8ET^^LMnX>okD>+un6?CGAR#m>ImFcO_lFZ9+H@Zi4gC^%U_G{U>~BG5=ggB3cxT zcRbI!7j>E3av^NE_2V<=E*(V%&5w(1g$YAgQ~L=o*=f`B*!lH5zn;15*Mud(uN5{< z<{8SCjqQ$k&KB}L*YBCpXpxDbce-6huPydl>xDD!jIy-Gf8vEp!Lg&Ex$M=~Vw`rA zo%dr}6E#G)mseb6r9`7e`9D63&?QW_KZ(xx%&W)2s~b`;Xtr86`%%4Xu0M0zZ}VM` zq<1k*npgMKlk$;g**Dq3WGeWOcb1J2kWYkIPYyH&pw%osmU4{~x=u=VcDa*0*ZqWi zM$qk)@a>lW>Us*cK0GmPI}fTV(?2>Tg0Q0Q6W6-Y^RTdR)UGRhl3_-k*!J|%1NWon zY{wN&Y^OUr&deXIqKw6@T4w3p7f%`+*ty3eSv9(TQEMUDb=Zx#tBVYJ%r5cdQu&$z zRXfC>Y(<^h?l9i*&+!frR_KIp?%?Oajn}lg5&07KG?=}+*e&d!xBYPW?axf=D(MI{ zRSXUYQTA(6fuf(+o=Vrt&K88FTC{{Q!3Ts8j%5IJL=S*X=5erPi~aj*a!ELpVfj#A z^+%1u6f*>@XFTtMYv~ZMJGNT77a?+y>$pQv($t*zEt(NUd>K}y&Y59Z8aOEIe7zUv z${N0f1d=rTVq-0-Zx%AT&=B&V*0NKL25t@6syW3T;c(46SF$p}t2ibGLcxH@XNJ;+A4&mO@Jac8j1V& zL>)kB)(*1S5WmEppi+gb-MlSR9g?BK`sFE)J>2=A$oz7WN6U}3K*V(~-l%J?qM9e! zNH@C9hBZK}xwgl&L0*(dy(+Qul<(hXK4bPhUnzV%27jo*aZJewQ(_GND*7E#>~_90Yp+lyp8rUlq-PS&O8#1+0q1eZAMCO~Ot~+dO6S z{@ZBY7)FoVSf?e#7W!B1Jx9NUghleMGV@Koc34Rej7DU&XU}G856)714`!5dD>*vZ z+$g@M{^t*TUt~ub1N{Pvwld_IW`2@p{+-~-JU|Wjfy@cp91T7b5FZUaqRs ztsQxz4lFGLe=XWJ-@Nw_7?9N~x_2MB(@>OMUvVpE+rdL|jqrEV%SgDbaUv|3RfKAz zJ%^J5j&-0P0B?m62rcSfUZQ}GK)uk8fZG+)0^ZSjax~Sk zDjB37w3se|X=`IT`qo^Fo6_D>)13dNbC1x`vWvVM-Q^*9aSHm%9{53`kG*JXtUs$& zM<@*}<@otI@hQDhRQHYR%%Ac)zJHZEG2SC_FQSkM$}tU?wM+P0UT)`S&iH5%HYya0 zUFcx#Er!Et;;w9QO1H+KgPUU9qs8;<92G}i7yiCpnoqVZoqnHHfH9>LuE!A3gUAbQ z4M1=L>4@?gClxe4vB&9u|Ndd)jUe&PeR)V_rKwVgs@qw(_u>7vEHbBX`JPCPR>|Z( zWp1eJQqFBv=ki<_I66UEp+4)lP{KbjI%_rQiDReL2)E&}f<5`L0(dD(6)l_CzF z+uLbI_V5T!jqtTrKjv5^{Wf>n;DtK#Q@&-HsmW&tl5Pl5EaRYW?A(@D3<_287Yrzz5 zyL(eH&t9a$oH>)>d*{U?V7?Ll86gofceBxAh)`3jmdBMGH;yP&4D`~lswaj+B^-wz zgJhv2Flr$9InyEJ;mID_-}u4@R4NxqNNr2~PCG}Q%^yzEwuOOjrU=ILOP?I~DYEwQ zZASRN9G}+;_eo=M$B1QXHajC$q;8vdD_x^VfTOrK5H%ol$qH$Au_<#P{DCMLGs&aj zrx3ss`^W?3F8eCHYcw-7)mEg)oLN47s4wq)q!K>xzDA1Uf#bwr#Cq{3PZ|gBHP)xk zjg82VLOLh8l=NrcpQlVQgHXBrUb9HJioSIZRYtN+fMCz?jaC0GiI3{S*?16vj_xhr z!;_7A?XeO*=jG;T0UdHoDZTzX@XL9>Rnu(UTlUV>|c*(Vk_}M@8OlY zTNXd(^eFaF#@|ZIVieCj%{EUz=6T0;*{ju4pnINI+v20@_BG`hpe>`Ug_GoQF*GX* z3&O6Q4T=T8>P$@Tkkc0MkJ!O}fZOl(I499&Smo*Uj$COzH$Y+W}9(L{e{MkhFl|07q$IeqEEI2>sIL`Y{(&)uqbq-sir*;5pRK$Bzw? zB}y@Jbob6hwa9&5<3Opxxnl2S({RtTjqMAwSwqVA1dX0htIYGHu{B$S$4WU|$kMQH z`NOQwK{!twx+xC5B`mcY+j#+Rb`jb^>Of(|mUMxIg@TF!*rW5|hGRKLX%42pA^2Tn z&D_ox{EJ$CgJqn`U1x>VlLbAp^P)vFo-H;aA59@_hT7>iRNt@fJsmK#qqK(=bL;z5 zCgI)8TBnd81FINdIx6BKokFeE;B-^8*RPoo147!_bg>90yXA z)ol+A>#os3q{E^$M^qSmnhr43uuB&W4Go*T`~`6KG$8saE2i)%wusKD)e8+P+v38# zfQBPR*duTd8hw!qOf&e2@lFPBEb)(jQdMftO^7l{p%`xSB9Cd{RuB#%oHc!!IQ=V; z&h7(Y(6rh#t~Aa!(RNk*(ZzpMOWM}%=6REae*WRG&p3f!Uh9cWg}KEmlg=BJ>D8np z^p-s;|T3_7Fpv+>}_(lbx{btS~%(p$s4lGLwsq;0vqF=*kh z!keMQVo0D-VQ%WDmI6AuZ;W9VCo~p^Y)iNQ&8+#^wwd0KBT-)aj4Yo^+G4PXrqOA{ z^c3$2kc2dNp5Z(yF1Yr3K)+VoZf*h5aiGh4t+_tr`s0w}qoVcXm3oIlEuq(>ZJ{!O zuzx*siI`}m6l6bedzzda0yuMjFG1CdkLfWNe&Gfb*AZW7k`Ak^)tnbfo5TL!H+R~$ zzt)lOahytqaYKxP?0kzI`{57| z&UpM1JdDUolJReril+@8OmI#yNm@*t>%PQ(>76eoHX!U*(V>w7PM+Q3h` z04md&{xW|-^S$u-{PZV^gvJyBwdds?T?LetgfOY4N0@LO$KXc4=m$OB==0VWl<(-# zrbqs>Jz8M*+er9Jc+NxTu7ok+_BWE2CuS}vuWFpf0r_HhnMD{{uMO>Kzf?N9BGovZ z;Xca~oh55E2oI90fop=hyejH;v00 zej+0mJW$p>d|fZy6WHEagu~Zxuo4m!MO3B`o5iIJ${@Z+60L-%VG_;@wZlIG)m#|l z(byGweE6dePlW)K5-s*yhLDNeBIn9yk9qI`WEVQI1yxH>as^aDRV1sKmCI;VQBVM?EB*1`NcPJ-lkQ zci4TTC3MWV=$HHutc_Qu{JF{AT7F0|aMte}N}RnZ07&E}VS z3aj3qQ=+eb8bfCIv1U(870C-3ehk+wm)?`V!ZF2He=)O$jqLBK6$ZDFFzg#&V^4{~ zMi$`EOyz<+?P%SGU#iL4eEM`4wieF^`{tTZzdJz0A}<#)dalMYk- z`V0B91M?Y;{@?nVFU()~k?95Pk64A9=ck)}$Y#m=yGdfSIXdCMGakfF@2|hZn1bA9 zNNuKXa6=8B>pyyHpN9>kiw3`4wxhnzbzXqXpUacqA<3e(n>j6AD1PM zKEPfEE|(X!;iy3RU{AB9+*eP~JQY4?dfN*G1BzF@n(m_~6L>cHW&{Fl${hGOKSt43 z@91)%e-}e%8x;EYa`h#AfiPc@5R;c*>5#3%0+P=HrF0(z=B?@;xmBkedqym1idmf* z1P@q&O3AUxZW<$G~j3$U5;Op#uv0^@Oh7~4 z?n|!SGz_AeZMZ)O_tL=H@x05n-&FkXGyhxV?8K`6$78QTs4-lcYwq7(3X|?8f0xw> z^13{siYDG5WuKpDl{!%LbGpWNAF#!6$g(PDIbVizP9m5R`t8&B}_3J%a*O3a>NiwU9E_5k@ zuh*J9+%OIz-2F4Wp3d5z{9(n72IL(SCb7JJ8alcKc$o;=g#CWyL{d;vhRAGwpoWVu zOMOfR8#s+9h86anPpc~D5zNZR^wxohjuQ6Pl+X$X)DO*;x^GXM16rj2Dkf>RAI$ES zf$TV*k)F8M#Wd4aThaEuBpN;V@%(pxgT0NwWJ13OX2yx!FUBAHCs#OHrcYc!AzNK5 zzwyTw;*Kn(Tv)!P6DdkKptMwv_kX=bC&^^O5)nw%h9DqBBpa*GU4{*V)1#B@E zBG3lT35-Kh!sc|a`~vL2qYWu4vX`NnAM^QSTTVP5O2ob`?;7N}9~8XlB<0kLH)FjIxhPEjBy6|(BEUg#Sb+V+5(ueJ1Fn2iz!iq z{JrN&FYbMxkNisf&*+)zVn(ywhydn+b=9B|By z%x#6-kd$ir66OmF-C0oXFyH%Qx3%qvPyK zWbfl5Tm8d=dl#f_tB{Fi`8R)u(+dBsDVL3;@!XxdRM-ytrN^Fc{oSWkxckbly@l0B z|Lp(jcJIDQV#4jK!$Wb?&`a>q3)Q#_5u&pHe$q_Nj#CD7{R7Uhi06VT9(rXB4><0` zfVBPuVTt**wOEK8b=g1VWE6zpGmj{V#H%mr*HiGZj?fE2_tsRT#Lzisq=F(AqZqJYY^oqAs2CxOc*3bc@E@v_R# zcP19uCDcCUPM-H!<(!dn zqS@LEUeeT87mM!8k5&0U^(;!)IcOWt3t*}(vS5IS4*qvGVW#IY!DS69_iUvdHJ%Fc zSN^fAL>N2L4LR_QEqhW_DQ4a}aa`hZYe=IYgH2ob@?|1G4a)!;0bA3?o}-Q(u_Qfx z{U;jS*REQaq^c=}TQRHFNuhr1_EEv1nz&vy?#0K9dY|77Eve`vYJ-h32d9$Cr9<;0 z(0ELaY!t!{zj!PeUA`0GLnxL1jA7w&-J!<@agJnQB_1*;E?wSAqn#$DTi~Rb=oh8h zlDx|?b#=GBhJfc-mJ7L2no8b?5g2`t&%(SvxfHavaS5Gg+iQ>9=z1eO*O@pc(+^$u zm0f zDe}}NUF9DN(YrpiQ_+TsNgprXzd_h~72ZFK@wGuU442~AmVjBYl+){KXJ zAMw*!q1S?Fw>-5Z$R$vF@96j~TFyTx`sv)gJlv@U1>;IgDcF1z&GMqq5j?@311{dZ z*)Y|IDI{{F^~yjCW54H*sJ&sI-NPSKEzMcoZ>uHiC)(%~4MKkUooCo-wxqPdRp%3gx4GtMF@Ce{G zO`Qt)Pb@5z=cO@qGN+sS2Bx4YgG242drm}yX#1P_KXOYURd_qWi-UJdINK*|j+|9_ zUM8eY%0ouJoqks6ntFC34UcHd_U!C{K`n(un-9uUgETwA)>BZ+-C<)C6C|TgphC0p ziy4>o1%op><%8BFT_%)qy-_k2gcF}|eua{lbn%3EoNp`}!>OXfy(Iqd#Tzf(c&0|@ zD20<` zJNMEikOqmM&%5{8^Qt&8-;_0y?qGTxplyBVaL4P)yBdCiqwWKJVxpWTI0JP$j@L6i zppB?jFaC`1XMLmIKlPvi<5xLyoNY?t($M;m^V>o)uBxedoSQxG6vH)16zcJ=>xBp= zE(7UcR=Be?9;n-7}N#Vj5)pIgxB@aomM^yxE=<(QUo8DQF=BIlWqmz0{e1A&3 z8~W~x!aZc@jF|P0_MmHg@Dg&1|DkxWd}Qo=DeQZV{1hR3Vu?yd6KMygtJ| zv_ZF7YwUuL3bT z=Sv(c7alViE`1onxnxn|G0)0$bLLY~uU+w)FlmoDZ8hnd{u?s$=lw4{-;=W$M-HWM zQV4SE*s&v)L`QQ=j%G&c{B+yrJ2M-yD9CW(gJQYIFfNKO=w#1W7G_ux5)&)CxbR|Y zzd)RshY?xh_1-+ti-z%gE6GGBoESuFDKf&tht+mV~;Xq31-qGUKOk*N+2#@W~MY*8<4( zHYRfwSvNU8W`DIma?xZsLK+2;0R}u96_QtTsw8d7<=56mI7q)e;>I|Hqy;Ou-;y=E z)6(#S@-E4@*=KppLN|pEneejB?UCs@oSI(#rLA2Ot|4LAI{=PGf(4jWxr}tX{(}TP zHf;{DvG(<+xER3nWb0(f-zjSWkQ|l^1%yk_hZ(^4-rbyK1w9En;Nv<-f+w+^%Dw>C#`5<9HL&{NK+ zAEFp0eJDUx8KDxQ3)4EQHQ)+H@7-O#s;eG9Ab`%|DO34Yrxt0CkWC))aURe1caEI5 zM+7We`p=f)bH5%>JdL`Bh@bqOI@3f zwslGOaBy+4v#N3n3kjv9q_CsoATc5r0ArTKmvi-tu#@QizAJh%z=gqU7&vK!&`b9% zv#aNJRGQnjCM4MWriO@A35kpFtot{^mu!PB73$h{v@$*4pQhXm@Fuum?N2NtI8(q$ zNdR^Dvsd-$c>1M7^Ii!}EM_WIi1eZn={eoGe=-xe$m#wAUN5aaEy|*5D9xOVWfm3Q z7srQ6GRpC`_b8d`@5!}HP6`8dmvlV4LkS;T=P3x?V5fTl^Ew11NhbI)lmPvDGfO@m zus`(wk3K3Vs#Ii1Ts`rDIz%&{o>laP4}DJ3JuG?J`CGv@5gW{5!H(uAx9cFz@c#c> z>nmnO#5dp&Pg1tI88<`Zw*F*@#-qU3IH;a@Y=@6|#uzfar>6rH0p1VXdw)-pf}j4( z_-@6Dwm4mxbi(zXb2d6I7l@Ql9u7XL9Ag3)`uAF3>toYJOurWsR_bYUrWN^Lz<-YB{QmslaV}h zQxY3E0+9IDh_Q7JtdmhuQHnsU#zMoed}{c|t_ih^V`JvP%jjk~X@rD;=aaQyD_G%EM{Oe7XMZTjE$OXliY|XL zE&t(miR6B_?%6wY zRO|Wk^ySeuK86%8{%-CiuQb~`YPAmc;`o*xC9e3Tj*$RIB&|+8Ugg27@0E@hL4t-@ z(*ba&VW39{SU((6Qr``B+JHdg3HaeF^gAH?4nk?%s`qk=W+h{ga!o}Q1x^bveTD$6 zkm0R&i3V0P(W5b%%fipZiFSB9vW3#-f$JTe$@hR)(49q!;Xl9 zvIz9;|AV&!U_+;$3=wvpk;US3u%!`zYHmZA0BE00SU~5OcQ7UF{QZ@$*jcxfANsK4 zbJMII5n;oiKyfbz5+inm1U3TQmH1`ya>;%769q`$Gc_ChiS&Lx(;nV_8N$-2E#*O$ zFoH{d?2^saBv_l>XI}h*$wOvMiH$cEbNw8Hp!U^<{r44!(o?5oGEUPCDPh4o^RMou zc}mqX>sJu6*gvNDaZwGRk~7fI%#50HB`O`6jKvVJe4Yd2gm%hIQA#z&SvghGu1D z&E1nfn8Q_7Q=13Aa2t#pB29Jhgzo^$TJQ;qn*oMg+qm8i#08J z$3TUXO3IM9pzf;)d6DwZpyKQIlg`b&{CZwNe()UJ6;3}IVUCQLRZ=ESj{e*My|%3L zjMk_S!aMIeCb)9ucMHd4V=;cI+TX$sO`IIQEV0I7pDZFZFk> zjrFD5&bHpFG%tK7fMM~<>5Wq_g1=ejBSsXKl~K1;-9@74g_3Z=qyLu)GkdW4bt&(q z;pm?O&wxINorx%}un7ewXisepiW7(9U;%KzkeU|jZq&T0~NHOk%FO0rfGK6PNF`(q~igXYB7EB4xrodk;>X6(?gEO$L}IG!!JPmvj{PmjjL;_{hXg4t*?>M(q_GJX2~ zx)srfK=L5rHU0byYr@0!)nD-*KEEvjx91OkidR8V7|N3yTElbwS&7=AM3#$eIOW^- z#S>;Pc}>dmql+&ZiIh=PsovJc(UY3T88zj^Al%{EuUtdAh|FKm(hI-20vUTZyygfV zF0OfC>ec*v2y8QRZq=)l(l7@ zgMT$)$Li71+{R|Y!moG^*~7)_B@OQqyY?ps_3FRi_%($1A|f5s(=K)VF2Uh6aMxy- z5Tx=q*x3e^@4$PAt(LRMv`Lq!qI_pEeR#uw!J>ti$D+loprE>cIJf(KN!yFrg7e*} zkb8Fq$L8h>Q8e&sw&x59-Pzu0yQAW~R8Y`eX`RSB)R%t1bQna{e{mOO?&@*I``WIs z3L0gk_es~bXDVQ)vg^YQ^c+hgs5sM<2hB`r3_rbG*Vx0Z1&)rX4*$s6$jlJ0(2n>Q z`7fESD6*?T`Rl>osIF+H4#})r5!O0WpGYPAXkF?sEaiw7jwU~T!0UdV5R*zI-Pd^N zm&xb+gp;87Kul=|vU;W!p3NjdSr>+ z_^dso)0D*LS#t4b@HpR+6XZo>T%=bpoU56yl9YJ&3od_8sBNi&u6BK6Fo~<|tN8dg zmD_*n5(xj^eSV$9C#0JUC&~NFH;%+*@Va5r9X$Y;jC!#H7pULl5*@B+@@b>3$;k(ne`VU0(KnK>?-~U-mb_Ib$%YPQ zN{BNtVNgu5AulPjBn3p4Y#8vt{f2fc7FbC|O)UbnK5Wqunexp$+7B?geDgMq3NM}Q z&8&t#UiT8hc>Fjnjt6WklwxxKarId}a%A zD)0dL(*CaZZ9%q{4PknJMDG#oX$y}Hqo0LQz4{w^qn?e`82@0&h`bfG=T*l@Q~E5) zt3?)}#5Uo>G)BeEf(NQd`q&1w3I`UyqEu|JS2`lK`^vlr2Y)wIH(!jqO)^xZtb9qf zor4N<1J!Cg2L~j!v>xouISzv41F}1$ShEVa)o7scKPEW$7rT@wTD>@;QZ!;J34U-t zLFrirm1erMGC#kIK-&W?(5zbrlD=5}wBzrrY_5SymQIJ7F-WjQ_nn+xJu3j)d3E zdrh6u=Ew~@wAA)m3DdY4DVvQe`>#0j>F3#Y9XOZRQR6fe{0MdcFQ{)SIl79xDY*@1 z?qumOfCJ091IOx-OM)t{BJ0_kTIPDjGh>KhbY3~k*q%NyZ;%%IgrOi|+h>7$g6=i0 z4?o*)k=VTWT6fa%^1Yeb^p6csLc?pGdF8}sR(u}LvokSfU0Z_6j+QN8Y`q+C85fw7 ztXnf!EMQQ)`TKfDCr1w>OHZwf7WBVZWAW`k>V+PPZ2iX7neV<|*!9|?IV(P2jTjOk z$u4SHXmZrhYBho1B`#X5|5<3o7*SXy(s0GxPDgY{I(M1sA2IvGmzvN0`%f ziI30w>~|DCF8vw(T*N{1UYC20Sz9)kZcof38k{4-k_c#^akcc$eX+|Nv82UtxBdmv zz--DVx>MrI1$&wZQsS2Th3!8egI9yamnOb{gTG85!l@DK5&Yoh!1`8r?DP+urKx7o zqC$0be(c2x6p&7cmf|8!6KN3x`xew6&gEUB+R4{r2r+HxB(+(5u(o*nGJ`ptBGlin z&?(BiQmi{6lr#Dy#QcdR?mJ z`XAmJK13c|BQ9ic>YddUBfD6O=28h*G&BZ}+UxCI!caw+3~~4cx`CF2Gw48)-HM(P zW5?5vCd}8oQJPzJ!;tN;mYARo=WgQdhN@uq_7PH>_=Hw~?I0LE7RDyzS-lj=xM)ZO zwMxzVx#eBwgc$+loZ(+vGuCP7^)^Gl>&#U#o*M>t=@ggkk-m2+6A9l>k6r0QeRoZW zHdVJ?y#am}90eB6tRVUXgD~QN6*&dd=PtZp9ugk>#W3Ro#)!vAE7N~wOnv?{Qrp)x z42p0}4L5tg7)dtZlU!Jt820{QG0>=21`m8R5R3Ii0X^`=qhp(vc)& z2WRe?ul$HNE*e$JvuCGTu~(h!!UJ27m~S{>h0Xl+{WxsI5l!pjDwDN1eEN~r_y{?> z=W&+so8srTpx}n0%h!fp763c^d@_N)0~Yi1i7OY7^4mKdW^FXRmMzthCeQEnm?Aem zSsZXuID)=FCH@00pFsVE!<^vl$)KCwJC&(;996HM$<(JBhYU{!AF2{$_|H)cm7MO)st4Avw&(Vm}6D5B)PcK32+s{`V_ z9nAcaYqUzC{G!KpFuc{A5plhv5u0N(xP*h|taq4J6@!B3)SvPaEo!pbKptl2i4{`d z7ji@|Os3~yK$_iud`#pMDKAkV2k_XJpD%STRsOY>zRH~{Vefg{cE`IIJ$Q$%e9zm= zq)6Q?h%1ZT%}3kc!Ddwn@uKtm7K0P!NExu~JXXdc^cSjno)B`?&JZWVBGbU;tZ2I?1F1)G`2_D?=KB6}x$c-5wez!i)Xjs-uutv(nxFm807yg~`Q zkSTpyVm?FP+N^JHq_BUodecwV7jK}9`7vqUJ)XrTL|{U;UQgc0OxFF_B{lA)G6K}+ z=ym=4we=%HTgm&&LoU_WQsqqWS>T7`KRwvKJbQ{J7QYH~>M;Xv&ef>4mGFZTLpo52 ze}re79%qrzwJ6+l$SX061to`JRJ>bYhpShl;a-Wtf1j&PU%3AcP8#FP_zm+f|M*@9 zm_C`XL*<1AZ0-K4K`@YYU~iskvT@~y^K?QNvH=VT0v@%kjpK*}=aLsPQ!O=56o+wK z7UU#f)7m`_#7gE5&I%?ibnKs8#(p%x5M|i)3cre0H)P$Yc!74!t0I3efNvvK1M^pd zw1GgmXN&sL?~`J-Y^YB%FByuS1DrJlBV!Eou@~TCgB^Z|B@)7@C+x%qAaG-E3es$E zRNYs!gbJ~Ng}P@35wcGYnh~DGGpKaERgpk`JwAO^`cQqmD-*5TReqdNosS-z?a;RA zM>GGv8x(jyjtmEZjr;D$93h55DrmFl8kKfH3F}pQWNm9lh}0s^jOQ2s?q&}xb!FaT zKXA`I2qF9MU>f`Cx^^c%8ea}8mB&|)AFs7d|$0R=tW(T@5Q$A1)j)w z`=w8E$QsU|;kcr}io}MBgt70jvP@IP>tEz_oKwo6J zPQE4yl;=!d(-WGp#2UQdI_OHOqNM%xVQQDP-n zsI0bR7VvAp568>t{1G5Z8vBGd52L^0veC7BZ0?Q9i22mejVFFG)BW}`dAT4(!16=v z7$O)XfTd3V{P`2xKBA#c-(6ZCCFgumG`NvCg9oI^2qn$UC2H{o38 zM_g(Ya&~g^p{JUNNxFX&_2Y@cqpKuJuVWovtTGm1v@LT?h@CbL>CLFr_~~rF{J2RG zjZwJixR{-i8fIaUe(klpEfJv(P6e&~n8av^Ta4PrbP zolq4`+!E$i;l#=m1urI0kd}w*;KFE9n%W4+Ho1^UvI5t@C7Kjk=V3g#AtiNa}VVcH8sLBbzkN2leZs&j*I9)&#nC zmyx@f1G&6Av*~j5<)wd=zyf{eZ{mnE$m#p7s+x0N3UBry2>siTqri@(QU{JXmIe;x zYC8bs9KbjgVX&HEVcilAH{w?XDH$#ecDnjuBZ{`{$9|I7d-E*Zn-ht=dMt?6o~IU- z$4!FU8YG4W4BouJm0Ly^G+%_@s(aKpwJP6pKx(s=YT1ut!X{kNX3gG_VIYk{nvNu< z-OiJ^s~6k*h0I-}x)!b(3po}Pk|+JhT9kH{tepjbe}XmyBrytC3RpOBXyAjkOC0sd znKHg2Z_eud^re@o906@-PLbVd?L{LTX^RBF`GVY(g=r&lHU3^zxX9Ab4$k1!%Ro;M z_6eVRa|qg66bxsfg4ttO3k0jof=#rLW*yX;mng5fjj_5}!9t%?Sy&}qBKOvP+h+ii z>c*5-o*-9C2I;FF^gw+`G5-QmEGErdXN9qshsO|9C%ht&nwNAOC8;1|bkJ6BrAVD7L^e{7-3 z+hH@fEJUd)M!h?-+l5l1l5IXCzLQ+9USe5*xuRcWJF6vI& zrGEsa)iX^NI8oIH3W{ef3s$_uykYers5z)*cY z;+#dzO)~?@;#8B{{1~^A=;b<(=TmazxMq&L9oX&8p91IpmHA zL3^~=gp`t*Ps=c`6Sy9l*Yx7hWzZCkit?L`K1V*$Zq(A<{roD}pXGMk#-jle5&PDA zCxLOcAu;L~aHl9J0``f>#Qvt26c%FiotuYb=H;GqW3Iirzh{;^A`%c-S|6Cvc+cXK zc+G;Z zqs`8D*Vf5LxcxLCMsIxrP88f%PHm%Q1TdI?|DMXMz}2_;71vW46>dsf9T)kT880HC z6JK&fxa1yZ!Cq8XiToike&jb|bhXzaoa4e8Dp+2YKlEDGSi2G0@fLs}C9L z=DfA7zEs?SCPgSu6FN{{q<87VH6mAJ#6OhJGrQ3kN>>G{biUvi%;>+9XOS;dFw>~! zw9a%@@qpik9?iz%qHX!S#$|yh|ArxQf%z*jL;;#tfb#)bypm>@(={%;I4AmWHrC6$ zx1?Pavdq`~r1`?LQIG}tTk6xPFHD++P_6PTTlS5<&y5$sEKy|}7PW@5CfJ>&1b_>y zwJBGqLSGK0>`jAbgbNQLC<@xC-OPuF*wzKGX?lfNfe77n^4I*wPqEVm%XnIUF6EcD z%N>&kcAGv(%lpQLKha3ovPi>YmsCT-_lq;NMx@fUC5)i1W?6(%D4aK;yAxV&mbYjr z@i!*S`$Y?vW_;VZWo*sRt49~&F($j;zNk~5`=w3kB$(;zo3&(Ru03s4#G#>U`Xzg* zovlrJ*8QMj{yL<((a5gz`G}Q|RBUw7fE3G4x}Nls0bg-;?1T7y={1}rK3s$KZ1iAy zHMwy7p8buDpQ4|+9_2X85xu@+dLB}wkw&atDU-Cveh>usx46a0`1HBzhP+xdTc*a= zv?GM*{pLal%AJNdRMi>%b-H1uA@~Hq&jvaN(Lh@YA<%?+`Aa?-G{3~p-rNw*x%;xm zp6XM@lHCvZuOx>?$?^>H^279=?1zzdHP@Nhc=%6fsTu`?6zUBnwHm=*_w{#XXcOM#mRwwG;er^=(Qc?#%jvkZqOQ2(JOtm1e-pz zEAJiV%V_%;sA#%xY{c`Zb7OO;JD#aP<;UZ$C46jx$2@SUGoSfLfPC5!Rb~A?TqkHq z0*OwaPn( z41_&%_ArsYdZL0!W=L4~t&i^8JtDRoK|1HM(O+A?ba>!ksFt|I?&oYlAkp`PBBnPc zHs1d!ogK>XZMBVQpzuTABCFqAVTT-os;s)1mS%m9%PAvI5WAR*=p2D)vcEqUQO1yQ zrc<#A3iM)cBsK3}l3Y(+y6_fa(l7Vi@4s<+$9L))(7397##*$6OJ%F1_pt5 zfg=P%$Ik(TZA;do_gYfo8WEejYeUqIsRQ9o8n(8~((eHS8-Wsffsv8rG4JDBLW2qD zL1XTaYp>t&7?s-o*ZJsE1X!%}AVD&U7$OdUE+gjM<4CCGpNKwNoSSM%;0%3^?H64T zX~%7M<8c)yNuNEX#OZx7f>^VhN_q&W%!VUJMs)LP<-{f9mI{GvOM;a%j z67lLoeT^F3%g8W9Z49P!Umv|^)FIX7eEb+IFi{k>b_Lc&KHsK zc_I0ph~(w>sRD#>f<+B0u(41&1L7n_Gm`%?5+_0VC)E@4fy6{{{hA}OviZWrr#4;> z0<~8Ly4-W(zOJ8}(^u2qwS2l{V zGBotVNhbT37k-yMVHEUaX;UtB*xK$dh7bxww*3NBnJRr2R04;@rFDZ};ykgkXdMQ| zk=7H`5B$GZtB>4BvEyZ75SK}XT{yuTm0>Y8{0Etpbc#^bf3fEX7pEL|JCpbfLcLlO zd7F5*iHYV}$o7JGGbQ*={Xbmhoz$su3RZaX_8m>DBZ86d-U8kp=o}K>VaQudy0REE zUGbObf~+_;V4r`BG2_(@Su$hS@pS(iguEd*j-A*~;O6TuOyWvai#5IH%y-%g+o%vb9GZ zaBzPHa5Tfpzm(5nCMaMtNVnr-OAe=!ufiJ%s(#qhqdv|}1hErH<&Q*>{B31=Dl-zb zo))F{3wi@ZwLKN5?Kfnv6bKyu2<3XLVnW;k+w^-yIz^p}2b0IU-*m7ND!)bD;L{!U zRSH2Ao<|e@9Owk|iWr~iWqg`B~1jc2I1FgJ!+bnrlx%@Tv>kU zHI*vfC16p0N}2L1FOfgJ_DhAGL)Vr9!wX0S5`|0D(p>~Open=V*naT^|I~DIzQJN0 zG0(9@Ei&-{_3p~`(E`nIJdpH|x&!)3iiBKES~?QMzQ_ zwAkcezMcMsyMEGx-cw4 z$@b3sCdO8wuC*?*-uL`Mio?=f_K0aJ?J$vQ(dfK{O5FF~>iXK2+~T7p-e~jXL@nYW zr)dgYC$5Nr|I^u5Mnx6*sYrlKv6?Ek5<}c=i4)NuBr}lrO57on{cpNyK zcJ$I(hrYpdbZ(oICOk>4g&cnz?TF)D`UQv;i-I!v5EKnMin;p9lhA1yPV{A8C*kbx zspU7eZ}7id{1qA##{xO*eIm;&KmLW*UCH(q|o)^ml0D|ViDVO*M&wy~VF(tovDdThPcd%2o?AK1xvW|V%PDq$}o@a}xP zn4s5l^=Ayc1Q?!~oujR(6`#ikt|!ziDen|1glfo8v%QU$PimzD{Qyn?{3c?z@U{!^ zuB<3~>xhk?t}_rpdM%fnpr+^dHg}?i*4IY`>GS?zRM>3;@szIrsHtQzgHzxq{siTB(L@TlodnX6oBPhP+KslzjG7^10mApFLfw zNivrE4-D_&yjCt~rOU?G2?Z&i2mh83FX-*;+|T;RT+*1ikGFQFXygyDgU3{P3|>58 zdN%)kEl7Y*N8D2ncS9v$@QZ{Wa=MwS1ZnA`vg9HCaMd zLB7t|^DhO8(Q>8r-t#;Ur<6c;4wn%$j}x6+3A@9MWT;{h&4=@hpU3q0d}WgA> zRL##x9XF>0$vO0*BL<0IoS{aHI#qd;!5!!3t@+EL7CY{5P{KAPE~^kZ&Ru3( zGz__&j}lSp(+O|;ef<3&FAP8a67#6ie)?eb+H2qLPV}Fc&Kd@(h22BR=Ch0R`7Y`O zU(D01bM&oO1b63@MuoOsZFgU|KU+Yz(Q}yO3V3gb#lTS`x`(1uC1b)k0l!+ZC0cM&CFO1bb24G+DmnXd zRx}_>ldr5uccgZ5zxDPS-x$?Tz9xaMGZnZhiPobCf!c^PyQf$yPpgx8dA0&8E z1I}Y#z4kqe$O9}P6|FCnu9>YMY+@zh2n~Tt-QQKl(8w?P@78|JgqOe2sB~Yvb2N5a zlKsN+m+2mQk|L3;?e92Eu~&A!zlbm+DU9Mg%-YOqU>RGY(_c)Nz1h^{U&OWXV6A_K z_3_Lwe^$ybg8aB{f@J(h_8hKKd-OD7Uh&HM;)aY4v)6ruW$MRtC%jM7JANqWR{Lh= zLi+3S2qgQZg&!*BIyIY42EkkzA5RHs$)zsyO|$VC-Bj_3Bk|rxL#En`^Q`QqF22-+ z?pXVd>JB@xQm=>t_XlnWp&{!dHYpv+pMtcjwshE{-uA*1#a9?N9?QvIki956PWvwf zZV6Wwof0wH*2WW|RA0GbkGtgK#F`(ZMbsgWRay4Zo89WVt2W`YUhm*hE1&GbyoJd# zqxNJ3x}!DGaH9O=uMSQeM>@Hr#0V+2o;2g0phXS zN?$`N;nip{+cnZUTe78$k1CYn>yh>DTK-DZ4|QY>nd6pyTfm9zFUw6I<&vxZ8sc^} z%)MV{IkD%l;apIJ@H4Ey5DHFDm!A& zyZ`eAqv@upOv1IBlom5z)mKt>23^aGsZLJ>DB&P7a^>XlcOo#F@xxEQ`1|6l!&+_J z{|oZOR4^+A@vRd#RlFr{*StPW?5&(|6OVQJf|6s8SY3mQcIc^ZDPizC#Zj7a z8v}HMMtPh-Z83UWE!D*i?%-jvXZsU7I`;Dm0q%rvmV%U!0Z)!C&)V{>%m)I0NiQg2 zZB|5-GD8u_IWw-LfFJmaI61a*jK`MjA)B`pE3PtY_ivbGHhLt_(g)Lxw0fU)v`<-c zC*o(kWMyDiwkJ=>`Q-RZ?x^*dtKsW=luy6DCw~6||5L*%@60MQ`lBM&#T^auUHS-Z z(RAthUD_3=M2@ka+~@_-1g<9pMkCxXfMsgp+ERQa-HD%Zh5S0*n<7Az&{gFMHob=- zp`lP?w~JqyGlLUHq3NUNtbSEnLSu0a`}1vThF1t$kJp#{3R(nZK2!LRp16DQU+lc~ zY%W#rS1HX5oousi3Gh+N-Ho1Ra7e;{a3MzHIBXc!SpQ*}PZzwvn;!gGh96U#)nUta zz3n*q>c^W+r74TA^pCIRHV7Z#NnbYV@k4Y06T7eFU#L^@vpzT&YQg@tM*qvZ;%f;e3 zAAlUDX7YBCw8h0MCd%8|$=pS_CWr1c(vowvW6s3U6zW`4$g zf?<$m{~fVJni<#nm0DTI+a;RP^p>ou|Dff%ZE9eSY0w~lwlTVUw9ZOZapuc$EcV-l zV+dm?eznj%j9PpbUx-6m>`&K@xs*oS)T0ZRSRKX@r4lLBC1%(2B5|In9v^bADl2b zt}#Eme!;lz%@&}L(F|Vl)t`8J97Q2;no zM0dpC_E`ACKb@BWY=ZCuf(J96h=bx6 zi_}I#Q@*jqASX9wZ>yDb=~AkX3;GWTJxnOZP~*PXt52(Q@3x=y@7U6_Y?%oF^B=V$ zD@n41$W&(57jDw@E$m)2{J>EZu1mwsi!O!tW-^hFA5HpRtSQfW{(b`?+>NHfUMn>m zU1HtgH1gQx^FvN3P5BmMV@r5dlySqQxTVBKsM|^WiItWGqwcjP!RVNOd42b?{5{s` z@|5ebDx*{+=>+0W1^|{xUyI(8=Xft4PNseSErla z8i4eWD!(|dKltV>W_`hNWqZgR=VjsWg6I=IM^C=WQIN{nPCV z<;pxx#+4+CgFxc5ep+uQWcUoRj&Pj!%d=DU0mS%Wr*lsipILQ`7f1I|XJScrc8_!C zAMvK@Mhf-PgrE|KsX_07lM0{D@Qf86ec z1SyUf^^Yl!%$KL^yUSxqJN($yvb$r$b+Ebq?tYmf)=)v__h998T20lQel`Psksd-t zbC~m(#rII^YX2CJPBr^+mn8qaBcL8Qk5O4edB*wkcR7b&3H}u=r+=%IgPBq4KOAUv7&!*_eq!M_B%R zTW$J6;oym{XGhom`e>Kn8LibbQe#zNQt6&uGJTw%ar(Z?C9wrNKfthd=W{J{WBD0sxxwgsQ z{k)__XI{=pdt(vvxB(inBg%-`|M8T^8wzN-gpPB!@l|@<&}EaaX|;F8{cAUSn?ilz z_k3^PR&^YrHAt7N!9C?oi(Ix-7Qo7h^Z&sD`D|BD@|kzykByCGWM!d=F8By$4Iia1 z{%4jvX34EqZ!lOm_Qm!>sR?{J{X}7ozz~uz?a8?Yw`X2 zwwBArxaiP9GX{S9{GWt@(CR?XH&FP)z{mHwb=u!=7I501-ixi$>re1+d`DtGe2S!S zhLSA3W3)_TD@-4C`Z~(GOla?fR+E9o!X7%WlM$l{p1Ge7BwDdMWd#%QnTBdfr|fNK zlvx(5rIqxry;Dtna(-lHw6L5o=hqiG!n)>e54NW}8inMyzG35B+EsC5f2MhZf3AB4 znojCK&w7PLH|ZO9cN77<$Hv$Ey?#f(D&y1czs`71Mln(v-%Tx0A_i7?n*0mMkW-UU zK!cc0R_x@kMrvqv6wRazGlU>k-4@A4X~|TDwrH!UWp7) zo{Z9XXJttmeumN0CD{SSzGJx9JnirfgX}WDP9i7W_>txOSScw1MTPyQrvJjqAUMA5 z%Y}>14@e`MN1t|P2Jrt0mu2u;WA>0_@Y#H^@NRUy{Rw+oAm}}zmbn;?-ivhfL05~l zge3kgP^JWVN9l^gmiR=8BSY=89aqygxkRs}n7_FNXWF3=ROh1P;*?u^bgf(UQW|>N zlk}$BgEolhQgOvWtD(JB7Y-bA8y+NDrxg5r&W*pNl-ydiq-#^cVDD_^viu-DZ}oUT zpj{w^Yd*hk*@cO2oH)v^rm}>7pZe!`u5X!Y*0qYWqmTQsE0IY9rwLO`MeL+9)?7TR zL!77iWPzwW){vcHiu_4uuNFqu^b|UWKhen5%jk{hSZ}AepHShGXxn_50zrAKy~ozX zDIwdzs{MAozHlpQ**oV3g6LvrK|W9&swpL1M&=%q1mL{bXGHEZ0$_3MJoVj6rTGD0 z7th%?m%8lR$f<>>m;F*=v(yS=G_Qo2kp+R;1Ti+n0X7_knWDuk#diDZB^4*w^Z_B3 zI%Ynv?+r+{5L&C!f520xOLI$p7sPn3*!1 z;(icifI8nzAHm$2=oA$wG{}?u7Dw=8!#vJ!^Ys-Cm=a~=g(~<<7vX1c38N?Jx$(a3 z5`vx^CaP zkp4rkXUm({;fL#IqLsfDDTO{%y3fNxk8{Odn{f|_wUpY-sAxo7y_Y!>gr5^ZgK5Jd zLAbmrjdK57a~rqkMvO9VBR;c-Uq`qgjXw;Iv-45iyF^0El5<;StOu z+apIju=uh%r8!<;#)Mjq{3+`-;d{Pk$L`R<4f~ONO^W`7<*53vWg3#sr1ei%f=e$rkc*g}C%IUZ-^$UKNKMtR%SLcZajftm( zJq&G6vXy~H|M0_LWXdyl`}Ob3a$mbb1QJ-v|&#Ga3=LDL_lFj_VVGQi)>m~=0lEu{B4>6_%>lWITYA{*S|2mcmL?m!R_Wv6pW|BE0y#5hKZ!Vjg+;D?c+-t^wN?Wi z_A=ime)s`PtslU8T;p7yYnU{p!YOxZn| zAz+CaINY%-_}N6H;a6Zro75)yM}8;T|7uyU%8J0t+xvLt=3=td4CMHdgltLSdMl;5 zxr&2})AiA5=FdEvjkI)h*sev1%}ONCdSyFaF(n3U_B5YGhg*T}t|mL|lW#|Vwk!Ug z_lRm&=@;pUdz)i2eSH|5cdMyVc%rd<>J$kJeYNmep7G~X3Pfj_qPA(u+xT9D6!Ye; z;{-b2@xnSy6#FlP9s?SaD{Fa5hf7Jkv?5dCb#c}mRft38=qJ%btBs!6Q&=9U+}&Rz zeCT3pL04QYfVx3TS9ckJ_I02*9`e)uXow{DAV5Q+=6lNor246Z?Z`#!r%W!T-J+PY z0{Fp(iA+fKq8msth<4KYK|k2?s!`pT%}S9;c4d`0aA+n*E7t--MFreM+_Pslzt;=W z9J+jw*AI<6Vb`hbh8}74YrsK#P=MlT!K8Z z-}SAmqYqv?+K=?s1~OUu)U@$W7W^@=j6zG}TMSWF^Smo=Y$p&6p6uQFNuHOyvPDeY zzcrZ55pQ1GZ&^Wt{pbT-46@A|(r<4~sZo@hNuA$4c5e&Y!k!wT-#M%fX=zVuu@xbR zU~a`GhVs@s&gq?*hbKN8 zlrihL2IGkLvbTUnF`lRezboJz!Gah1A#bdpLu1TTRgL6QoVyl+P@G^@zrn78KJ-k( zXFSwqh~N){Z1$_$PrrAY7Y$KFEbSoYMs~YY`Z6Q2;Ub?6+*2@EpuO z{;dNm4F^#lSPE*@_`2Vz%P^=``kK(M(oShWk@>6nPYW!*=THGJj22hc;$%0LUD(vj zS6^*a&~P1Qk^pQcKIuu(exoOef)ghC$^?{_B#*Vo5+=FlzD2z0&APa@T(rt2VlrVz zPr7_jJ(?-oshe3~Cm~^b)v_)CUoV6QOjWyaRJ5cA#KC2|`;4F#dKElTx2;l1k!QJ%C9 zyDyzdXVoxyTl_I}ua;CnIDX0xpE;0$>L(;8QjJwymHe`eLx=>A%>r|y%xH!{6|zp} z!>#JnI$r%spyI`qbUy+9_rNiEGQPrWY`c;W3Q%Bv9Nlr6_%L;P#3IkxsguM#`Q3fT z9!Zm;!!>nAS!l1_dY)F$2@J74>PeapskX3GuWi1sioVZ+n|7YgX zx&P|cUITqdkl83*U(n09?X)m-44&j2fg`92AC({E~7o;Le zg0E3=?X>v9ItE+a zF+QKV1H<)Jr`Bm&+bl_lEKYzs(VHbMb^FekGljqx18L%B`Gn^#1;D#T6n^S+d=V;@ zLU`>>-Oai<23L4Cs?}qFsTg``RqMz*_iw?`eFfoe?BROC?M&$xS9cZJzamciLK<^RkgchqQu*>cNtlCou2nQVtJFVa5nsx0Fj{@c8#d} z@9yJERI~!(YpEe$XtJjqNS@$Z8}uyrsDc2d*J=NNpO8K*RTX#=m0|dg1tq81{l0Z#K9cKfNE-081bce%@=3{v7op3YY}8)3^d% z%J4vwchHmUp7Mj_)4iojC8xbsul>L3Puq~*E`ng)N0oFJb&=w?rEAF&zer*+OUb7$t-t`wjV9gj!JMds$h)ejBhhZoY1fq--)M$`4nb!%& zOCm)3au?d|qU%&k-~*609~39TOMW4KZkPo3Z#gs=!Owf39;ir^)SF-%3m&SE=&sGL zk?(0QJa@a>EBomn9L7XK5jgo*R{f{XdeP9$xw$!iO&Yk1j)~4lgTRbtFaw->=l9M3;aMEG@IyCO5dCokMxX*qs7v9^%z#{T&(PO`oyqQoz*m}VV_4~F} z*@v;%8d-INzidCfp|74n*Z2f;*NU{f`g?uEYC;)6j)5-A!Wl9~oh#pOOZIAiHWJTi zTYj@*Q;*0h@@sqkO2j5vF-Qz>grV{sPLqm)u=aQG6IrUyr`5}I@BR9uOFy+4hmpG9 zhwy_0jr}FaWFzc)B*iWRH4}^zsqblrV;X&>p0-I@3V$=o58v`W?KXlxj5UH^m>)M1 zJas`>pUxI@e%V%o4KuROd-H>=6AmjHg6|TdB>y)u1ztqkYs^?RcaAU+EJ69*8rn;p zXARF#0YkIxQk}T-)G62dL#wKTTb>|pywTfSz8lWTM@h@^6Sl0jN3I$E6yb^;TTkpP>mN(vca$ZIhBr4_8nMf1 z5=i|nxVg-z4fsv!^l(p`J?kCSmMxQ;z0_8hQV9(FGwH~6+EDIcb%!pbnL4jUKeyMy z4Z}O89yn`gE(M&zG%C9vX_kQtTW1gm%Fz(ZCrBk{dO}1?^I6ThW9H2 zOU0{~mgLeifz%tS>V`T?U%EFXu@~BXbY?Arloj?wH3)!h+CH$W-0M0rueSvzC5QCx{WJQ27RUQ6FaEjHe7E@B{p%v?v`HJZ1o(@ zud7uhEVxxOYgK&8*WMZup^sNSRV8Rx_+{=*6i?efKD31NsDO!5z+|CgRdB^N=23DAQK4mt~a;y{=B7%YS8J#M5pACs`}gH>694&AdgfT+}b_!Hkm zLz?5G`T4RiLbDK_&B% zm#bMgs|ko0G)Xh6wA7} zbprK7yxQ`5*K5sxEjz$23~k}x#fIzj8ii#g zSqUCr`%}y!tsm|9;wcLER@lj!VHiqR`OC7P+iGK&#lzlMZJ={hI?ksy5bc>L-6Z(4 zE)TvISxpeX)Ef`HL2jRb%#=6e{lj33Uko#6aSAIa1oyidg_FW~`S#=6(qdba3w$70 zhwdU>B2^Lb(mWTq`I$Ms@RZ*Kz4p_+n^DJNu@BAova%$;)E9D@V+}=!emNgeu&1u; zV;PO_$Emab$=W?%j>{a_@|00k5R35f)^-&qTDJ&DDxbi5JP|2uP8BlSVA8Soh%qdmIM;IVL1s?*c&z2=}aqOtWq65_&Emt8`UiISQmN%7Sy`nxG8sf8@BFE#s zHGaQs%WM~5sFY=TzEIW9fS7XLLRv@923wEgKEg4bLQg{Kh_kXaLxPrjq_CKC^NrUg zl^*WG1L)FIB$v}NJkcQHfY|JNO=MyxxMm2F_m#vs>^Ur?e;E*R%c$36KCYmTWszOv z}!DSTbc{hdFA=0a1q-g#j}?vu{(uoi9xLMf6hIHGNRf!pg#6ye*MQ zLS#mO0-NCtoru=O!53;3T&T(bE$Z4)IsqP8V!}chIc~eR7Y~#{jH6HIji*#52guIQ z;cC3t;Fpq4|G;!(LQbNM`1|M1o8-GzNP%74zht|yk#SMz4RAQv6 zU}>BPZQc5MahI6#2?e3CCkrQ4bPGl*4rD=@(=aw?{Z+X|6YEe+Do5C;T=V(LaN=i6 zh=WT*J~;tS;7v`2$ux^he3FGs^OTh#zO(qu(~vOL(?^O@?W;OZTzTC@_bC6xm)c*^ z_!)77H~yc}R;@bY8!(Eo;nTd`iJj;OS+TJ4!cN9?6~u?{(r^VWJ}Yl%RCVa_>!i;_ zB~qbi#9s@wu;7|F%%t30#bL7egYr=gG#&URkCInly^v3a0Q?cyuKb1H!{2%v3~v!- zPGn(*|HzcpgqWc!xy4zUhwOf(cD=I+QY4r1ejb`};FDF$TVj6A+T0|wuD9x(Q1ZJi ziF>^#!Z7U#WTP!K!gz2wPD>-A>+#Y_+^pAVF4Ja(<>Q&>aeFvrUqabeUUQ1_3hJu6 ziEvBJ0h83h2ct9@w%@m{`;*8!N#4!pn0dQnl_%iC%3O)oyvevNVlgU#(zWJ4EkjAct9=9q z!e-j?*FchCu!%yoq1R3sZaOVUA`E(YKB(TWo+XS?!6FW+erL3v-*IdpL<}ecl#mL_$ z?KiENlgjMETvm5!6|7?cov(8>dhGe;?&;9Xe7k>*<%!f}hNLiLiB<0OAHlZ$e2Kbd z0{_lf#P!L+Ltr}S-!|t;3W+QZ=Eu`BZoBq(JC|JP&mekxg2vY>@*$ytS1pXD^Su~W zhNCGn)%%ygke5hGMMuQ3E*c7kj`{oi4J|PF^Esrj{t3XhSbbhT2DVgjA zR_b^qsTfs7{P9PaN%CaqGostNTLQ1J=(UCEY{D_&WE)u0f(hJ3&`=V|{e%;?&g-ay z_bFL_80z9_1mJ2)E7u7^|JjRmX@tHb@K(`xJ7+DtRjm3<4|*pSlow6zYKGb*SaO~= zEV^)LR4b6pzUkE#5c_-6x|LM@?g8*53)nPP-V%0C3ci&ty^Ad2=pdV-I+dU)`t6$5 zXVwR~oY$70ZIEd`>@NP58N~!;RJO;vm8G$(_aZ7yUA04JjxO(oz3ch(=c!S{I<|}B zbMwDLczQvVq`>HCE`dRa_J+!Lsn6M>@L?u3m&hQ2=^=x03^_aGi(0CxWqb%PyiA&e zBCao$ek+6;6 zSJtKlSn$q_pB#zznB>!(>l<4!nGRYi4-#P}ru*YSHh$6-R+2rAy*d4AJvOYrS`?uQt5Q=`&+ZrdaEJO^Q6;xx(+6&ES z{C#R0$zriiQ6>&?HyM%Ufy8h$5(uB!mR`M4EV#kc%uf3v0%ml zH~h~c@>l7+Sm~|{Oo^6)gZI`TbbZQoD0VD*m?;vOr6)!o)FpxDo#*&5y2UZN4EdeFCwu!7T{I{tA>&&b1a}>kIOrOT@KNhfgr7h2v*{3`d>_ zA5XCT1P^gkZ9sRIpB|R~hc0~J-p1`mBGg6~ZgyZ}LZDLbBJ|Fq(MP&W#db+Tfu}hH z?yNzJUT@;nTRY|BL6WdM2@TWV)fhK};-IO->hzORmO$&C)5LXTVkCi~H& z47& zylyjY63j%?1SQkl4Xdw3ea~0!DA+SN)%1Sgo=awj4=vJA@ZKZ~724~4!{Xlw7kn08 zP9g+}(N|n2lM2E+0)UfGz~#c=Bv!~w-YpG%6GV%`(gi6p6*Vb`DJ_FuUuT_I*|4ww zt|2TiU_qnfnG7AFrPSR=0qFo9T@6jmfLmm2ixLaxgbF>pMm49?0Grg1M>icg0U%k2 z)PqAV?oBE$h7@L2iJ~El+HMgrq|ZFCzgX3`goK+(j>rZqG7)tqlYdt^U`YL0FsL%K zx9>;$xWxab>`#jDE2ouY>+j1?uG*vl(k_brYiqu_ap5!>U_TWW6*+fOTQAnHexd!i zDywiF|B4r(LkZVl_{q5d@<57HI5dyvM}hOUPj#Ss0O}EJY-}DkydEpiQ!l-v6!pi4 zF|qeU<4yyfW6L>P&Fh&UR69Q4r1t>Nyg$fFj@!0-%6_e+@SgV+-y{nYU$Zn-tw@Bg zg6M7sCB$Y4f#iV@*0pk}epTnUv+rjMlPxFJ-=cpz{S+Zy$9p(3w;K0ctxf85_B~+9 z%dV&(shtN+b1fHkv!E?3A=(*aL9+@Am647h_gB*@L-JRhhZ+I2p*ja8-$a}M`r~@A zBxzU2W~TTy$*}tj?_1Vix4px}!Fq2S?M!u|E+itd1d`=Xj2#^uCR(l75-%Y{H+y=- zZ6lAigU$alyC{frmlJL%00*gG%g}H~voYRI_~Y@wO#U~L=z4E_A!>*+`<-F;Q)*dr z2sQa7z%#CJmvq?ia%SNsC@2W)X|h1a(Y|Xv5oAAIi3wh7g7K+Wb3t+O(~Ia3EMqY4 ziJhqf$CuQJ{$Kr{q02&RIDx|?A+1etWj=qoyfW$><{EMs{M>e20rJ9OGxZ5z9(85R$}bXZ8?a4 zC#B0$nJ+^vs{=jv&&7hLu$8;Ha|yvBzMf>3{ya$%PlDZ7mcLP+n4DbBO*HyG=NCU0|Mav=L-)D29sqcn&voT#1ib`h>*d_;9_Z&@zSt~d zJX(FMFdajU(9o)CzFo&{1T*ZyHR(Z5rg;7VaT$DNvl)t5c3C`n@)lFN>dKWLy082r zYkzLG-n9bMH1w7Y0ur^D$9KO*8|Pi3s_%)Ujx?mzV?(f>)EvS=Elyw-$_?m8Bkn;D zmWK%in7?GUe=v3n0ttOpO%W>hav~E=&J?b0wgH7Z!9Ow)^b0nOVOI0l9IMEQIM1+B zMQn<{p#E#4PBkZDjKRjh?3pt2@6fak>%p!6<@djWPxteb32(L{Gb2o z%05AU7J;Sqi~63!ceO80E zsX=HWt^xZf)#i^=m!N6vMlWAY-ZzA`V7W#4rW>b5SaJ994R=ltIG6ri4PshwZ@gLFKM-5TZ{F4p^ilppwHrri!$<=n*S(30zqj%$@Tc920A z(z(F(rFs9IVmH0_+P~uiN{p%))i&dsNF@4)UgTzugg3YlMKNlpY7g9@0GfgZRGfNK z%Qi!S6bOX}`=H*^WMWM&9qTXkVLfU<0}z%4)<H>lH+Xx5N;?{qwQ>o~JV1*I`H2e0(bV|3(1bj}(ip`M_g)5ZYaSRG3H863 zbG^hW=c4*h2;<3r=feBq3+aD-4%AUUNV;Ako#9d>ngUpGfT5Y&3)NtXp>B%%pPM>t z;+q7|qXl6yDJXpX&$IIbz8wc<+IIJ6%y^qoAgWVgPZh?n|NT6r(08waZVmU*ew%5l zpEsy*;V68l2`?l?jV9L&Xt*BnJus`EM>O;2KR$4RXwU^}-Lu=NyOP zzr#ht*jTbGP*>P!C3^8?eq70{%d^MrP&s2mLjwdY zcSdsUB?A&2%^L834WMP$Mmca4BmV5wrVFY5$dnHTIv=K}>EcJ%x)2S3;Y|T?2N1M< z%hb30l6&%f~;yu7?ewiIb|jqb}R&>|qs ztp-vxVCO)ULM<~`OhylLSegpr;UJMybe?h zT=-lAZU6*IlBcB5_-s5+mwW#FxmuToS6W)y*)k(C#P{;#_qS2CAK+(Gt4X@Xz7%E6 zCp0}hJ>{VI5U?xU%Qyd-l4pC?Ykcz#=tXR`d@@jj&<4sVF6nAbe_%Boji@-)8=}e; zK?{3vY7{dXP$NmQOz;nQx0e7Eydo&Ncuyo9f}(J!uC5-+*U@UZIWAlNj>p>$pp}Q_ z<|51dj*9@3IYUEZk6FlotCG zRlgi1;RLXav#YBqHYZAc6zf-&dmV2SM>D^Qd5nRAI3^ICg_oA{2#Ja=1NxoLcwM99 zH?!zOlJKelaXf57Is~fp<+-{Pg}UUv!bBJGItE4iY0IgUrm-=v!HX9kh~+@lX84m> zwonQ#9rClju-=Q~O+_J^apc^@1e@KfR~^2mbNLG=U}Sh@lUxAxkv))@g)}q-pf880 z`(KRe)61U#05WA@J1C+op6{E-Y`)uI93)VCXC&?M3{S%v%l>|}zhsd)NAvu=5x?J+ zhcl>;Wt(dO43O8z*3)@!IZg6?u*hq*+{P`2sZQT-fxE6Z?|0Io!Kc32#`?|R@is9* zApo-R7IUDO%b$?FbDt&M){A(*K43y~gJCKLhG9BSZm0~LB>nCeykDu_z>ASjCQAxNJdmQ$QcJTV` zhfBj2!4-Ga#Mg6jX1@4c*k*EsiMeehZG&mBfANrmhGd44fKlqLU~Zm0B&6E94Y-eP zgHSE^3wuT|dgRR|8eFf{ui0!^TOE@a_)$Nl@ZTR3=a*GW>|Cpgd& z!1e#;iyuP*;zouk`5XnlUoF4`2Etx9r09PD(7|SH4n()fNHHDU|#d!eewfJ+B!p?tG!^EcJMlb zb&Wh(*ORtqYRwP+bZd|+wyL)5%+xy8`r_w`0vqY-AhET5RR-xf>-2-*?ECE&IEwHr zTKa;6hK2@eH|ibER$|{KNf&cwnRRd_VT2GC8{1%JLE%p=4=`yiH^H90>Y zg|fAWvlQz#3X6_rMqh@5dhZ!#7>cB!ry$g(ppRX6waPQ(aN$ z@}udV%otaG{=XK&$H0~aGUy|B5@zza@ zE=lBd3Tn#&*g!N0?4SGvw_mpT4>ifRX6wmhx8BYJ5)&cS(dd}6%Lr=0|K7Pac6KB0 zWuPPgwLa@0T4O(r#&lx9@W2Jbuhm$_YO?fY$fN8hlPshB3Quqw(48?Z!2!Q-XJ^+A zc)w6G<;|NAK+P5g804xD);fk)eyvG>!v_e?FKcUSd{Qf+>|cl-YG2qdw7kS2Df%e6 zo)h~i?9CRP{4_roS`0-D3Vfef4o6$N1Dr6f0dSwPaIm)Ym<| zy&XWrjpvxR9H#At0N$MnP|@f-@3|V<)1$mU@xsy47hga8QT9?+I1edMS4-i>S6Ou@ zzg{T-rBe@rMrJ^fw~^nuB@jL+w&^PC!5!B=ph@?D z=av2K8#(G(G_E?VD<>F2X!cnROsKW}oaZVJLdw?tiN=!RZ zrq06Eis+N*Ym_&f@~ZTqx3`4I>tBH=I*f(O`BU7Zr=cNR=D>_rEGa1=05%6Os9+GN z_ciMXqY&F~CsU2yU0-h-^g9up1)8Oxq(l+iA|)lI9PCxelPU8jT|9<$#DIJ_7&Jkk z%omrx%948sbo86lkdTXB?KLtc7MjPgY^vX_r4On5K8q41zI3Ce19w3DTu@Me04IpOx9iiq*JeqMf0=$2 z79dMf@bvU-Nyj45H2Sv%YCv=VB`G}q#_Ku(QWg|OE09w^0BsZuLcIf!R>ES=#uC;SxpL0T{ibfC2P-+B&@hNE}}v zdn$=Rq=ADg?D6$u6$LGe8=&78f!=;l=?PA#GoS~hxX=m-sqADm`5zxjld!O`5RfV9tc^0U^xR5>|Hs?