From 5311039f38b2f99f72e1799fcac28a07f6fe7d5c Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Fri, 26 Jun 2026 22:54:12 +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: mlfoundations-dev/bespoke_stratos_0.3k Source: Original Platform --- .gitattributes | 56 ++ README.md | 61 +++ added_tokens.json | 24 + all_results.json | 8 + config.json | 29 ++ configs.yaml | 37 ++ configuration.json | 1 + generation_config.json | 14 + merges.txt | 3 + model-00001-of-00004.safetensors | 3 + model-00002-of-00004.safetensors | 3 + model-00003-of-00004.safetensors | 3 + model-00004-of-00004.safetensors | 3 + model.safetensors.index.json | 346 +++++++++++++ special_tokens_map.json | 31 ++ tokenizer.json | 3 + tokenizer_config.json | 208 ++++++++ train_results.json | 8 + trainer_log.jsonl | 118 +++++ trainer_state.json | 861 +++++++++++++++++++++++++++++++ training_args.bin | 3 + training_loss.png | Bin 0 -> 45117 bytes vocab.json | 3 + 23 files changed, 1826 insertions(+) create mode 100644 .gitattributes create mode 100644 README.md create mode 100644 added_tokens.json create mode 100644 all_results.json create mode 100644 config.json create mode 100644 configs.yaml create mode 100644 configuration.json create mode 100644 generation_config.json create mode 100644 merges.txt create mode 100644 model-00001-of-00004.safetensors create mode 100644 model-00002-of-00004.safetensors create mode 100644 model-00003-of-00004.safetensors create mode 100644 model-00004-of-00004.safetensors create mode 100644 model.safetensors.index.json create mode 100644 special_tokens_map.json 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_loss.png create mode 100644 vocab.json diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..62da7f4 --- /dev/null +++ b/.gitattributes @@ -0,0 +1,56 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text + + +*.bz2 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 +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack 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 +*.pt filter=lfs diff=lfs merge=lfs -text +*.pth filter=lfs diff=lfs merge=lfs -text +*.rar filter=lfs diff=lfs merge=lfs -text +saved_model/**/* 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 +*.xz filter=lfs diff=lfs merge=lfs -text +*.zip filter=lfs diff=lfs merge=lfs -text +*.zstandard filter=lfs diff=lfs merge=lfs -text +*.tfevents* filter=lfs diff=lfs merge=lfs -text +*.db* filter=lfs diff=lfs merge=lfs -text +*.ark* filter=lfs diff=lfs merge=lfs -text +**/*ckpt*data* filter=lfs diff=lfs merge=lfs -text +**/*ckpt*.meta filter=lfs diff=lfs merge=lfs -text +**/*ckpt*.index filter=lfs diff=lfs merge=lfs -text + +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.gguf* filter=lfs diff=lfs merge=lfs -text +*.ggml filter=lfs diff=lfs merge=lfs -text +*.llamafile* filter=lfs diff=lfs merge=lfs -text +*.pt2 filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs -text +*.pickle filter=lfs diff=lfs merge=lfs -text +*.pkl filter=lfs diff=lfs merge=lfs -text +*.tar filter=lfs diff=lfs merge=lfs -text +*.wasm 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 +model-00001-of-00004.safetensors filter=lfs diff=lfs merge=lfs -text +merges.txt filter=lfs diff=lfs merge=lfs -text +training_args.bin filter=lfs diff=lfs merge=lfs -text +model-00002-of-00004.safetensors filter=lfs diff=lfs merge=lfs -text +vocab.json filter=lfs diff=lfs merge=lfs -text +model-00004-of-00004.safetensors filter=lfs diff=lfs merge=lfs -text +model-00003-of-00004.safetensors filter=lfs diff=lfs merge=lfs -text \ No newline at end of file diff --git a/README.md b/README.md new file mode 100644 index 0000000..ef03bb1 --- /dev/null +++ b/README.md @@ -0,0 +1,61 @@ +--- +library_name: transformers +license: apache-2.0 +base_model: Qwen/Qwen2.5-7B-Instruct +tags: +- llama-factory +- full +- generated_from_trainer +model-index: +- name: bespoke_stratos_0.3k + results: [] +--- + + + +# bespoke_stratos_0.3k + +This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) on the mlfoundations-dev/bespoke_stratos_0.3k dataset. + +## Model description + +More information needed + +## Intended uses & limitations + +More information needed + +## Training and evaluation data + +More information needed + +## Training procedure + +### Training hyperparameters + +The following hyperparameters were used during training: +- learning_rate: 1e-05 +- train_batch_size: 1 +- eval_batch_size: 8 +- seed: 42 +- distributed_type: multi-GPU +- num_devices: 4 +- gradient_accumulation_steps: 8 +- total_train_batch_size: 32 +- total_eval_batch_size: 32 +- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments +- lr_scheduler_type: cosine +- lr_scheduler_warmup_ratio: 0.1 +- num_epochs: 13.0 + +### Training results + + + +### Framework versions + +- Transformers 4.46.1 +- Pytorch 2.6.0+cu124 +- Datasets 3.1.0 +- Tokenizers 0.20.3 diff --git a/added_tokens.json b/added_tokens.json new file mode 100644 index 0000000..482ced4 --- /dev/null +++ b/added_tokens.json @@ -0,0 +1,24 @@ +{ + "": 151658, + "": 151657, + "<|box_end|>": 151649, + "<|box_start|>": 151648, + "<|endoftext|>": 151643, + "<|file_sep|>": 151664, + "<|fim_middle|>": 151660, + "<|fim_pad|>": 151662, + "<|fim_prefix|>": 151659, + "<|fim_suffix|>": 151661, + "<|im_end|>": 151645, + "<|im_start|>": 151644, + "<|image_pad|>": 151655, + "<|object_ref_end|>": 151647, + "<|object_ref_start|>": 151646, + "<|quad_end|>": 151651, + "<|quad_start|>": 151650, + "<|repo_name|>": 151663, + "<|video_pad|>": 151656, + "<|vision_end|>": 151653, + "<|vision_pad|>": 151654, + "<|vision_start|>": 151652 +} diff --git a/all_results.json b/all_results.json new file mode 100644 index 0000000..1b79375 --- /dev/null +++ b/all_results.json @@ -0,0 +1,8 @@ +{ + "epoch": 12.30379746835443, + "total_flos": 4.902218749915955e+16, + "train_loss": 0.26980868625080484, + "train_runtime": 2812.7387, + "train_samples_per_second": 1.46, + "train_steps_per_second": 0.042 +} \ No newline at end of file diff --git a/config.json b/config.json new file mode 100644 index 0000000..6c52571 --- /dev/null +++ b/config.json @@ -0,0 +1,29 @@ +{ + "_name_or_path": "Qwen/Qwen2.5-7B-Instruct", + "architectures": [ + "Qwen2ForCausalLM" + ], + "attention_dropout": 0.0, + "bos_token_id": 151643, + "eos_token_id": 151645, + "hidden_act": "silu", + "hidden_size": 3584, + "initializer_range": 0.02, + "intermediate_size": 18944, + "max_position_embeddings": 32768, + "max_window_layers": 28, + "model_type": "qwen2", + "num_attention_heads": 28, + "num_hidden_layers": 28, + "num_key_value_heads": 4, + "rms_norm_eps": 1e-06, + "rope_scaling": null, + "rope_theta": 1000000.0, + "sliding_window": null, + "tie_word_embeddings": false, + "torch_dtype": "bfloat16", + "transformers_version": "4.46.1", + "use_cache": false, + "use_sliding_window": false, + "vocab_size": 152064 +} diff --git a/configs.yaml b/configs.yaml new file mode 100644 index 0000000..3930106 --- /dev/null +++ b/configs.yaml @@ -0,0 +1,37 @@ +assistant_tag: gpt +bf16: true +content_tag: value +cutoff_len: 16384 +dataloader_num_workers: 4 +dataloader_persistent_workers: true +dataloader_pin_memory: true +dataset: mlfoundations-dev/bespoke_stratos_0.3k +dataset_dir: ONLINE +ddp_timeout: 180000000 +deepspeed: dcft/train/zero3.json +do_train: true +enable_liger_kernel: true +finetuning_type: full +global_batch_size: 32 +gradient_accumulation_steps: 8 +hub_model_id: mlfoundations-dev/bespoke_stratos_0.3k +learning_rate: 1.0e-05 +logging_steps: 1 +lr_scheduler_type: cosine +messages: conversations +model_name_or_path: Qwen/Qwen2.5-7B-Instruct +num_train_epochs: 13.0 +output_dir: /data/cat/ws/ryma833h-dcft/checkpoints/bespoke_stratos_0.3k +overwrite_cache: true +per_device_train_batch_size: 1 +plot_loss: true +preprocessing_num_workers: 16 +push_to_db: true +push_to_hub: true +report_to: wandb +role_tag: from +save_strategy: epoch +stage: sft +template: qwen25 +user_tag: human +warmup_ratio: 0.1 diff --git a/configuration.json b/configuration.json new file mode 100644 index 0000000..bbeeda1 --- /dev/null +++ b/configuration.json @@ -0,0 +1 @@ +{"framework": "pytorch", "task": "text-generation", "allow_remote": true} \ No newline at end of file diff --git a/generation_config.json b/generation_config.json new file mode 100644 index 0000000..a753841 --- /dev/null +++ b/generation_config.json @@ -0,0 +1,14 @@ +{ + "bos_token_id": 151643, + "do_sample": true, + "eos_token_id": [ + 151645, + 151643 + ], + "pad_token_id": 151643, + "repetition_penalty": 1.05, + "temperature": 0.7, + "top_k": 20, + "top_p": 0.8, + "transformers_version": "4.46.1" +} diff --git a/merges.txt b/merges.txt new file mode 100644 index 0000000..80c1a19 --- /dev/null +++ b/merges.txt @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:8831e4f1a044471340f7c0a83d7bd71306a5b867e95fd870f74d0c5308a904d5 +size 1671853 diff --git a/model-00001-of-00004.safetensors b/model-00001-of-00004.safetensors new file mode 100644 index 0000000..0116440 --- /dev/null +++ b/model-00001-of-00004.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:a3d9fcdf01a87cbb3f61149e98641014bff4bf229b611173d0c6a58e5375b6e3 +size 4877660776 diff --git a/model-00002-of-00004.safetensors b/model-00002-of-00004.safetensors new file mode 100644 index 0000000..3854b45 --- /dev/null +++ b/model-00002-of-00004.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:881ec43116bda77d6d2f062ea21098042bb225ab2c857c236650b684b5316f85 +size 4932751008 diff --git a/model-00003-of-00004.safetensors b/model-00003-of-00004.safetensors new file mode 100644 index 0000000..fb3011e --- /dev/null +++ b/model-00003-of-00004.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:9c83b48be686e8f7ea49f0b7b29062fda20ff281e2313e517597b44c42184568 +size 4330865200 diff --git a/model-00004-of-00004.safetensors b/model-00004-of-00004.safetensors new file mode 100644 index 0000000..70e3234 --- /dev/null +++ b/model-00004-of-00004.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:41dab64cc81b3b312d37498ad82ced156164342229bf25c4b42d5474e3eb06ce +size 1089994880 diff --git a/model.safetensors.index.json b/model.safetensors.index.json new file mode 100644 index 0000000..6ca5084 --- /dev/null +++ b/model.safetensors.index.json @@ -0,0 +1,346 @@ +{ + "metadata": { + "total_size": 15231233024 + }, + "weight_map": { + "lm_head.weight": "model-00004-of-00004.safetensors", + "model.embed_tokens.weight": "model-00001-of-00004.safetensors", + "model.layers.0.input_layernorm.weight": "model-00001-of-00004.safetensors", + "model.layers.0.mlp.down_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.0.mlp.gate_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.0.mlp.up_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.0.post_attention_layernorm.weight": "model-00001-of-00004.safetensors", + "model.layers.0.self_attn.k_proj.bias": "model-00001-of-00004.safetensors", + "model.layers.0.self_attn.k_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.0.self_attn.o_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.0.self_attn.q_proj.bias": "model-00001-of-00004.safetensors", + "model.layers.0.self_attn.q_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.0.self_attn.v_proj.bias": "model-00001-of-00004.safetensors", + "model.layers.0.self_attn.v_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.1.input_layernorm.weight": "model-00001-of-00004.safetensors", + "model.layers.1.mlp.down_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.1.mlp.gate_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.1.mlp.up_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.1.post_attention_layernorm.weight": "model-00001-of-00004.safetensors", + "model.layers.1.self_attn.k_proj.bias": "model-00001-of-00004.safetensors", + "model.layers.1.self_attn.k_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.1.self_attn.o_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.1.self_attn.q_proj.bias": "model-00001-of-00004.safetensors", + "model.layers.1.self_attn.q_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.1.self_attn.v_proj.bias": "model-00001-of-00004.safetensors", + "model.layers.1.self_attn.v_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.10.input_layernorm.weight": "model-00002-of-00004.safetensors", + "model.layers.10.mlp.down_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.10.mlp.gate_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.10.mlp.up_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.10.post_attention_layernorm.weight": "model-00002-of-00004.safetensors", + "model.layers.10.self_attn.k_proj.bias": "model-00002-of-00004.safetensors", + "model.layers.10.self_attn.k_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.10.self_attn.o_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.10.self_attn.q_proj.bias": "model-00002-of-00004.safetensors", + "model.layers.10.self_attn.q_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.10.self_attn.v_proj.bias": "model-00002-of-00004.safetensors", + "model.layers.10.self_attn.v_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.11.input_layernorm.weight": "model-00002-of-00004.safetensors", + "model.layers.11.mlp.down_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.11.mlp.gate_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.11.mlp.up_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.11.post_attention_layernorm.weight": "model-00002-of-00004.safetensors", + "model.layers.11.self_attn.k_proj.bias": "model-00002-of-00004.safetensors", + "model.layers.11.self_attn.k_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.11.self_attn.o_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.11.self_attn.q_proj.bias": "model-00002-of-00004.safetensors", + "model.layers.11.self_attn.q_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.11.self_attn.v_proj.bias": "model-00002-of-00004.safetensors", + "model.layers.11.self_attn.v_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.12.input_layernorm.weight": "model-00002-of-00004.safetensors", + "model.layers.12.mlp.down_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.12.mlp.gate_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.12.mlp.up_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.12.post_attention_layernorm.weight": "model-00002-of-00004.safetensors", + "model.layers.12.self_attn.k_proj.bias": "model-00002-of-00004.safetensors", + "model.layers.12.self_attn.k_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.12.self_attn.o_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.12.self_attn.q_proj.bias": "model-00002-of-00004.safetensors", + "model.layers.12.self_attn.q_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.12.self_attn.v_proj.bias": "model-00002-of-00004.safetensors", + "model.layers.12.self_attn.v_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.13.input_layernorm.weight": "model-00002-of-00004.safetensors", + "model.layers.13.mlp.down_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.13.mlp.gate_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.13.mlp.up_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.13.post_attention_layernorm.weight": "model-00002-of-00004.safetensors", + "model.layers.13.self_attn.k_proj.bias": "model-00002-of-00004.safetensors", + "model.layers.13.self_attn.k_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.13.self_attn.o_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.13.self_attn.q_proj.bias": "model-00002-of-00004.safetensors", + "model.layers.13.self_attn.q_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.13.self_attn.v_proj.bias": "model-00002-of-00004.safetensors", + "model.layers.13.self_attn.v_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.14.input_layernorm.weight": "model-00002-of-00004.safetensors", + "model.layers.14.mlp.down_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.14.mlp.gate_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.14.mlp.up_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.14.post_attention_layernorm.weight": "model-00002-of-00004.safetensors", + "model.layers.14.self_attn.k_proj.bias": "model-00002-of-00004.safetensors", + "model.layers.14.self_attn.k_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.14.self_attn.o_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.14.self_attn.q_proj.bias": "model-00002-of-00004.safetensors", + "model.layers.14.self_attn.q_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.14.self_attn.v_proj.bias": "model-00002-of-00004.safetensors", + "model.layers.14.self_attn.v_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.15.input_layernorm.weight": "model-00002-of-00004.safetensors", + "model.layers.15.mlp.down_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.15.mlp.gate_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.15.mlp.up_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.15.post_attention_layernorm.weight": "model-00002-of-00004.safetensors", + "model.layers.15.self_attn.k_proj.bias": "model-00002-of-00004.safetensors", + "model.layers.15.self_attn.k_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.15.self_attn.o_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.15.self_attn.q_proj.bias": "model-00002-of-00004.safetensors", + "model.layers.15.self_attn.q_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.15.self_attn.v_proj.bias": "model-00002-of-00004.safetensors", + "model.layers.15.self_attn.v_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.16.input_layernorm.weight": "model-00002-of-00004.safetensors", + "model.layers.16.mlp.down_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.16.mlp.gate_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.16.mlp.up_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.16.post_attention_layernorm.weight": "model-00002-of-00004.safetensors", + "model.layers.16.self_attn.k_proj.bias": "model-00002-of-00004.safetensors", + "model.layers.16.self_attn.k_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.16.self_attn.o_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.16.self_attn.q_proj.bias": "model-00002-of-00004.safetensors", + "model.layers.16.self_attn.q_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.16.self_attn.v_proj.bias": "model-00002-of-00004.safetensors", + "model.layers.16.self_attn.v_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.17.input_layernorm.weight": "model-00002-of-00004.safetensors", + "model.layers.17.mlp.down_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.17.mlp.gate_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.17.mlp.up_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.17.post_attention_layernorm.weight": "model-00002-of-00004.safetensors", + "model.layers.17.self_attn.k_proj.bias": "model-00002-of-00004.safetensors", + "model.layers.17.self_attn.k_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.17.self_attn.o_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.17.self_attn.q_proj.bias": "model-00002-of-00004.safetensors", + "model.layers.17.self_attn.q_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.17.self_attn.v_proj.bias": "model-00002-of-00004.safetensors", + "model.layers.17.self_attn.v_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.18.input_layernorm.weight": "model-00003-of-00004.safetensors", + "model.layers.18.mlp.down_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.18.mlp.gate_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.18.mlp.up_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.18.post_attention_layernorm.weight": "model-00003-of-00004.safetensors", + "model.layers.18.self_attn.k_proj.bias": "model-00002-of-00004.safetensors", + "model.layers.18.self_attn.k_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.18.self_attn.o_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.18.self_attn.q_proj.bias": "model-00002-of-00004.safetensors", + "model.layers.18.self_attn.q_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.18.self_attn.v_proj.bias": "model-00002-of-00004.safetensors", + "model.layers.18.self_attn.v_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.19.input_layernorm.weight": "model-00003-of-00004.safetensors", + "model.layers.19.mlp.down_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.19.mlp.gate_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.19.mlp.up_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.19.post_attention_layernorm.weight": "model-00003-of-00004.safetensors", + "model.layers.19.self_attn.k_proj.bias": "model-00003-of-00004.safetensors", + "model.layers.19.self_attn.k_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.19.self_attn.o_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.19.self_attn.q_proj.bias": "model-00003-of-00004.safetensors", + "model.layers.19.self_attn.q_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.19.self_attn.v_proj.bias": "model-00003-of-00004.safetensors", + "model.layers.19.self_attn.v_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.2.input_layernorm.weight": "model-00001-of-00004.safetensors", + "model.layers.2.mlp.down_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.2.mlp.gate_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.2.mlp.up_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.2.post_attention_layernorm.weight": "model-00001-of-00004.safetensors", + "model.layers.2.self_attn.k_proj.bias": "model-00001-of-00004.safetensors", + "model.layers.2.self_attn.k_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.2.self_attn.o_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.2.self_attn.q_proj.bias": "model-00001-of-00004.safetensors", + "model.layers.2.self_attn.q_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.2.self_attn.v_proj.bias": "model-00001-of-00004.safetensors", + "model.layers.2.self_attn.v_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.20.input_layernorm.weight": "model-00003-of-00004.safetensors", + "model.layers.20.mlp.down_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.20.mlp.gate_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.20.mlp.up_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.20.post_attention_layernorm.weight": "model-00003-of-00004.safetensors", + "model.layers.20.self_attn.k_proj.bias": "model-00003-of-00004.safetensors", + "model.layers.20.self_attn.k_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.20.self_attn.o_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.20.self_attn.q_proj.bias": "model-00003-of-00004.safetensors", + "model.layers.20.self_attn.q_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.20.self_attn.v_proj.bias": "model-00003-of-00004.safetensors", + "model.layers.20.self_attn.v_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.21.input_layernorm.weight": "model-00003-of-00004.safetensors", + "model.layers.21.mlp.down_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.21.mlp.gate_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.21.mlp.up_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.21.post_attention_layernorm.weight": "model-00003-of-00004.safetensors", + "model.layers.21.self_attn.k_proj.bias": "model-00003-of-00004.safetensors", + "model.layers.21.self_attn.k_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.21.self_attn.o_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.21.self_attn.q_proj.bias": "model-00003-of-00004.safetensors", + "model.layers.21.self_attn.q_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.21.self_attn.v_proj.bias": "model-00003-of-00004.safetensors", + "model.layers.21.self_attn.v_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.22.input_layernorm.weight": "model-00003-of-00004.safetensors", + "model.layers.22.mlp.down_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.22.mlp.gate_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.22.mlp.up_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.22.post_attention_layernorm.weight": "model-00003-of-00004.safetensors", + "model.layers.22.self_attn.k_proj.bias": "model-00003-of-00004.safetensors", + "model.layers.22.self_attn.k_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.22.self_attn.o_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.22.self_attn.q_proj.bias": "model-00003-of-00004.safetensors", + "model.layers.22.self_attn.q_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.22.self_attn.v_proj.bias": "model-00003-of-00004.safetensors", + "model.layers.22.self_attn.v_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.23.input_layernorm.weight": "model-00003-of-00004.safetensors", + "model.layers.23.mlp.down_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.23.mlp.gate_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.23.mlp.up_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.23.post_attention_layernorm.weight": "model-00003-of-00004.safetensors", + "model.layers.23.self_attn.k_proj.bias": "model-00003-of-00004.safetensors", + "model.layers.23.self_attn.k_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.23.self_attn.o_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.23.self_attn.q_proj.bias": "model-00003-of-00004.safetensors", + "model.layers.23.self_attn.q_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.23.self_attn.v_proj.bias": "model-00003-of-00004.safetensors", + "model.layers.23.self_attn.v_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.24.input_layernorm.weight": "model-00003-of-00004.safetensors", + "model.layers.24.mlp.down_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.24.mlp.gate_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.24.mlp.up_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.24.post_attention_layernorm.weight": "model-00003-of-00004.safetensors", + "model.layers.24.self_attn.k_proj.bias": "model-00003-of-00004.safetensors", + "model.layers.24.self_attn.k_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.24.self_attn.o_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.24.self_attn.q_proj.bias": "model-00003-of-00004.safetensors", + "model.layers.24.self_attn.q_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.24.self_attn.v_proj.bias": "model-00003-of-00004.safetensors", + "model.layers.24.self_attn.v_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.25.input_layernorm.weight": "model-00003-of-00004.safetensors", + "model.layers.25.mlp.down_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.25.mlp.gate_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.25.mlp.up_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.25.post_attention_layernorm.weight": "model-00003-of-00004.safetensors", + "model.layers.25.self_attn.k_proj.bias": "model-00003-of-00004.safetensors", + "model.layers.25.self_attn.k_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.25.self_attn.o_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.25.self_attn.q_proj.bias": "model-00003-of-00004.safetensors", + "model.layers.25.self_attn.q_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.25.self_attn.v_proj.bias": "model-00003-of-00004.safetensors", + "model.layers.25.self_attn.v_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.26.input_layernorm.weight": "model-00003-of-00004.safetensors", + "model.layers.26.mlp.down_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.26.mlp.gate_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.26.mlp.up_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.26.post_attention_layernorm.weight": "model-00003-of-00004.safetensors", + "model.layers.26.self_attn.k_proj.bias": "model-00003-of-00004.safetensors", + "model.layers.26.self_attn.k_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.26.self_attn.o_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.26.self_attn.q_proj.bias": "model-00003-of-00004.safetensors", + "model.layers.26.self_attn.q_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.26.self_attn.v_proj.bias": "model-00003-of-00004.safetensors", + "model.layers.26.self_attn.v_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.27.input_layernorm.weight": "model-00003-of-00004.safetensors", + "model.layers.27.mlp.down_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.27.mlp.gate_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.27.mlp.up_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.27.post_attention_layernorm.weight": "model-00003-of-00004.safetensors", + "model.layers.27.self_attn.k_proj.bias": "model-00003-of-00004.safetensors", + "model.layers.27.self_attn.k_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.27.self_attn.o_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.27.self_attn.q_proj.bias": "model-00003-of-00004.safetensors", + "model.layers.27.self_attn.q_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.27.self_attn.v_proj.bias": "model-00003-of-00004.safetensors", + "model.layers.27.self_attn.v_proj.weight": "model-00003-of-00004.safetensors", + "model.layers.3.input_layernorm.weight": "model-00001-of-00004.safetensors", + "model.layers.3.mlp.down_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.3.mlp.gate_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.3.mlp.up_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.3.post_attention_layernorm.weight": "model-00001-of-00004.safetensors", + "model.layers.3.self_attn.k_proj.bias": "model-00001-of-00004.safetensors", + "model.layers.3.self_attn.k_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.3.self_attn.o_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.3.self_attn.q_proj.bias": "model-00001-of-00004.safetensors", + "model.layers.3.self_attn.q_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.3.self_attn.v_proj.bias": "model-00001-of-00004.safetensors", + "model.layers.3.self_attn.v_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.4.input_layernorm.weight": "model-00001-of-00004.safetensors", + "model.layers.4.mlp.down_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.4.mlp.gate_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.4.mlp.up_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.4.post_attention_layernorm.weight": "model-00001-of-00004.safetensors", + "model.layers.4.self_attn.k_proj.bias": "model-00001-of-00004.safetensors", + "model.layers.4.self_attn.k_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.4.self_attn.o_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.4.self_attn.q_proj.bias": "model-00001-of-00004.safetensors", + "model.layers.4.self_attn.q_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.4.self_attn.v_proj.bias": "model-00001-of-00004.safetensors", + "model.layers.4.self_attn.v_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.5.input_layernorm.weight": "model-00001-of-00004.safetensors", + "model.layers.5.mlp.down_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.5.mlp.gate_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.5.mlp.up_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.5.post_attention_layernorm.weight": "model-00001-of-00004.safetensors", + "model.layers.5.self_attn.k_proj.bias": "model-00001-of-00004.safetensors", + "model.layers.5.self_attn.k_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.5.self_attn.o_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.5.self_attn.q_proj.bias": "model-00001-of-00004.safetensors", + "model.layers.5.self_attn.q_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.5.self_attn.v_proj.bias": "model-00001-of-00004.safetensors", + "model.layers.5.self_attn.v_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.6.input_layernorm.weight": "model-00001-of-00004.safetensors", + "model.layers.6.mlp.down_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.6.mlp.gate_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.6.mlp.up_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.6.post_attention_layernorm.weight": "model-00001-of-00004.safetensors", + "model.layers.6.self_attn.k_proj.bias": "model-00001-of-00004.safetensors", + "model.layers.6.self_attn.k_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.6.self_attn.o_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.6.self_attn.q_proj.bias": "model-00001-of-00004.safetensors", + "model.layers.6.self_attn.q_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.6.self_attn.v_proj.bias": "model-00001-of-00004.safetensors", + "model.layers.6.self_attn.v_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.7.input_layernorm.weight": "model-00001-of-00004.safetensors", + "model.layers.7.mlp.down_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.7.mlp.gate_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.7.mlp.up_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.7.post_attention_layernorm.weight": "model-00001-of-00004.safetensors", + "model.layers.7.self_attn.k_proj.bias": "model-00001-of-00004.safetensors", + "model.layers.7.self_attn.k_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.7.self_attn.o_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.7.self_attn.q_proj.bias": "model-00001-of-00004.safetensors", + "model.layers.7.self_attn.q_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.7.self_attn.v_proj.bias": "model-00001-of-00004.safetensors", + "model.layers.7.self_attn.v_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.8.input_layernorm.weight": "model-00002-of-00004.safetensors", + "model.layers.8.mlp.down_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.8.mlp.gate_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.8.mlp.up_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.8.post_attention_layernorm.weight": "model-00002-of-00004.safetensors", + "model.layers.8.self_attn.k_proj.bias": "model-00001-of-00004.safetensors", + "model.layers.8.self_attn.k_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.8.self_attn.o_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.8.self_attn.q_proj.bias": "model-00001-of-00004.safetensors", + "model.layers.8.self_attn.q_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.8.self_attn.v_proj.bias": "model-00001-of-00004.safetensors", + "model.layers.8.self_attn.v_proj.weight": "model-00001-of-00004.safetensors", + "model.layers.9.input_layernorm.weight": "model-00002-of-00004.safetensors", + "model.layers.9.mlp.down_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.9.mlp.gate_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.9.mlp.up_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.9.post_attention_layernorm.weight": "model-00002-of-00004.safetensors", + "model.layers.9.self_attn.k_proj.bias": "model-00002-of-00004.safetensors", + "model.layers.9.self_attn.k_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.9.self_attn.o_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.9.self_attn.q_proj.bias": "model-00002-of-00004.safetensors", + "model.layers.9.self_attn.q_proj.weight": "model-00002-of-00004.safetensors", + "model.layers.9.self_attn.v_proj.bias": "model-00002-of-00004.safetensors", + "model.layers.9.self_attn.v_proj.weight": "model-00002-of-00004.safetensors", + "model.norm.weight": "model-00003-of-00004.safetensors" + } +} diff --git a/special_tokens_map.json b/special_tokens_map.json new file mode 100644 index 0000000..17305b3 --- /dev/null +++ b/special_tokens_map.json @@ -0,0 +1,31 @@ +{ + "additional_special_tokens": [ + "<|im_start|>", + "<|im_end|>", + "<|object_ref_start|>", + "<|object_ref_end|>", + "<|box_start|>", + "<|box_end|>", + "<|quad_start|>", + "<|quad_end|>", + "<|vision_start|>", + "<|vision_end|>", + "<|vision_pad|>", + "<|image_pad|>", + "<|video_pad|>" + ], + "eos_token": { + "content": "<|endoftext|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + }, + "pad_token": { + "content": "<|endoftext|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + } +} diff --git a/tokenizer.json b/tokenizer.json new file mode 100644 index 0000000..51ebb3b --- /dev/null +++ b/tokenizer.json @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:9c5ae00e602b8860cbd784ba82a8aa14e8feecec692e7076590d014d7b7fdafa +size 11421896 diff --git a/tokenizer_config.json b/tokenizer_config.json new file mode 100644 index 0000000..b84f53a --- /dev/null +++ b/tokenizer_config.json @@ -0,0 +1,208 @@ +{ + "add_bos_token": false, + "add_prefix_space": false, + "added_tokens_decoder": { + "151643": { + "content": "<|endoftext|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "151644": { + "content": "<|im_start|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "151645": { + "content": "<|im_end|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "151646": { + "content": "<|object_ref_start|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "151647": { + "content": "<|object_ref_end|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "151648": { + "content": "<|box_start|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "151649": { + "content": "<|box_end|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "151650": { + "content": "<|quad_start|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "151651": { + "content": "<|quad_end|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "151652": { + "content": "<|vision_start|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "151653": { + "content": "<|vision_end|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "151654": { + "content": "<|vision_pad|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "151655": { + "content": "<|image_pad|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "151656": { + "content": "<|video_pad|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "151657": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": false + }, + "151658": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": false + }, + "151659": { + "content": "<|fim_prefix|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": false + }, + "151660": { + "content": "<|fim_middle|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": false + }, + "151661": { + "content": "<|fim_suffix|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": false + }, + "151662": { + "content": "<|fim_pad|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": false + }, + "151663": { + "content": "<|repo_name|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": false + }, + "151664": { + "content": "<|file_sep|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": false + } + }, + "additional_special_tokens": [ + "<|im_start|>", + "<|im_end|>", + "<|object_ref_start|>", + "<|object_ref_end|>", + "<|box_start|>", + "<|box_end|>", + "<|quad_start|>", + "<|quad_end|>", + "<|vision_start|>", + "<|vision_end|>", + "<|vision_pad|>", + "<|image_pad|>", + "<|video_pad|>" + ], + "bos_token": null, + "chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0]['role'] == 'system' %}\n {{- messages[0]['content'] }}\n {%- else %}\n {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}\n {%- endif %}\n {{- \"\\n\\n# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within XML tags:\\n\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\n\\n\\nFor each function call, return a json object with function name and arguments within XML tags:\\n\\n{\\\"name\\\": , \\\"arguments\\\": }\\n<|im_end|>\\n\" }}\n{%- else %}\n {%- if messages[0]['role'] == 'system' %}\n {{- '<|im_start|>system\\n' + messages[0]['content'] + '<|im_end|>\\n' }}\n {%- else %}\n {{- '<|im_start|>system\\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {{- '<|im_start|>' + message.role }}\n {%- if message.content %}\n {{- '\\n' + message.content }}\n {%- endif %}\n {%- for tool_call in message.tool_calls %}\n {%- if tool_call.function is defined %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {{- '\\n\\n{\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\", \"arguments\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- '}\\n' }}\n {%- endfor %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n\\n' }}\n {{- message.content }}\n {{- '\\n' }}\n {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n", + "clean_up_tokenization_spaces": false, + "eos_token": "<|endoftext|>", + "errors": "replace", + "model_max_length": 131072, + "pad_token": "<|endoftext|>", + "padding_side": "right", + "split_special_tokens": false, + "tokenizer_class": "Qwen2Tokenizer", + "unk_token": null +} diff --git a/train_results.json b/train_results.json new file mode 100644 index 0000000..1b79375 --- /dev/null +++ b/train_results.json @@ -0,0 +1,8 @@ +{ + "epoch": 12.30379746835443, + "total_flos": 4.902218749915955e+16, + "train_loss": 0.26980868625080484, + "train_runtime": 2812.7387, + "train_samples_per_second": 1.46, + "train_steps_per_second": 0.042 +} \ No newline at end of file diff --git a/trainer_log.jsonl b/trainer_log.jsonl new file mode 100644 index 0000000..5fcfa98 --- /dev/null +++ b/trainer_log.jsonl @@ -0,0 +1,118 @@ +{"current_steps": 1, "total_steps": 117, "loss": 0.9281, "lr": 8.333333333333333e-07, "epoch": 0.10126582278481013, "percentage": 0.85, "elapsed_time": "0:00:19", "remaining_time": "0:37:25"} +{"current_steps": 2, "total_steps": 117, "loss": 0.9108, "lr": 1.6666666666666667e-06, "epoch": 0.20253164556962025, "percentage": 1.71, "elapsed_time": "0:00:41", "remaining_time": "0:39:35"} +{"current_steps": 3, "total_steps": 117, "loss": 0.8874, "lr": 2.5e-06, "epoch": 0.3037974683544304, "percentage": 2.56, "elapsed_time": "0:00:57", "remaining_time": "0:36:39"} +{"current_steps": 4, "total_steps": 117, "loss": 0.9102, "lr": 3.3333333333333333e-06, "epoch": 0.4050632911392405, "percentage": 3.42, "elapsed_time": "0:01:16", "remaining_time": "0:35:51"} +{"current_steps": 5, "total_steps": 117, "loss": 0.8248, "lr": 4.166666666666667e-06, "epoch": 0.5063291139240507, "percentage": 4.27, "elapsed_time": "0:01:31", "remaining_time": "0:34:07"} +{"current_steps": 6, "total_steps": 117, "loss": 0.8383, "lr": 5e-06, "epoch": 0.6075949367088608, "percentage": 5.13, "elapsed_time": "0:01:50", "remaining_time": "0:34:07"} +{"current_steps": 7, "total_steps": 117, "loss": 0.7354, "lr": 5.833333333333334e-06, "epoch": 0.7088607594936709, "percentage": 5.98, "elapsed_time": "0:02:08", "remaining_time": "0:33:44"} +{"current_steps": 8, "total_steps": 117, "loss": 0.7928, "lr": 6.666666666666667e-06, "epoch": 0.810126582278481, "percentage": 6.84, "elapsed_time": "0:02:26", "remaining_time": "0:33:11"} +{"current_steps": 9, "total_steps": 117, "loss": 0.7744, "lr": 7.500000000000001e-06, "epoch": 0.9113924050632911, "percentage": 7.69, "elapsed_time": "0:02:37", "remaining_time": "0:31:35"} +{"current_steps": 10, "total_steps": 117, "loss": 0.7524, "lr": 8.333333333333334e-06, "epoch": 1.0506329113924051, "percentage": 8.55, "elapsed_time": "0:03:43", "remaining_time": "0:39:46"} +{"current_steps": 11, "total_steps": 117, "loss": 0.6639, "lr": 9.166666666666666e-06, "epoch": 1.1518987341772151, "percentage": 9.4, "elapsed_time": "0:03:55", "remaining_time": "0:37:47"} +{"current_steps": 12, "total_steps": 117, "loss": 0.6936, "lr": 1e-05, "epoch": 1.2531645569620253, "percentage": 10.26, "elapsed_time": "0:04:11", "remaining_time": "0:36:40"} +{"current_steps": 13, "total_steps": 117, "loss": 0.6682, "lr": 9.997762161417517e-06, "epoch": 1.3544303797468356, "percentage": 11.11, "elapsed_time": "0:04:39", "remaining_time": "0:37:13"} +{"current_steps": 14, "total_steps": 117, "loss": 0.5577, "lr": 9.991050648838676e-06, "epoch": 1.4556962025316456, "percentage": 11.97, "elapsed_time": "0:04:55", "remaining_time": "0:36:13"} +{"current_steps": 15, "total_steps": 117, "loss": 0.5829, "lr": 9.979871469976197e-06, "epoch": 1.5569620253164556, "percentage": 12.82, "elapsed_time": "0:05:16", "remaining_time": "0:35:53"} +{"current_steps": 16, "total_steps": 117, "loss": 0.6041, "lr": 9.964234631709188e-06, "epoch": 1.6582278481012658, "percentage": 13.68, "elapsed_time": "0:05:33", "remaining_time": "0:35:05"} +{"current_steps": 17, "total_steps": 117, "loss": 0.6291, "lr": 9.944154131125643e-06, "epoch": 1.759493670886076, "percentage": 14.53, "elapsed_time": "0:05:47", "remaining_time": "0:34:05"} +{"current_steps": 18, "total_steps": 117, "loss": 0.6081, "lr": 9.91964794299315e-06, "epoch": 1.8607594936708862, "percentage": 15.38, "elapsed_time": "0:06:02", "remaining_time": "0:33:16"} +{"current_steps": 19, "total_steps": 117, "loss": 0.5927, "lr": 9.890738003669029e-06, "epoch": 1.9620253164556962, "percentage": 16.24, "elapsed_time": "0:06:24", "remaining_time": "0:33:01"} +{"current_steps": 20, "total_steps": 117, "loss": 0.5682, "lr": 9.857450191464337e-06, "epoch": 2.1012658227848102, "percentage": 17.09, "elapsed_time": "0:07:18", "remaining_time": "0:35:26"} +{"current_steps": 21, "total_steps": 117, "loss": 0.5403, "lr": 9.819814303479268e-06, "epoch": 2.2025316455696204, "percentage": 17.95, "elapsed_time": "0:07:33", "remaining_time": "0:34:32"} +{"current_steps": 22, "total_steps": 117, "loss": 0.4855, "lr": 9.777864028930705e-06, "epoch": 2.3037974683544302, "percentage": 18.8, "elapsed_time": "0:07:48", "remaining_time": "0:33:42"} +{"current_steps": 23, "total_steps": 117, "loss": 0.5031, "lr": 9.731636918995821e-06, "epoch": 2.4050632911392404, "percentage": 19.66, "elapsed_time": "0:08:07", "remaining_time": "0:33:13"} +{"current_steps": 24, "total_steps": 117, "loss": 0.4571, "lr": 9.681174353198687e-06, "epoch": 2.5063291139240507, "percentage": 20.51, "elapsed_time": "0:08:25", "remaining_time": "0:32:37"} +{"current_steps": 25, "total_steps": 117, "loss": 0.4672, "lr": 9.626521502369984e-06, "epoch": 2.607594936708861, "percentage": 21.37, "elapsed_time": "0:08:37", "remaining_time": "0:31:45"} +{"current_steps": 26, "total_steps": 117, "loss": 0.4384, "lr": 9.567727288213005e-06, "epoch": 2.708860759493671, "percentage": 22.22, "elapsed_time": "0:08:57", "remaining_time": "0:31:22"} +{"current_steps": 27, "total_steps": 117, "loss": 0.3985, "lr": 9.504844339512096e-06, "epoch": 2.810126582278481, "percentage": 23.08, "elapsed_time": "0:09:18", "remaining_time": "0:31:00"} +{"current_steps": 28, "total_steps": 117, "loss": 0.4792, "lr": 9.437928945022772e-06, "epoch": 2.911392405063291, "percentage": 23.93, "elapsed_time": "0:09:38", "remaining_time": "0:30:38"} +{"current_steps": 29, "total_steps": 117, "loss": 0.362, "lr": 9.36704100308565e-06, "epoch": 3.050632911392405, "percentage": 24.79, "elapsed_time": "0:10:49", "remaining_time": "0:32:50"} +{"current_steps": 30, "total_steps": 117, "loss": 0.3723, "lr": 9.292243968009332e-06, "epoch": 3.151898734177215, "percentage": 25.64, "elapsed_time": "0:11:09", "remaining_time": "0:32:22"} +{"current_steps": 31, "total_steps": 117, "loss": 0.3369, "lr": 9.213604793270196e-06, "epoch": 3.2531645569620253, "percentage": 26.5, "elapsed_time": "0:11:31", "remaining_time": "0:31:57"} +{"current_steps": 32, "total_steps": 117, "loss": 0.3604, "lr": 9.131193871579975e-06, "epoch": 3.3544303797468356, "percentage": 27.35, "elapsed_time": "0:11:54", "remaining_time": "0:31:37"} +{"current_steps": 33, "total_steps": 117, "loss": 0.3631, "lr": 9.045084971874738e-06, "epoch": 3.4556962025316453, "percentage": 28.21, "elapsed_time": "0:12:12", "remaining_time": "0:31:04"} +{"current_steps": 34, "total_steps": 117, "loss": 0.3553, "lr": 8.955355173281709e-06, "epoch": 3.5569620253164556, "percentage": 29.06, "elapsed_time": "0:12:28", "remaining_time": "0:30:28"} +{"current_steps": 35, "total_steps": 117, "loss": 0.4085, "lr": 8.862084796122998e-06, "epoch": 3.6582278481012658, "percentage": 29.91, "elapsed_time": "0:12:47", "remaining_time": "0:29:58"} +{"current_steps": 36, "total_steps": 117, "loss": 0.2889, "lr": 8.765357330018056e-06, "epoch": 3.759493670886076, "percentage": 30.77, "elapsed_time": "0:13:03", "remaining_time": "0:29:23"} +{"current_steps": 37, "total_steps": 117, "loss": 0.2859, "lr": 8.665259359149132e-06, "epoch": 3.8607594936708862, "percentage": 31.62, "elapsed_time": "0:13:15", "remaining_time": "0:28:39"} +{"current_steps": 38, "total_steps": 117, "loss": 0.36, "lr": 8.561880484756726e-06, "epoch": 3.962025316455696, "percentage": 32.48, "elapsed_time": "0:13:29", "remaining_time": "0:28:02"} +{"current_steps": 39, "total_steps": 117, "loss": 0.284, "lr": 8.455313244934324e-06, "epoch": 4.10126582278481, "percentage": 33.33, "elapsed_time": "0:14:41", "remaining_time": "0:29:23"} +{"current_steps": 40, "total_steps": 117, "loss": 0.2657, "lr": 8.345653031794292e-06, "epoch": 4.2025316455696204, "percentage": 34.19, "elapsed_time": "0:14:58", "remaining_time": "0:28:49"} +{"current_steps": 41, "total_steps": 117, "loss": 0.2237, "lr": 8.232998006078998e-06, "epoch": 4.30379746835443, "percentage": 35.04, "elapsed_time": "0:15:11", "remaining_time": "0:28:10"} +{"current_steps": 42, "total_steps": 117, "loss": 0.2345, "lr": 8.117449009293668e-06, "epoch": 4.405063291139241, "percentage": 35.9, "elapsed_time": "0:15:26", "remaining_time": "0:27:34"} +{"current_steps": 43, "total_steps": 117, "loss": 0.2498, "lr": 7.99910947343957e-06, "epoch": 4.506329113924051, "percentage": 36.75, "elapsed_time": "0:15:42", "remaining_time": "0:27:01"} +{"current_steps": 44, "total_steps": 117, "loss": 0.2405, "lr": 7.87808532842837e-06, "epoch": 4.6075949367088604, "percentage": 37.61, "elapsed_time": "0:15:56", "remaining_time": "0:26:26"} +{"current_steps": 45, "total_steps": 117, "loss": 0.2913, "lr": 7.754484907260513e-06, "epoch": 4.708860759493671, "percentage": 38.46, "elapsed_time": "0:16:19", "remaining_time": "0:26:07"} +{"current_steps": 46, "total_steps": 117, "loss": 0.286, "lr": 7.628418849052523e-06, "epoch": 4.810126582278481, "percentage": 39.32, "elapsed_time": "0:16:38", "remaining_time": "0:25:41"} +{"current_steps": 47, "total_steps": 117, "loss": 0.2364, "lr": 7.500000000000001e-06, "epoch": 4.911392405063291, "percentage": 40.17, "elapsed_time": "0:16:59", "remaining_time": "0:25:18"} +{"current_steps": 48, "total_steps": 117, "loss": 0.2076, "lr": 7.369343312364994e-06, "epoch": 5.050632911392405, "percentage": 41.03, "elapsed_time": "0:18:13", "remaining_time": "0:26:11"} +{"current_steps": 49, "total_steps": 117, "loss": 0.1667, "lr": 7.236565741578163e-06, "epoch": 5.151898734177215, "percentage": 41.88, "elapsed_time": "0:18:34", "remaining_time": "0:25:46"} +{"current_steps": 50, "total_steps": 117, "loss": 0.1684, "lr": 7.101786141547829e-06, "epoch": 5.253164556962025, "percentage": 42.74, "elapsed_time": "0:18:51", "remaining_time": "0:25:16"} +{"current_steps": 51, "total_steps": 117, "loss": 0.2039, "lr": 6.965125158269619e-06, "epoch": 5.3544303797468356, "percentage": 43.59, "elapsed_time": "0:19:10", "remaining_time": "0:24:48"} +{"current_steps": 52, "total_steps": 117, "loss": 0.1794, "lr": 6.8267051218319766e-06, "epoch": 5.455696202531645, "percentage": 44.44, "elapsed_time": "0:19:24", "remaining_time": "0:24:16"} +{"current_steps": 53, "total_steps": 117, "loss": 0.1529, "lr": 6.686649936914151e-06, "epoch": 5.556962025316456, "percentage": 45.3, "elapsed_time": "0:19:35", "remaining_time": "0:23:39"} +{"current_steps": 54, "total_steps": 117, "loss": 0.1956, "lr": 6.545084971874738e-06, "epoch": 5.658227848101266, "percentage": 46.15, "elapsed_time": "0:19:55", "remaining_time": "0:23:15"} +{"current_steps": 55, "total_steps": 117, "loss": 0.1958, "lr": 6.402136946530014e-06, "epoch": 5.759493670886076, "percentage": 47.01, "elapsed_time": "0:20:14", "remaining_time": "0:22:48"} +{"current_steps": 56, "total_steps": 117, "loss": 0.217, "lr": 6.257933818722544e-06, "epoch": 5.860759493670886, "percentage": 47.86, "elapsed_time": "0:20:35", "remaining_time": "0:22:26"} +{"current_steps": 57, "total_steps": 117, "loss": 0.1946, "lr": 6.112604669781572e-06, "epoch": 5.962025316455696, "percentage": 48.72, "elapsed_time": "0:20:58", "remaining_time": "0:22:04"} +{"current_steps": 58, "total_steps": 117, "loss": 0.1701, "lr": 5.9662795889777666e-06, "epoch": 6.10126582278481, "percentage": 49.57, "elapsed_time": "0:22:14", "remaining_time": "0:22:37"} +{"current_steps": 59, "total_steps": 117, "loss": 0.1426, "lr": 5.819089557075689e-06, "epoch": 6.2025316455696204, "percentage": 50.43, "elapsed_time": "0:22:30", "remaining_time": "0:22:07"} +{"current_steps": 60, "total_steps": 117, "loss": 0.1184, "lr": 5.671166329088278e-06, "epoch": 6.30379746835443, "percentage": 51.28, "elapsed_time": "0:22:42", "remaining_time": "0:21:34"} +{"current_steps": 61, "total_steps": 117, "loss": 0.1978, "lr": 5.522642316338268e-06, "epoch": 6.405063291139241, "percentage": 52.14, "elapsed_time": "0:22:58", "remaining_time": "0:21:05"} +{"current_steps": 62, "total_steps": 117, "loss": 0.1521, "lr": 5.373650467932122e-06, "epoch": 6.506329113924051, "percentage": 52.99, "elapsed_time": "0:23:14", "remaining_time": "0:20:36"} +{"current_steps": 63, "total_steps": 117, "loss": 0.1556, "lr": 5.224324151752575e-06, "epoch": 6.6075949367088604, "percentage": 53.85, "elapsed_time": "0:23:34", "remaining_time": "0:20:12"} +{"current_steps": 64, "total_steps": 117, "loss": 0.1134, "lr": 5.074797035076319e-06, "epoch": 6.708860759493671, "percentage": 54.7, "elapsed_time": "0:23:47", "remaining_time": "0:19:42"} +{"current_steps": 65, "total_steps": 117, "loss": 0.1085, "lr": 4.9252029649236835e-06, "epoch": 6.810126582278481, "percentage": 55.56, "elapsed_time": "0:23:58", "remaining_time": "0:19:10"} +{"current_steps": 66, "total_steps": 117, "loss": 0.1296, "lr": 4.775675848247427e-06, "epoch": 6.911392405063291, "percentage": 56.41, "elapsed_time": "0:24:13", "remaining_time": "0:18:42"} +{"current_steps": 67, "total_steps": 117, "loss": 0.1223, "lr": 4.626349532067879e-06, "epoch": 7.050632911392405, "percentage": 57.26, "elapsed_time": "0:25:26", "remaining_time": "0:18:59"} +{"current_steps": 68, "total_steps": 117, "loss": 0.0976, "lr": 4.477357683661734e-06, "epoch": 7.151898734177215, "percentage": 58.12, "elapsed_time": "0:25:41", "remaining_time": "0:18:30"} +{"current_steps": 69, "total_steps": 117, "loss": 0.1576, "lr": 4.3288336709117246e-06, "epoch": 7.253164556962025, "percentage": 58.97, "elapsed_time": "0:26:02", "remaining_time": "0:18:06"} +{"current_steps": 70, "total_steps": 117, "loss": 0.1002, "lr": 4.180910442924312e-06, "epoch": 7.3544303797468356, "percentage": 59.83, "elapsed_time": "0:26:17", "remaining_time": "0:17:39"} +{"current_steps": 71, "total_steps": 117, "loss": 0.0634, "lr": 4.033720411022235e-06, "epoch": 7.455696202531645, "percentage": 60.68, "elapsed_time": "0:26:28", "remaining_time": "0:17:09"} +{"current_steps": 72, "total_steps": 117, "loss": 0.1324, "lr": 3.887395330218429e-06, "epoch": 7.556962025316456, "percentage": 61.54, "elapsed_time": "0:26:50", "remaining_time": "0:16:46"} +{"current_steps": 73, "total_steps": 117, "loss": 0.0783, "lr": 3.7420661812774577e-06, "epoch": 7.658227848101266, "percentage": 62.39, "elapsed_time": "0:27:05", "remaining_time": "0:16:19"} +{"current_steps": 74, "total_steps": 117, "loss": 0.1258, "lr": 3.5978630534699873e-06, "epoch": 7.759493670886076, "percentage": 63.25, "elapsed_time": "0:27:28", "remaining_time": "0:15:58"} +{"current_steps": 75, "total_steps": 117, "loss": 0.1357, "lr": 3.4549150281252635e-06, "epoch": 7.860759493670886, "percentage": 64.1, "elapsed_time": "0:27:47", "remaining_time": "0:15:33"} +{"current_steps": 76, "total_steps": 117, "loss": 0.1221, "lr": 3.3133500630858507e-06, "epoch": 7.962025316455696, "percentage": 64.96, "elapsed_time": "0:28:02", "remaining_time": "0:15:07"} +{"current_steps": 77, "total_steps": 117, "loss": 0.0895, "lr": 3.173294878168025e-06, "epoch": 8.10126582278481, "percentage": 65.81, "elapsed_time": "0:29:27", "remaining_time": "0:15:18"} +{"current_steps": 78, "total_steps": 117, "loss": 0.1119, "lr": 3.0348748417303826e-06, "epoch": 8.20253164556962, "percentage": 66.67, "elapsed_time": "0:29:47", "remaining_time": "0:14:53"} +{"current_steps": 79, "total_steps": 117, "loss": 0.0546, "lr": 2.8982138584521734e-06, "epoch": 8.30379746835443, "percentage": 67.52, "elapsed_time": "0:29:58", "remaining_time": "0:14:25"} +{"current_steps": 80, "total_steps": 117, "loss": 0.0701, "lr": 2.7634342584218364e-06, "epoch": 8.405063291139241, "percentage": 68.38, "elapsed_time": "0:30:15", "remaining_time": "0:13:59"} +{"current_steps": 81, "total_steps": 117, "loss": 0.088, "lr": 2.6306566876350072e-06, "epoch": 8.50632911392405, "percentage": 69.23, "elapsed_time": "0:30:32", "remaining_time": "0:13:34"} +{"current_steps": 82, "total_steps": 117, "loss": 0.0989, "lr": 2.5000000000000015e-06, "epoch": 8.60759493670886, "percentage": 70.09, "elapsed_time": "0:30:51", "remaining_time": "0:13:10"} +{"current_steps": 83, "total_steps": 117, "loss": 0.1138, "lr": 2.371581150947476e-06, "epoch": 8.708860759493671, "percentage": 70.94, "elapsed_time": "0:31:11", "remaining_time": "0:12:46"} +{"current_steps": 84, "total_steps": 117, "loss": 0.0778, "lr": 2.245515092739488e-06, "epoch": 8.810126582278482, "percentage": 71.79, "elapsed_time": "0:31:26", "remaining_time": "0:12:21"} +{"current_steps": 85, "total_steps": 117, "loss": 0.1197, "lr": 2.1219146715716332e-06, "epoch": 8.91139240506329, "percentage": 72.65, "elapsed_time": "0:31:44", "remaining_time": "0:11:57"} +{"current_steps": 86, "total_steps": 117, "loss": 0.0645, "lr": 2.0008905265604316e-06, "epoch": 9.050632911392405, "percentage": 73.5, "elapsed_time": "0:32:52", "remaining_time": "0:11:50"} +{"current_steps": 87, "total_steps": 117, "loss": 0.0707, "lr": 1.8825509907063328e-06, "epoch": 9.151898734177216, "percentage": 74.36, "elapsed_time": "0:33:08", "remaining_time": "0:11:25"} +{"current_steps": 88, "total_steps": 117, "loss": 0.0592, "lr": 1.7670019939210025e-06, "epoch": 9.253164556962025, "percentage": 75.21, "elapsed_time": "0:33:22", "remaining_time": "0:10:59"} +{"current_steps": 89, "total_steps": 117, "loss": 0.107, "lr": 1.6543469682057105e-06, "epoch": 9.354430379746836, "percentage": 76.07, "elapsed_time": "0:33:41", "remaining_time": "0:10:36"} +{"current_steps": 90, "total_steps": 117, "loss": 0.0515, "lr": 1.544686755065677e-06, "epoch": 9.455696202531646, "percentage": 76.92, "elapsed_time": "0:33:55", "remaining_time": "0:10:10"} +{"current_steps": 91, "total_steps": 117, "loss": 0.1044, "lr": 1.438119515243277e-06, "epoch": 9.556962025316455, "percentage": 77.78, "elapsed_time": "0:34:20", "remaining_time": "0:09:48"} +{"current_steps": 92, "total_steps": 117, "loss": 0.0741, "lr": 1.3347406408508695e-06, "epoch": 9.658227848101266, "percentage": 78.63, "elapsed_time": "0:34:37", "remaining_time": "0:09:24"} +{"current_steps": 93, "total_steps": 117, "loss": 0.1096, "lr": 1.234642669981946e-06, "epoch": 9.759493670886076, "percentage": 79.49, "elapsed_time": "0:34:56", "remaining_time": "0:09:00"} +{"current_steps": 94, "total_steps": 117, "loss": 0.0738, "lr": 1.137915203877003e-06, "epoch": 9.860759493670885, "percentage": 80.34, "elapsed_time": "0:35:11", "remaining_time": "0:08:36"} +{"current_steps": 95, "total_steps": 117, "loss": 0.0798, "lr": 1.044644826718295e-06, "epoch": 9.962025316455696, "percentage": 81.2, "elapsed_time": "0:35:34", "remaining_time": "0:08:14"} +{"current_steps": 96, "total_steps": 117, "loss": 0.0772, "lr": 9.549150281252633e-07, "epoch": 10.10126582278481, "percentage": 82.05, "elapsed_time": "0:36:54", "remaining_time": "0:08:04"} +{"current_steps": 97, "total_steps": 117, "loss": 0.0706, "lr": 8.688061284200266e-07, "epoch": 10.20253164556962, "percentage": 82.91, "elapsed_time": "0:37:09", "remaining_time": "0:07:39"} +{"current_steps": 98, "total_steps": 117, "loss": 0.0854, "lr": 7.863952067298042e-07, "epoch": 10.30379746835443, "percentage": 83.76, "elapsed_time": "0:37:33", "remaining_time": "0:07:16"} +{"current_steps": 99, "total_steps": 117, "loss": 0.0463, "lr": 7.077560319906696e-07, "epoch": 10.405063291139241, "percentage": 84.62, "elapsed_time": "0:37:46", "remaining_time": "0:06:52"} +{"current_steps": 100, "total_steps": 117, "loss": 0.0642, "lr": 6.329589969143518e-07, "epoch": 10.50632911392405, "percentage": 85.47, "elapsed_time": "0:37:58", "remaining_time": "0:06:27"} +{"current_steps": 101, "total_steps": 117, "loss": 0.0462, "lr": 5.620710549772295e-07, "epoch": 10.60759493670886, "percentage": 86.32, "elapsed_time": "0:38:13", "remaining_time": "0:06:03"} +{"current_steps": 102, "total_steps": 117, "loss": 0.1179, "lr": 4.951556604879049e-07, "epoch": 10.708860759493671, "percentage": 87.18, "elapsed_time": "0:38:36", "remaining_time": "0:05:40"} +{"current_steps": 103, "total_steps": 117, "loss": 0.0675, "lr": 4.322727117869951e-07, "epoch": 10.810126582278482, "percentage": 88.03, "elapsed_time": "0:38:53", "remaining_time": "0:05:17"} +{"current_steps": 104, "total_steps": 117, "loss": 0.0693, "lr": 3.734784976300165e-07, "epoch": 10.91139240506329, "percentage": 88.89, "elapsed_time": "0:39:12", "remaining_time": "0:04:54"} +{"current_steps": 105, "total_steps": 117, "loss": 0.0957, "lr": 3.18825646801314e-07, "epoch": 11.050632911392405, "percentage": 89.74, "elapsed_time": "0:40:35", "remaining_time": "0:04:38"} +{"current_steps": 106, "total_steps": 117, "loss": 0.041, "lr": 2.6836308100417874e-07, "epoch": 11.151898734177216, "percentage": 90.6, "elapsed_time": "0:40:49", "remaining_time": "0:04:14"} +{"current_steps": 107, "total_steps": 117, "loss": 0.0564, "lr": 2.2213597106929608e-07, "epoch": 11.253164556962025, "percentage": 91.45, "elapsed_time": "0:41:02", "remaining_time": "0:03:50"} +{"current_steps": 108, "total_steps": 117, "loss": 0.0804, "lr": 1.801856965207338e-07, "epoch": 11.354430379746836, "percentage": 92.31, "elapsed_time": "0:41:18", "remaining_time": "0:03:26"} +{"current_steps": 109, "total_steps": 117, "loss": 0.041, "lr": 1.4254980853566248e-07, "epoch": 11.455696202531646, "percentage": 93.16, "elapsed_time": "0:41:33", "remaining_time": "0:03:03"} +{"current_steps": 110, "total_steps": 117, "loss": 0.0903, "lr": 1.0926199633097156e-07, "epoch": 11.556962025316455, "percentage": 94.02, "elapsed_time": "0:41:52", "remaining_time": "0:02:39"} +{"current_steps": 111, "total_steps": 117, "loss": 0.0721, "lr": 8.035205700685167e-08, "epoch": 11.658227848101266, "percentage": 94.87, "elapsed_time": "0:42:09", "remaining_time": "0:02:16"} +{"current_steps": 112, "total_steps": 117, "loss": 0.0657, "lr": 5.584586887435739e-08, "epoch": 11.759493670886076, "percentage": 95.73, "elapsed_time": "0:42:30", "remaining_time": "0:01:53"} +{"current_steps": 113, "total_steps": 117, "loss": 0.078, "lr": 3.576536829081323e-08, "epoch": 11.860759493670885, "percentage": 96.58, "elapsed_time": "0:42:48", "remaining_time": "0:01:30"} +{"current_steps": 114, "total_steps": 117, "loss": 0.0652, "lr": 2.012853002380466e-08, "epoch": 11.962025316455696, "percentage": 97.44, "elapsed_time": "0:43:05", "remaining_time": "0:01:08"} +{"current_steps": 115, "total_steps": 117, "loss": 0.0842, "lr": 8.949351161324227e-09, "epoch": 12.10126582278481, "percentage": 98.29, "elapsed_time": "0:44:14", "remaining_time": "0:00:46"} +{"current_steps": 116, "total_steps": 117, "loss": 0.0994, "lr": 2.237838582483387e-09, "epoch": 12.20253164556962, "percentage": 99.15, "elapsed_time": "0:44:41", "remaining_time": "0:00:23"} +{"current_steps": 117, "total_steps": 117, "loss": 0.0314, "lr": 0.0, "epoch": 12.30379746835443, "percentage": 100.0, "elapsed_time": "0:44:56", "remaining_time": "0:00:00"} +{"current_steps": 117, "total_steps": 117, "epoch": 12.30379746835443, "percentage": 100.0, "elapsed_time": "0:46:50", "remaining_time": "0:00:00"} diff --git a/trainer_state.json b/trainer_state.json new file mode 100644 index 0000000..f721c72 --- /dev/null +++ b/trainer_state.json @@ -0,0 +1,861 @@ +{ + "best_metric": null, + "best_model_checkpoint": null, + "epoch": 12.30379746835443, + "eval_steps": 500, + "global_step": 117, + "is_hyper_param_search": false, + "is_local_process_zero": true, + "is_world_process_zero": true, + "log_history": [ + { + "epoch": 0.10126582278481013, + "grad_norm": 6.43825208149568, + "learning_rate": 8.333333333333333e-07, + "loss": 0.9281, + "step": 1 + }, + { + "epoch": 0.20253164556962025, + "grad_norm": 6.559153069315341, + "learning_rate": 1.6666666666666667e-06, + "loss": 0.9108, + "step": 2 + }, + { + "epoch": 0.3037974683544304, + "grad_norm": 7.045196702684219, + "learning_rate": 2.5e-06, + "loss": 0.8874, + "step": 3 + }, + { + "epoch": 0.4050632911392405, + "grad_norm": 6.450857710098491, + "learning_rate": 3.3333333333333333e-06, + "loss": 0.9102, + "step": 4 + }, + { + "epoch": 0.5063291139240507, + "grad_norm": 5.274518665853932, + "learning_rate": 4.166666666666667e-06, + "loss": 0.8248, + "step": 5 + }, + { + "epoch": 0.6075949367088608, + "grad_norm": 3.2648170762097477, + "learning_rate": 5e-06, + "loss": 0.8383, + "step": 6 + }, + { + "epoch": 0.7088607594936709, + "grad_norm": 2.5880252500398844, + "learning_rate": 5.833333333333334e-06, + "loss": 0.7354, + "step": 7 + }, + { + "epoch": 0.810126582278481, + "grad_norm": 3.845109483810076, + "learning_rate": 6.666666666666667e-06, + "loss": 0.7928, + "step": 8 + }, + { + "epoch": 0.9113924050632911, + "grad_norm": 4.109400755644465, + "learning_rate": 7.500000000000001e-06, + "loss": 0.7744, + "step": 9 + }, + { + "epoch": 1.0506329113924051, + "grad_norm": 4.311702547596846, + "learning_rate": 8.333333333333334e-06, + "loss": 0.7524, + "step": 10 + }, + { + "epoch": 1.1518987341772151, + "grad_norm": 3.822432777947372, + "learning_rate": 9.166666666666666e-06, + "loss": 0.6639, + "step": 11 + }, + { + "epoch": 1.2531645569620253, + "grad_norm": 3.5468998915875813, + "learning_rate": 1e-05, + "loss": 0.6936, + "step": 12 + }, + { + "epoch": 1.3544303797468356, + "grad_norm": 2.800787770940674, + "learning_rate": 9.997762161417517e-06, + "loss": 0.6682, + "step": 13 + }, + { + "epoch": 1.4556962025316456, + "grad_norm": 2.1669190884101175, + "learning_rate": 9.991050648838676e-06, + "loss": 0.5577, + "step": 14 + }, + { + "epoch": 1.5569620253164556, + "grad_norm": 2.087992110618876, + "learning_rate": 9.979871469976197e-06, + "loss": 0.5829, + "step": 15 + }, + { + "epoch": 1.6582278481012658, + "grad_norm": 2.7059991544282798, + "learning_rate": 9.964234631709188e-06, + "loss": 0.6041, + "step": 16 + }, + { + "epoch": 1.759493670886076, + "grad_norm": 2.2940983342523125, + "learning_rate": 9.944154131125643e-06, + "loss": 0.6291, + "step": 17 + }, + { + "epoch": 1.8607594936708862, + "grad_norm": 1.6808408200948324, + "learning_rate": 9.91964794299315e-06, + "loss": 0.6081, + "step": 18 + }, + { + "epoch": 1.9620253164556962, + "grad_norm": 1.6600609215129083, + "learning_rate": 9.890738003669029e-06, + "loss": 0.5927, + "step": 19 + }, + { + "epoch": 2.1012658227848102, + "grad_norm": 1.472819671631874, + "learning_rate": 9.857450191464337e-06, + "loss": 0.5682, + "step": 20 + }, + { + "epoch": 2.2025316455696204, + "grad_norm": 1.6799800601492856, + "learning_rate": 9.819814303479268e-06, + "loss": 0.5403, + "step": 21 + }, + { + "epoch": 2.3037974683544302, + "grad_norm": 1.3804440688611062, + "learning_rate": 9.777864028930705e-06, + "loss": 0.4855, + "step": 22 + }, + { + "epoch": 2.4050632911392404, + "grad_norm": 1.1432325373879264, + "learning_rate": 9.731636918995821e-06, + "loss": 0.5031, + "step": 23 + }, + { + "epoch": 2.5063291139240507, + "grad_norm": 0.9092916002520707, + "learning_rate": 9.681174353198687e-06, + "loss": 0.4571, + "step": 24 + }, + { + "epoch": 2.607594936708861, + "grad_norm": 1.1253148386623655, + "learning_rate": 9.626521502369984e-06, + "loss": 0.4672, + "step": 25 + }, + { + "epoch": 2.708860759493671, + "grad_norm": 1.4032465429020564, + "learning_rate": 9.567727288213005e-06, + "loss": 0.4384, + "step": 26 + }, + { + "epoch": 2.810126582278481, + "grad_norm": 1.1988699935589895, + "learning_rate": 9.504844339512096e-06, + "loss": 0.3985, + "step": 27 + }, + { + "epoch": 2.911392405063291, + "grad_norm": 0.8951456999785163, + "learning_rate": 9.437928945022772e-06, + "loss": 0.4792, + "step": 28 + }, + { + "epoch": 3.050632911392405, + "grad_norm": 0.9624502825360387, + "learning_rate": 9.36704100308565e-06, + "loss": 0.362, + "step": 29 + }, + { + "epoch": 3.151898734177215, + "grad_norm": 1.0438288012802868, + "learning_rate": 9.292243968009332e-06, + "loss": 0.3723, + "step": 30 + }, + { + "epoch": 3.2531645569620253, + "grad_norm": 0.9703176540776492, + "learning_rate": 9.213604793270196e-06, + "loss": 0.3369, + "step": 31 + }, + { + "epoch": 3.3544303797468356, + "grad_norm": 0.893163662422422, + "learning_rate": 9.131193871579975e-06, + "loss": 0.3604, + "step": 32 + }, + { + "epoch": 3.4556962025316453, + "grad_norm": 1.2422079407990139, + "learning_rate": 9.045084971874738e-06, + "loss": 0.3631, + "step": 33 + }, + { + "epoch": 3.5569620253164556, + "grad_norm": 0.9151822546049537, + "learning_rate": 8.955355173281709e-06, + "loss": 0.3553, + "step": 34 + }, + { + "epoch": 3.6582278481012658, + "grad_norm": 1.0114454402313395, + "learning_rate": 8.862084796122998e-06, + "loss": 0.4085, + "step": 35 + }, + { + "epoch": 3.759493670886076, + "grad_norm": 0.9443337928269486, + "learning_rate": 8.765357330018056e-06, + "loss": 0.2889, + "step": 36 + }, + { + "epoch": 3.8607594936708862, + "grad_norm": 0.865644384923322, + "learning_rate": 8.665259359149132e-06, + "loss": 0.2859, + "step": 37 + }, + { + "epoch": 3.962025316455696, + "grad_norm": 0.8599590553282734, + "learning_rate": 8.561880484756726e-06, + "loss": 0.36, + "step": 38 + }, + { + "epoch": 4.10126582278481, + "grad_norm": 0.8238766304670959, + "learning_rate": 8.455313244934324e-06, + "loss": 0.284, + "step": 39 + }, + { + "epoch": 4.2025316455696204, + "grad_norm": 0.8904225393629464, + "learning_rate": 8.345653031794292e-06, + "loss": 0.2657, + "step": 40 + }, + { + "epoch": 4.30379746835443, + "grad_norm": 0.8281971083836545, + "learning_rate": 8.232998006078998e-06, + "loss": 0.2237, + "step": 41 + }, + { + "epoch": 4.405063291139241, + "grad_norm": 0.9318352078173276, + "learning_rate": 8.117449009293668e-06, + "loss": 0.2345, + "step": 42 + }, + { + "epoch": 4.506329113924051, + "grad_norm": 0.9593192555567228, + "learning_rate": 7.99910947343957e-06, + "loss": 0.2498, + "step": 43 + }, + { + "epoch": 4.6075949367088604, + "grad_norm": 0.8527439601562876, + "learning_rate": 7.87808532842837e-06, + "loss": 0.2405, + "step": 44 + }, + { + "epoch": 4.708860759493671, + "grad_norm": 0.9473177017919994, + "learning_rate": 7.754484907260513e-06, + "loss": 0.2913, + "step": 45 + }, + { + "epoch": 4.810126582278481, + "grad_norm": 0.8102313751416961, + "learning_rate": 7.628418849052523e-06, + "loss": 0.286, + "step": 46 + }, + { + "epoch": 4.911392405063291, + "grad_norm": 0.820114624158469, + "learning_rate": 7.500000000000001e-06, + "loss": 0.2364, + "step": 47 + }, + { + "epoch": 5.050632911392405, + "grad_norm": 0.7927604968113404, + "learning_rate": 7.369343312364994e-06, + "loss": 0.2076, + "step": 48 + }, + { + "epoch": 5.151898734177215, + "grad_norm": 0.6375951563290391, + "learning_rate": 7.236565741578163e-06, + "loss": 0.1667, + "step": 49 + }, + { + "epoch": 5.253164556962025, + "grad_norm": 0.6651567314411381, + "learning_rate": 7.101786141547829e-06, + "loss": 0.1684, + "step": 50 + }, + { + "epoch": 5.3544303797468356, + "grad_norm": 0.7043980605084836, + "learning_rate": 6.965125158269619e-06, + "loss": 0.2039, + "step": 51 + }, + { + "epoch": 5.455696202531645, + "grad_norm": 0.7406146243351966, + "learning_rate": 6.8267051218319766e-06, + "loss": 0.1794, + "step": 52 + }, + { + "epoch": 5.556962025316456, + "grad_norm": 0.7560497079368976, + "learning_rate": 6.686649936914151e-06, + "loss": 0.1529, + "step": 53 + }, + { + "epoch": 5.658227848101266, + "grad_norm": 0.6135830262872792, + "learning_rate": 6.545084971874738e-06, + "loss": 0.1956, + "step": 54 + }, + { + "epoch": 5.759493670886076, + "grad_norm": 0.7112397939983846, + "learning_rate": 6.402136946530014e-06, + "loss": 0.1958, + "step": 55 + }, + { + "epoch": 5.860759493670886, + "grad_norm": 0.7940516397429221, + "learning_rate": 6.257933818722544e-06, + "loss": 0.217, + "step": 56 + }, + { + "epoch": 5.962025316455696, + "grad_norm": 0.7871752636384775, + "learning_rate": 6.112604669781572e-06, + "loss": 0.1946, + "step": 57 + }, + { + "epoch": 6.10126582278481, + "grad_norm": 0.5470125055488606, + "learning_rate": 5.9662795889777666e-06, + "loss": 0.1701, + "step": 58 + }, + { + "epoch": 6.2025316455696204, + "grad_norm": 0.5813020536626888, + "learning_rate": 5.819089557075689e-06, + "loss": 0.1426, + "step": 59 + }, + { + "epoch": 6.30379746835443, + "grad_norm": 0.5710246684545575, + "learning_rate": 5.671166329088278e-06, + "loss": 0.1184, + "step": 60 + }, + { + "epoch": 6.405063291139241, + "grad_norm": 0.8565249872894666, + "learning_rate": 5.522642316338268e-06, + "loss": 0.1978, + "step": 61 + }, + { + "epoch": 6.506329113924051, + "grad_norm": 0.7450325352987529, + "learning_rate": 5.373650467932122e-06, + "loss": 0.1521, + "step": 62 + }, + { + "epoch": 6.6075949367088604, + "grad_norm": 0.7228163461638277, + "learning_rate": 5.224324151752575e-06, + "loss": 0.1556, + "step": 63 + }, + { + "epoch": 6.708860759493671, + "grad_norm": 0.5931907548279679, + "learning_rate": 5.074797035076319e-06, + "loss": 0.1134, + "step": 64 + }, + { + "epoch": 6.810126582278481, + "grad_norm": 0.6442106835491783, + "learning_rate": 4.9252029649236835e-06, + "loss": 0.1085, + "step": 65 + }, + { + "epoch": 6.911392405063291, + "grad_norm": 0.6660065713778855, + "learning_rate": 4.775675848247427e-06, + "loss": 0.1296, + "step": 66 + }, + { + "epoch": 7.050632911392405, + "grad_norm": 0.513068792938708, + "learning_rate": 4.626349532067879e-06, + "loss": 0.1223, + "step": 67 + }, + { + "epoch": 7.151898734177215, + "grad_norm": 0.4707168636389631, + "learning_rate": 4.477357683661734e-06, + "loss": 0.0976, + "step": 68 + }, + { + "epoch": 7.253164556962025, + "grad_norm": 0.5584208200417776, + "learning_rate": 4.3288336709117246e-06, + "loss": 0.1576, + "step": 69 + }, + { + "epoch": 7.3544303797468356, + "grad_norm": 0.4948162292093854, + "learning_rate": 4.180910442924312e-06, + "loss": 0.1002, + "step": 70 + }, + { + "epoch": 7.455696202531645, + "grad_norm": 0.6003769756361554, + "learning_rate": 4.033720411022235e-06, + "loss": 0.0634, + "step": 71 + }, + { + "epoch": 7.556962025316456, + "grad_norm": 0.632817072117396, + "learning_rate": 3.887395330218429e-06, + "loss": 0.1324, + "step": 72 + }, + { + "epoch": 7.658227848101266, + "grad_norm": 0.5512268097086501, + "learning_rate": 3.7420661812774577e-06, + "loss": 0.0783, + "step": 73 + }, + { + "epoch": 7.759493670886076, + "grad_norm": 0.5935696380747312, + "learning_rate": 3.5978630534699873e-06, + "loss": 0.1258, + "step": 74 + }, + { + "epoch": 7.860759493670886, + "grad_norm": 0.43674489606470374, + "learning_rate": 3.4549150281252635e-06, + "loss": 0.1357, + "step": 75 + }, + { + "epoch": 7.962025316455696, + "grad_norm": 0.5040701068675334, + "learning_rate": 3.3133500630858507e-06, + "loss": 0.1221, + "step": 76 + }, + { + "epoch": 8.10126582278481, + "grad_norm": 0.5537439646466557, + "learning_rate": 3.173294878168025e-06, + "loss": 0.0895, + "step": 77 + }, + { + "epoch": 8.20253164556962, + "grad_norm": 0.3734160602926547, + "learning_rate": 3.0348748417303826e-06, + "loss": 0.1119, + "step": 78 + }, + { + "epoch": 8.30379746835443, + "grad_norm": 0.36353809777994334, + "learning_rate": 2.8982138584521734e-06, + "loss": 0.0546, + "step": 79 + }, + { + "epoch": 8.405063291139241, + "grad_norm": 0.5432026494165365, + "learning_rate": 2.7634342584218364e-06, + "loss": 0.0701, + "step": 80 + }, + { + "epoch": 8.50632911392405, + "grad_norm": 0.7187854238009306, + "learning_rate": 2.6306566876350072e-06, + "loss": 0.088, + "step": 81 + }, + { + "epoch": 8.60759493670886, + "grad_norm": 0.6028065371137555, + "learning_rate": 2.5000000000000015e-06, + "loss": 0.0989, + "step": 82 + }, + { + "epoch": 8.708860759493671, + "grad_norm": 0.6029218748519589, + "learning_rate": 2.371581150947476e-06, + "loss": 0.1138, + "step": 83 + }, + { + "epoch": 8.810126582278482, + "grad_norm": 0.44030990822373384, + "learning_rate": 2.245515092739488e-06, + "loss": 0.0778, + "step": 84 + }, + { + "epoch": 8.91139240506329, + "grad_norm": 0.44206891285952626, + "learning_rate": 2.1219146715716332e-06, + "loss": 0.1197, + "step": 85 + }, + { + "epoch": 9.050632911392405, + "grad_norm": 0.4181481470988038, + "learning_rate": 2.0008905265604316e-06, + "loss": 0.0645, + "step": 86 + }, + { + "epoch": 9.151898734177216, + "grad_norm": 0.47866066389040807, + "learning_rate": 1.8825509907063328e-06, + "loss": 0.0707, + "step": 87 + }, + { + "epoch": 9.253164556962025, + "grad_norm": 0.4855471053569369, + "learning_rate": 1.7670019939210025e-06, + "loss": 0.0592, + "step": 88 + }, + { + "epoch": 9.354430379746836, + "grad_norm": 0.42763865169197446, + "learning_rate": 1.6543469682057105e-06, + "loss": 0.107, + "step": 89 + }, + { + "epoch": 9.455696202531646, + "grad_norm": 0.3690131276831282, + "learning_rate": 1.544686755065677e-06, + "loss": 0.0515, + "step": 90 + }, + { + "epoch": 9.556962025316455, + "grad_norm": 0.3883137017573927, + "learning_rate": 1.438119515243277e-06, + "loss": 0.1044, + "step": 91 + }, + { + "epoch": 9.658227848101266, + "grad_norm": 0.7347299174387595, + "learning_rate": 1.3347406408508695e-06, + "loss": 0.0741, + "step": 92 + }, + { + "epoch": 9.759493670886076, + "grad_norm": 0.4812162548965024, + "learning_rate": 1.234642669981946e-06, + "loss": 0.1096, + "step": 93 + }, + { + "epoch": 9.860759493670885, + "grad_norm": 0.369367326407901, + "learning_rate": 1.137915203877003e-06, + "loss": 0.0738, + "step": 94 + }, + { + "epoch": 9.962025316455696, + "grad_norm": 0.48681431404942604, + "learning_rate": 1.044644826718295e-06, + "loss": 0.0798, + "step": 95 + }, + { + "epoch": 10.10126582278481, + "grad_norm": 0.38416364988319346, + "learning_rate": 9.549150281252633e-07, + "loss": 0.0772, + "step": 96 + }, + { + "epoch": 10.20253164556962, + "grad_norm": 0.2972730096642589, + "learning_rate": 8.688061284200266e-07, + "loss": 0.0706, + "step": 97 + }, + { + "epoch": 10.30379746835443, + "grad_norm": 0.3687593689489182, + "learning_rate": 7.863952067298042e-07, + "loss": 0.0854, + "step": 98 + }, + { + "epoch": 10.405063291139241, + "grad_norm": 0.28383029271802473, + "learning_rate": 7.077560319906696e-07, + "loss": 0.0463, + "step": 99 + }, + { + "epoch": 10.50632911392405, + "grad_norm": 0.329282008425657, + "learning_rate": 6.329589969143518e-07, + "loss": 0.0642, + "step": 100 + }, + { + "epoch": 10.60759493670886, + "grad_norm": 0.2500705047947425, + "learning_rate": 5.620710549772295e-07, + "loss": 0.0462, + "step": 101 + }, + { + "epoch": 10.708860759493671, + "grad_norm": 0.3989612983696247, + "learning_rate": 4.951556604879049e-07, + "loss": 0.1179, + "step": 102 + }, + { + "epoch": 10.810126582278482, + "grad_norm": 0.2662828923303931, + "learning_rate": 4.322727117869951e-07, + "loss": 0.0675, + "step": 103 + }, + { + "epoch": 10.91139240506329, + "grad_norm": 0.2711704696179231, + "learning_rate": 3.734784976300165e-07, + "loss": 0.0693, + "step": 104 + }, + { + "epoch": 11.050632911392405, + "grad_norm": 0.34511642958777133, + "learning_rate": 3.18825646801314e-07, + "loss": 0.0957, + "step": 105 + }, + { + "epoch": 11.151898734177216, + "grad_norm": 0.2889242607992141, + "learning_rate": 2.6836308100417874e-07, + "loss": 0.041, + "step": 106 + }, + { + "epoch": 11.253164556962025, + "grad_norm": 0.24450548412580397, + "learning_rate": 2.2213597106929608e-07, + "loss": 0.0564, + "step": 107 + }, + { + "epoch": 11.354430379746836, + "grad_norm": 0.35934542044635454, + "learning_rate": 1.801856965207338e-07, + "loss": 0.0804, + "step": 108 + }, + { + "epoch": 11.455696202531646, + "grad_norm": 0.26298606930327606, + "learning_rate": 1.4254980853566248e-07, + "loss": 0.041, + "step": 109 + }, + { + "epoch": 11.556962025316455, + "grad_norm": 0.31777226755411614, + "learning_rate": 1.0926199633097156e-07, + "loss": 0.0903, + "step": 110 + }, + { + "epoch": 11.658227848101266, + "grad_norm": 0.3193608086114228, + "learning_rate": 8.035205700685167e-08, + "loss": 0.0721, + "step": 111 + }, + { + "epoch": 11.759493670886076, + "grad_norm": 0.25486180463366104, + "learning_rate": 5.584586887435739e-08, + "loss": 0.0657, + "step": 112 + }, + { + "epoch": 11.860759493670885, + "grad_norm": 0.25091083569651457, + "learning_rate": 3.576536829081323e-08, + "loss": 0.078, + "step": 113 + }, + { + "epoch": 11.962025316455696, + "grad_norm": 0.25614891878084256, + "learning_rate": 2.012853002380466e-08, + "loss": 0.0652, + "step": 114 + }, + { + "epoch": 12.10126582278481, + "grad_norm": 0.3196686889199045, + "learning_rate": 8.949351161324227e-09, + "loss": 0.0842, + "step": 115 + }, + { + "epoch": 12.20253164556962, + "grad_norm": 0.306975262273726, + "learning_rate": 2.237838582483387e-09, + "loss": 0.0994, + "step": 116 + }, + { + "epoch": 12.30379746835443, + "grad_norm": 0.24537391909796794, + "learning_rate": 0.0, + "loss": 0.0314, + "step": 117 + }, + { + "epoch": 12.30379746835443, + "step": 117, + "total_flos": 4.902218749915955e+16, + "train_loss": 0.26980868625080484, + "train_runtime": 2812.7387, + "train_samples_per_second": 1.46, + "train_steps_per_second": 0.042 + } + ], + "logging_steps": 1, + "max_steps": 117, + "num_input_tokens_seen": 0, + "num_train_epochs": 13, + "save_steps": 500, + "stateful_callbacks": { + "TrainerControl": { + "args": { + "should_epoch_stop": false, + "should_evaluate": false, + "should_log": false, + "should_save": true, + "should_training_stop": true + }, + "attributes": {} + } + }, + "total_flos": 4.902218749915955e+16, + "train_batch_size": 1, + "trial_name": null, + "trial_params": null +} diff --git a/training_args.bin b/training_args.bin new file mode 100644 index 0000000..956b850 --- /dev/null +++ b/training_args.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:0e359e3476ac1fbe0beec77a258cb644e16d901568de9a8025204ac5c6c8742c +size 7288 diff --git a/training_loss.png b/training_loss.png new file mode 100644 index 0000000000000000000000000000000000000000..8a3034bea3de588f1a2f694b349a1fe02ba3724f GIT binary patch literal 45117 zcmdqJg;$pC);)Ry(%ndk0wN_SoeBto2!fPIBPt;w-5@Oj3L+|PQBo@1E${*=AShkZ z(p_g=e&6_=G0r)E!P#T){p!oZeP6ZKnrqH^J&`vwRmn-1NiYl}SG%gLgJHOV7=|-O zL;(Lr?EBCZ{6pIHilOUG$Gff`77wkl>lUs~_KvRhHkPN{tslDBI67Pu5)l>>5jb_< z)z!&G`uzC^|K}4zjt}phcX2$LhNloaUA^UkVU!l=e>hnRnKl?!kgcYCS=TdpaoEH6 zrrt5(N_VGbyy$S$ix+z7AJtEOqNk?YR%}+K8cNS9JFDq5ap_WX5DRNo_Zb%dQ@li9 zpH`DvyDcY(w(TB1`}4!~!-EQi<^J6Bvz^u3$y^c=qp7QMaa4+d5%8biWLIt){QDC# zBi^Ocr%%5T55qY{O--%M(uh5U4`fAKU{{rum3v!+F)sMItrZhS13xboA;Tik1DFT` z;m67k$o~KI>pinL<{BDgf6FFgq}hDFUtt`76D71}>nE$1<}E>}8pB#Y`~9tjcoL@? zjsM}MK|%6%jLhFl8X8Xwx~}v-HT7M+ay2ewW5cx|b-O8&_9+)JDWlNG&7#4Q2aRL( z!4|?yr_^ZNmwr$8Rg@1ox3UQ{N0UGNJ8$gz{mSgG&-dOYR{9@$!xJ_a`X#)7CEO}= z;^b0mP&hv5>D9|->|faH(NYj|)B8%wcOo!J{6Rz1`I?Bu#YLVh3bE&rv}Y~5Q{_CD ziu+eK`_0~()%uIEyEKwZm@f_#k?Uu^x_Hl9km~x?t98%M-K=_;|4DXN_PRrbrHHGb4oR2T;bhwJhP+xeQE(`)PNEDJV$YHDi44i$4e zckbSu81@)#?l%jFo}In_Uy?*Yi}|OFd=K2NRJkZdGvA_-de3V|$t7H)e%ov#KFiev zQl+K&_>P5!0-kGaXW{VSRGY>I;SpMH&iApi-R?Wo)$?z?o+Lj0KGC#+&0`2hK|#S$ zfsj?&m5AiZFf+SBp3(I5?=R$6u3Q4+@ zNV2RK4Jm^_or%XVw_}=wBm1LAk8&2B?|)sWE@qPVm3;j8ar*cBwtn!!d#gXLo#*7? zAy{2qb<0<}c9>iuidJ*$?{HK&hyTFB%+}B1F>;R~XF~tIxwEndD~+>1-jgy28AlXZ zwOS5WxG_n)-Y;&|cT>ot!hVJ|jtBPHhH7T6?=a=*-=0~UU$fvjB`8Ra+0uV=94e#s z^71O1c+Ah7r9bl7clY6}tMn6AsZZZKgaibdI06oWcGqVllGaE_NX&(qnBU76uWpY9 zSV1)GtTa-JxXtT&`SjYNo6VSjAc_{LCv`X&_}8`_*e^Ys(k-+fOLyL-ojQl2AqM++}V@yTyH6 zuMcHqOw7?AejRBWCgj~Nwfz3(iswRJDS7}7#-s5vFjdY64tr|dhwDi>ay2>o*@L+& z6H(_UR$Dm;G1u8|IB{H;cx3{X4J3BjdqoW*$dz+0Oqkd-32m6_CLK@Zl2;Ri{>({Rvda!IV?2Jv}`cH+ZR-n20z- zst%9#msJf7Umol~JEQ6Z8SfN4MmmM!*|TS5(=Tp6jgOz)GVXXmn0$P209*U=f;EYv zq9WDFlaX!lpA;J0r#N|(mR$FZ@k zBRw82t`qX|^6cbV&L*V^OGzmyf~B*sJMU_|79|c14HZlMyjTQ@*x%p(rKGcE!lsnx z$|>0W@Uby-$iuEnzv;W>_XV&SJ9*0{BCPJZ#PA8VI47u2DAxD4mKq`0IL#cVm$lr= zM@+hsrGo7Wsu@(?QrFkldoC8WnwJg^Z#he{dM;OQqjLj+8WI*Z0ZI0XzP^6wx}aGN z>lu|NkhdPe@z~p5HXGmLb?nR0TUlML&nq1vN$Mo1JFI+f*Ps7w&h;u35lCBntY$rO zlv%!H>2|UcM~C~)tIdp!t*wMhzl$4_9Bby>jgOBGajv5xa28q5V3YkJM*|O~s zA8Ob+Gcz-dm%4Q!j4)JfqN^9Z#4>Q**OLTO2oi`^LupM_D*3`~_7scR$~vP_}g;*US8{+!7^J zK?Fh5+!lX!db@q|mxl>n6oX)cOSfD&>~1{_81{>O__J*V12)#m5umK7h`Zq}2T67% z?f8K3URScS4@GK~me}rGW?H%~pL4g|_SZpIX|}&r>zei>RVN`S<@7C(NG@kmSs&~# z*G~Mr?MRO`RW8@?*BtHHtwJJ*Iyms}I)ah^VN zrWvYo6NE1B-R@LD0y3skSj1?+akV}5X=!OAjbusfqeH0nR9F)}qwy(~7}j%t{(E(X z-ETuXLzl0)%z1JshE2pWgbDt4uwUV}Fl9wcL-TJ42$YOZPM(2hj=3*Zd99zoMC=EI zSL+EmBIbHBqXGl5@7Xucmb&P__pOePkH2#Neim%S#IJj4^q=o_Gx+UoP(xZ3xb;bS zWI0|-o*HY4mKfocKiaWcg}{rFS+2UNktBY7EY`3(G`KZa&SZ z@A~y(x8Ic>1+dGom&R3V?fet4DvWH>u2e>O`X~=663zJR{jFRk!Tv3uS-@d2N;kH? zHBgjjW97CWyxSA_LlrZq3hei6mWT=%N3JJ>y;0c=HuJqs+ zn|Lb42#5{sjkzAxDySF}Xa?P~>rYm;w;3Un-=wG4m1?PLix^C}~|L z;)Hp~e=jgo*xd$v6vg6DcKPTq(aayMBSr;BAfa@7_Pf%M=VUZ&z5qki?6(ZSRS{GL zHG4Tb8$DXh*UndSK@^_XOqLwq^6f~R**k!P9!Y&hB|^&OPXs_H6G>JIYI^!bR=q}yt>;Fv&2KTYQ_R+VJlPuC(dsx@ za@}>lS50=a_vXZ8tO5g?-2MLi6j<8{K!|JpHa0d5=E4yU!xfRmcKwfgGPR-rp+=cj zdq+apN5#d(k+^lXx6@>2XIpOn9kyJXYQqgg%fq*5prdp8$B!RPfU%lj`>vEa42QJc zp*eZ-#L zD)MmZ>UXFcyTuQ80Y!us6ciAVk%T3nNLq6rVm8zY{R>!Z=I)-(V}PxJC#^)E0U zbTf}F}Uc~OFfcA|WW8dX+E9^2BeSX&l1gygGeVm!(bsasNX!8rxv8Yp!%3vDGKB^~xJ zHOhMf*u`?{>obSJToOz*nt6JQ({t*XYKTrY9e|3pk{sN+zr&S)Gfq1O93O7uW4kRD zMTW}e=H{X2Uxkt~l3;Em7>ECk1a@XBfqv`!ebcB!VM1i|%7VtMnPoFUM;e8x`I?9KC+EVVZv-H6zWo^1#UO_3G!fjuXUNIsw%^xMy(rp1TF}*BZ zzET%dj4-N;_qv{!T3cHaSDT*aQlo*28du68>v;onlBp>xGprdgp`oP>)z76zXMAuA zYMBX4k`!C(hEXY-nwq}vE`{l=`K!Fumfaq5p>L;|IM^KDoBLgyJGjZ;w2L`G8gUpb zsQfDpXu;5C*ZOd8p#V3~bG=hy8kXQX8H@NwMNHCn$I0Ttt0t)K!(G~2%mT;O^FQ9I z#_}zzxmAytEIaRRH*U6m?f^7}kF7%fu2?FyY$hpPf}L-;b0HGi$;WTryy5E*WWkOO z*1Hw+^rN71S2p;}dXGZC#^E&xkA@bA7TS}Ps?HuCQ#~B>U7v_%OKJ-X3x@#S2ZJSf z4g2RpJmfQpiHRL>z5(_*2i4nu|2on50mbV2IxWf|gS&ufAjn>n-m|v$a@C5BiGkRK zwno6Qqpgh^kmAH6QlY1%UVDD}TdzAiI%olqQC+@#`JvKNs#G(j)Rn2q)yMq#Su1S1 zCHVm9KRVTJZ=~w=6`L0up*=-OWpMKt00=2I0bLZ8qUVu(-#bY4^fd~hRF=@7Lso`7 zCM&JAyKj>x)1dl~8s^vg8GWAh0VV@zg*7mn?ml7 z1qe_E%lj-fRp^+Di>vOwDB=jPKp;=foIg*gCAX;?TI8OPun!1s@=uauOZE0h6!ej0 zKST_J3CN+%dUW6e{Rv8t=F{y7g@a3`>YAn|g-R@YbTA>MCG^D(v|O^)VY1qZ%Png>n#qP1o@x*N-b&b= zNeg)T`t{>;H$Rk_92*!r<0Dw$k<$OiFGo{bTl@X`Sz~KPdU`L{)V1v%Bf>y{s#&hE ze#bGW35V_y2M33Uf}-VMcb)%9be8%q%X@y|^{FelbA|>~zu*X#9_sSxrML{F0DA+C zab96HR4xZ=`Q52_p#2aHRN*@JDEnsS1Yp*OGJiTHMiH9^m@X6oXAG+E$JMasutg0G z4SWk@PLlJYLYSn2Pba-VWh(SDCVY#xZ|!bYGXVVq!1nwpK0XqoJO)S@Ff0{!clS^i z0h5Z}B^4i_kgzO~ZNs~FdDy*YIic}GTm^I?H6?O+GpN^RW}bhc(@Nj_04N=NeEflO zm$QhLf(Yoq8H3CT?Ja-zouzLXcptRVVgPc{!E2Z<-X;6fm2!K|MbIqunsr(S;KPi7 zQy9=aJ#LWteUB^kt-`J zB)c2!0R+Zr!(m?o4Eh(?vJT|7wzoZe&d0J!JxWey4G9T3B`G`+jJZfIr2$xC(s zU>k;=QH}YyvR7bKtnPnUY$S+4m;m(M85tRf#T$VxNh+N`*JY-QKGntEUI6<#?Y-ys zXAP(_M41_WzDw@CF+0BXGPD2b+4;3$LsRQ*6|Lo4dd}7C3DtKYF5@{0I`?(is!b`Q znsqFEoSlmf%FecrYT2=2`ug8sADuV*43vOq9I5g`A*Nqo8ofH%T1oC(pt<{#lu;|D zpu31X56&sdfeeC1AsI^H6A&pa-!ha$tXjyt(wrw-#(|G|dGQ_vG!!e)>1IHIN$}?s z|I*N)h~lzq_qfVgP!@O^L`4fb3`s)br8F$IrAM!;tGfh^i&rfqWL8VoX;^vgQ2eAxKR>C-R(Lf}Mkk|Z3%sBj^*G!$Ai zI?eZW#llB|f8gU9k8W?!3s1;>MoU6u*hF}pS8ubYSYS<5qDc=EeDP>VOWa6IT( z+qN$cD+oA8_-^NG6il!o><}-lT`4klCJqlw;J8yMjzK?N;8eTuM{Fv3xuyMYbn3|G zs(O~?o1UJM@IeEMO1s<8Oyn(0FE5*kkZYI-{f5GN5)v6q)79?70mPlHUw+uwYkZ%L zS#4uz8Q0vCI>VsKrh6=pxJhT`CKY^yq*{?cj6p$@81=pAP_uj2Fi+n&;BfPw>;NI! zalH(X45HXRXuNvV+pD{=G{{&`y=4@7>y8lAH{g@9KT(i`;zEus_BTD=4mdWj*m}KC zUUnocnCrV+T+WbF@e^^=05hqVtJY(x@&KYV*mta%^aWl#Bph1|J1J(X`+laoy}jXg zu^l43%df{4Ebi**wJt8&+yDNO{iEtJ;28KX3pzGUt*woBE@Wt>$wM_WEV9H0PCY2m z)H}Pux!QYE5eU4MA(w6oXd0O=+#!|ytH=o=0!XV|gLpeSilvc*lOvzb@pv~7eqrlZ_)W$ z3tNkuXT<`T;ID#-|ltckg3*%H;Sa``~ij!^l`QM5}tCk zEw%UqFf7PhyI}^!S_!CQNCsnD-0OhUf0mp1gLXAg;g*}Mj_35pY#%5EDrg5|qxqBc zPdLR$MMgyhQ{jSq1-OE~<{e^nLBX_%FNo5~ZUUZu6~d?d`dKYCwR!+V;V`%g6W&xK zNPT;o3o|cr&H%)O#&id0@!|Oj=xIr;lx$rD0Yj-5Tzs!{YyA8g&@H+|tT6aLKlR8l zzx}N%;S_8uK%DAHmM$dc>j$n`>%O>NlhYl{e{L6E$g3xC-=n7O-Gvbp^E&sj!ZQj!VCfmTQ*rWT>JT1KyP_KbVc$%6!6 z?@&4kX)b%^W#`@a4z%+cJhYH|xIL8g4Dx^3w*ZkdEy|uRH1!FTtVQvod1x_rVC2Hy z8~1q=+6gLW5)At8jj*KkXvyz3EqSLX1jqyN!TKL6+ch;cFQr`WzV9#Q7c+tmDzv}) zW~L@Ej`TGWAOtSFpx~2`U^MgFq=%C^t*e{rpOzqI(Qv|drJfLVFDq~e+6U#T!)zz! zJl@uuXKiwLL$1rIV1PXhfBKZlcjLRNgWIhdUnvS!$y1a)Sx^&GSRAXUVe)CdYmrr* zmPKO#t?TN7@P?08)YR4E@H`T8{$|n}VJ5*&X`m7gJ?s#?k=s``pOc$&UBIWA-oSio z@mJa6rw(EN1J8FKJ|L=RcBuTK`|`-rYP>x!b2I^xQP_P~E`tC@18Bby?Tpj7A~0*& zngN#)xrTal=iTWlfDuHE$pLho54T6)>`*f>gmEf`oe~wL0}-(f=*S5E z{4!jgcw$6Td=daEHt75Prq^P2g%1YBOBo8=QKmAi_7)4HU_(&$(tDk8VDQ44EuA|a z=&?Xm$#uPS1lpPtngWmpFJ-+hT)22~`XJ1jaIpW65n}S;al*jElrOlB)diISHH!%A zMtkuyLP8W!Zd>5zAhhsu+}70%0l}o4`vgI9&`-d<&V70YoFHld!LJBahJsx-0^-90 zVE)SHW~fAgB_iS>DG&2Bmz6!L1eU=9itgGL>a}*)ra`lM z=zp&6*Zf``9_84FBnNcz?ZsITjn12(j>tLe#se?0SHc#!4pplvSk}e|V>2WOnELNp zBQXUER0{}JD2^(~dkK@vmq+~f9}Iz*j6f~mry%H@$3RBE0@U0PLC*GkA8DfTLt;2< z0K3@Bg2R88Yyx^?N2~5 zPw^Ou1Qvi3PCFnGDIFc1A#ZEhLwWw?AVT&_4h}*{uZI*QyZ+xrb~7chwvLYV*-8;k zP8`UrEkI^{2d0oITE*C{Pp>a^u*XMVuU`=*XYeJML(2?W$O(t)P5pQ8-i<+fstUdi zcCRUFEUORl0nk1ZaK0MgBt!#Bas4}V5(dZ(e7klAeUI2;rhOpz3%)2aGjWD^PA3@r zTf_tF{O5RBPIBBKh$E3gCKW`$>Y~1}W@my_YDw{y-us|mB@dDY{q?R-76_1Q?Aq++ ze>ppy=@0annlP`!Rsr2bhJ>7O27IfxmzCWjhm5)4tx*X0fk7yjdQuG{BrXW^{id?y16KSqPpR5fw!XhngDB z=tp7v(H^^Tz|)pHE91~90%y07l#sy9bNw|Jh+-k%@6%beJfS9}WOwzU^gllI01EM{ znp*ak{D7m~Ohgw<_kRJ%h=hi|)ZtLsh&JI-+Y zCtgsztAf;xQsQpt6hk_7~R;qxs+dP-6bP8llDr6FYJ}4TduKzY?EoblG zxpk3YNNsH`Ks$OJccO6(YD-}zKKt`&jh)=E-p0<&^lQt_&CL_vRXOMZnZkUcAjL*> zCP^6VRFRDP4xdG@05TVNDk4fsM!*TB(8{?CI)d5d4VY*eMn}zn_XPI|r$hNPLy^z6 zL+N1*yBr^)^QGMvc|rb3UT}a%$&H9A<%DUsF#!W3Am^x$U{QVmLhT;sRGID z?+y;{E{{~NiGApqL$puxdbh%P1=GGmekrM2Xt+R1w%O#&`&1ijvKwrb(>1)R73Ji- z3`{uCoXUV!K_QXlM3u4xNY#Bar0`_)FCaYxsZglMOt75O+gWh-a&HV?IbZ5scQTZEy}Iy*ZnzSn76&XbVO3^-T~N2J}qm1T~e zC>eBc>Cn4Xa)dS>b`j1e(hR}D$p)>@w#VwgwgG+mws!Wb$ST=;_g0=ha39K7u7KwtGdoww^iBUlhJG$`&j7BNb*=c2uk*R_=}UOI zYzbAdysuVnt3mkx?Zxa>se(iv5gS|3C&FmrO3m)SGtN^$=*8HIHldgrL~_P^7;Ra z-7)?xo--oVn0xsBd0W`li=Lj>fFB3Iu!fmKrv}!>j>Pk-V3hzX6w*yd zObUSdh9){VEsX;g4{sGYG6O({i*Cyfofupktat87~ zSk*tmM_A16kTrX}5Z3awuq3lPr;~UkQF*g?a=ULmDBJK zA_ckMyK@#loP7zXwf%lAQXH&w&+(k|F|NIu^*pt>1FTi%M+dux;Qkb`G?>+A1-WBm%zeer~GgbL(V)S?M zuf=f@Mx*ZLLFsT9kU_*y*@B?8eRCyh1=tYLt0q|vk_3gX;<$(pEt4-6#AMQ+670ss zR{FA?_d~z$+)-2z@VU=)lp?}Bn8p%H`greBL?_R5C-;YcC4Ummi zl$jh(-g&Rv&{vc^7z_i=CbkR2EFj+bv{-Sl%3(PA?!7re(+_@sAqHEDCu}t`khsqM zzz2Zxv0tifp9vGUx~w87O(1jZo$IisnywvHu*@29By#kXzhr!?yTo!Z@;~)$?$d8x zbejv0!TD^3UNDB9U*8;jSY<%4Y8x6xfL*6&avjmLFU9N_{P&k6kX@EiZi5O$_ETy) zDGNWL&*9?cwg9`Nr28Thst*T1khsZnh>;Nlb{hLW=jc@@hTV{Sp?_me-bZuByyv^C zz{_ux!O{e$M=cwd(jL@LJWxv((NOMHuZD@2jfb%~fm8CW<7kZ}FigPO69)tY#CD@3 zf$TobA;h$Z)(13?C<5t}{I1OkXl+-&o{1ep-GHyJtoVc9ArRX&T{CaPIEht=++F~) z^!eA5qdiu2KwrT;iC&3{6h81mED(#%suU?aLJ7{cHL!uvZ>=? z#=~cE3rzasKZis{@F5`(GB|iWGfXdQ*^N6%B5Cajiv&eM)tdTEgG|#LA4isj{Yoh- zQghO8QcXm~I*Ja@$nUv49%h$$o=j*!WM*EZRG>ZaIr4C|$=W1C_v+4a?LFt|WQC%A zSNBPS=2Df~%Gb6g zXk=m%=NNof)=bWbe7rn5f@II6vG`xBOFZi=DG#{XJzAz=D+S5ieD67TxSUz zd3JZ|w*AZE#Y=C0zJlSFg5dEzH|I>5(zZ%cc!&(23NF3`*)rCA}FO#=$w9}&#{az$tohMoOE>I570 z_!_J5{e)T5it6+@j0*Es-5dYouZ;yV`VSIT2Cw_0>jf7G0tK%=)sDLKmVg3hQ9cC^ ziy#-P&vFr(wJg%BPT!fds%Ut3)8e??*tb?J`};h+NV$^|R`P?-!0z0RHdbdWG@zecrd?GZ(+~w-La`mh{4>oI?9GRosr2E|H-b=96Y*wNsZp-4qz!SWPJRV zYj7TV5HLDhf(wV2m-lI47&kdT=~KOOC0u!+t{Qo zR9}X*n5jqNv^Wzf&qlCHc3r#QInO(*`Ft+KG}OiJibQlq53aA>Oj1KKawE81AA{p# z64*h*T7S9x+9U5>R-{vegXho^M1_}fKH_)(dl`g`rr_@%_+(9r+;)g#lJwgX#nRK$ zF;q=J8A7=pXnJb9pC9Y-C}mG2?m||c1mdF}i0Nq1aIC;$SO$sCdFm@QR`)aSHV%e9 zTkbMb2oP>}0P6NQ$W(@<4s10CYu5yf%cuZ}~9_<(u8 z{HEG&Xy?i9I7)1-Q=R-(?F022af(2GQn9fuZ4DrAH*jc^pc&raOIRU&cw z0Sp7u9@=)qSR?w#9Dymg=HU#Y9#9!r9n$}RVH^jxfQX#@3b0thaAN?mK@V?%JN^>*}MIDAD!9R$W2mmEmO3r}I1M~q-4hay6$(V#O z@Gv#Oz@Ej&2fx3T*d99yv@a5fK7Ibo?-$)(TWT$qxxD{zWC54NpcElFv#wRSZt-t1TJ6tw zd-;c)ph z#uVM6l5KXo2`i*`c4srZF*~j?)^6N)7I$u!p=zV{(9@-v^UHeA15bJ6&4z#Kz-{&qspn=8t_$@afK;iD6xaC{K_?j08xpih7ib{0GuDP10e z4@%LE9cXX{z&`|m8&1gKO9ecNjG~g#|6HZ`r|*L!2q?)0L=Hn%9?uA8$Hh=PRnTwM z{FokSv&+Ebsam(Tv>=kD5pWO+dR#W^x0ZM8#_VfTK7|duMMCAmhcPWz{<-3Ngo8$BH)M6Yrf&m7#oZn%QiTfn- z&gE21^@8I0-nfXY-7JR>yv6p(_{MT2Sjp+I3!ek4srwgt)qR~7@Ne*QAGnF)CB=N` z-%mz0egg{dX?a_2E@CI5^s*+Ii4m>!4ufT)hw}QEmo840qOgv1 z5;OS_vq+X=6qEveXKiq{smys`5yZ%0y`S*=UA`=L4>ytC^2c~geb=pe$2?ix-1mP_ zm%eL(4YV^E3kEXWW9P~34C>pzS$K5g(CF`9mhaR&c_aXs3SGO)z5ChxR0 zsGIum54Kmy-c8?vwvnls+f9pVY36OcNux9_He%w(B2Af?Z-k^Y@6or#_MOE}1hy$zjV-@zS>3?(t>n%&odM`UVSMd5Jp+Td^YyQT#>-%! zoc)?@{n0~--K7}&Fmu~kD3b|G=S?|jtZNx=CfD`gNA~L1_eGxLrG77q53n#-3dI?! z{GO}If{DP5Kv%DGGo|s4udgq33AFu>=aqX)e875vF|3wn`MfojyS(%4LsFQ7Bnz4WWv5)K2=PC zoN+$a=%H#`8^>S5>OLA+T?)tSWuD<#G){U#4`yb?))<*~y<>I3}`dM4z6WwyR zy&!Wv=28RhRuu{hz=YQo(o^`h#jgbe#9&+7v!0WjI4K4#lEwYRQ}7ol33I4z)b&<$v*B`bkr=q5Zabib$A z&H#`a@J!?AUMBFmXZlK3%Wz>a1;m#N#-L3Z{??@x3qyije7PVk4W3w)+jk=He{~h) z^a1_=4|IikFze?0x3B?5t?}&4)CTCzoW|;K5EEfoic>x~()yL>MCJ8Fzkl*(3OHmt|iHV67pybi*8xViI z-tR+}BSyI&>M=OJgTZt&35{W1QD5QvhwmS)ZYfhGW|%y3x^~Qq)zK;(E^Mxb!Aefa z<(bbIT0iVLiU*sT!yD2!&6HP+ihzphA4cv@#CN% z7@8l1cM0?S^Y|~(X5WOe3MZhmUj+P!a+}Z8I}tcHHwPF6z=zu)J2Ug+si`UT*pr~Q zA^ZwdC!K9EbBeTE!xcso-3N>-AlaFNKQ#@yrvmxdFkSc4SCv-#vPGPo$gr_WK{axH z3P>Y;TDe5n0&*sT3eNMVGbtQ8e{;COgmg1gujvH7Sg*agOu!^(j+3R`a;WW$708G2 z7a!hKq|+rKuGF-)I{x*dM-eE;-WOjUW5T?=L~us|lr@JzxYn9uOtc3SS}TyXF+h2f z0^n$H>o*C9`xlmQ+to>uFYR1zpDoCD3tK%px_!8Y#+I#Xax;b78Zid##Nsw0AHvtg zjvW@%3X)Nps>+3R0CgLj&4yrNtm+(hGKc$JOrrO1yl(}&zhZ_{z+S%Csp=H|0;z9$ zMa*AcEuOwZ|H6EGj`a?MVYSZBouDNgtoE;LM-`Bu%AGf0`Z(rL0t^eyaS*0um2|?8 zl@Bh73d4;rtPX163UU(dn}M(gMs;~aQ$drCT&^Hl$>vwg=jfL+l?~w==i>`kt{gDe z0OwMr^D{jrD1vz7G60=p=LassNV&Dgmb!87Th` z?N)uj>I}C#Q+@tQ0n8yl9$b+9kq1|-@8VeI_N()u(H!&N4Tk;^pdlliJ!P z>EPryam-shkj`2futM_h3D@u^Nw7mdQ7ka#vdYeGmPN5tVK=GNfzTpTV15PqE4P`Sj&_?MN`Q<9s5d#l~x%Ib4P&hcm0tZ*>1gM``QJ3X)` zx*qVNr=P4amniiysz9T2_33U}geU3K!__h$_5G>SKK~yPI~(I;cIq15!r!ZHVUwHk z94KCaQxI=bog~|MtZq-w6Zo84jiw@8X8kmqMpx*tcCGF+xHsx;!#|doqzMe6PQf}- z91hVKyR>kfPvyGeM$}$5nX6%YME1>&j`x%F)0d_u&|1rl~mzo{W@x%y+bDA4TCkEXR}ezX`7 zA8w7XS1XNeF)XY=z0H5}?*I`nz(&fSyf z{P0~A2 zOmiFAf~}}Hro(-s$h!|em5xl3qLH}&8wph0&B^2TWwZOMnxv=3lFirtL|13%s~h?V z(;pA|b=l3JWBD53ft9PZ5!TuF{6>Nm{05Uc z-lbxlM@2(4PI}J8xD19>5)@RJC?7t9#%y>@JwbBkxfV7v`zsF4kp>;7U`&tE`2FRX zH)2F58)AakIjnfevFc%5BFWpFwaKDbJ&zy-&&>FdV@ac}i)S?}9D8Y?+gW-)r<~Nr zk!N3Ce(P4k?CrwibPN8vGZAwneE<2*!hM2Nqfbc}gJFr7sqil4JR8EDZGKfZy=i~1 zrRtdLQuforJFO>uD@2Ow+fgJfFkw2;#@Xh~Ir!hKmFQe4r;vOSPTZ6=8J4XAStOr3n5BY+3H!pwEx)IQ+t4Y^s>NTYG`eiRQU~=T zOAx+AgniYfPFFYqipy%-(qX#Zxx&9Um`85Alxeqf!}~~?usBt+d|hEvO#+h?(`R@8 ztEgeb#)6M!9@G28v*g*s690UHbIR*o(QV8mf0-pxP013&Vvh<*Rd1Hx6^3y06T!G* znV9cONovVnERi8_C%Od6i%-q(E;UZr)=iM>WG9Ts(F1URX*K`*z>nJE=eVagPU_Ax z{!mDgeS~*@)%S@d+FCP6LBrXWXr6- zan4uz+1rq1NXGW92H7-9{ z2sV#rP}NyqU0dE~d2fu?BLvptzsw=Yx-Y(@BFmFm#T@%lt&bFPG0rwnP)+6YhbF$!;&0Lb?8*#eNa< z@8KFkm%^1!Ws72D;x<4W>#VU9%f}l3#xKfHc{g)=bs}I}%=QjGcT*;a9N8YR#;4i6BL5F=*1=pjeqV>pXzC;t6b-zDSW+V4T~ z!nS(%XEF%`Rm^how4QVPWgA~4@!v|U{wj3G0PXN~I3%sUqFoGiRhCJzBL#lxlvuh; z1U2R)n}>;4zSUmX{Kjnp1bxJYFRAGs$31*n*wlZklER4fzP1P%(q3#V2381xxbf%C!TW6k1qESaR+fOJK#0(%7 zayM)Z7@d0X10fOg2mvp!<20-dQo?n8xNZFAPXrvJgnUs<;FI`+{)IAsZG_IeYv>*G zB?sQQal#5i4T>`;$E~xx-P2X4$4~FM`P&o=ED%p?dNFzOx)BF@3fjX2O%rM2caadi z=Fr3q{ZJsmR;IculdANf)MS;LV^>Y5nepzs5E&+w(Nkfm)gzO`RtT^dNQi8p9VV74+C8C+a=Gg9tNUe#Hv$#Qesn?0o>8 zG{MQI+UCt?Sz;uvoITw1ZGRrx~kmnafTj@*bY z)TzEze%2Q>X+z#aGH{*;v+@pU;0)|fbV)IXo%Mm8?Vsy-7exK$kABtZT(->5Bskb` zgGNNu3O=?dlQeiLFA!USRy1ArDk||{J@}s)chdixal6+oVjM$RLyEtKM)Itgq?=Dl8zhIzQs z*wq{tR?|ePGZ@rNDn6G8*ZCFF`XxV}?MDUZm%Wz+K(4mei@8R57= zb}7q{;3D2}-nX%rjr)0O8l6XpJRZy#dT4Z`>g2_{=0IBm6HJM|VyU;cSA84qEh8@- zl627Br++tc;GPV8Wrf(o&f90bPG2Qoz~K-|2^|Dg^1WhQY3_3pFM+ZAn^Iz_nfZIo zC(I|(nXtN>3d@&+n*aBmXW^a6AYc3ij}mgr0ylsx)nnkjfX=Gw$02Z?E?@?lK(`Np zj|Q`SFgQ}v;qFAV@%qoU_|3r2qR{s)ri5(nIE zg^eUbeI>d(g#6TcFD}BBbTFRop5^0f&+UFI=A1{MqjzC8`3+6-e@-9#=T2JWugN07 zXFub6kVgB8_lvj&82Iik5K#*^uXZqRC>ToSBLjr|O59KQt26kPnHg)5X};PP() zPgfKWt6A+` z>j5W|`tFz|ieQyU#7)|?&i&6KXBYp!hyW@E2K_k^a6H1dQ-$heKQDEIZ{=!hYlAN? zNML{azYKseJKnXM;TyJEV$Tx9dJizM<%CPU^X^%i&8*xBh(0wZ$4 zqX8(<$A^0l8_Nnlufd-k}X~K%1Blro1$ct5%GJTeZIf@{_nnzwKNB^Z9x{AM1?a20lqPa3iBR4D@rT1rcP-xj?z6N#ABc9hRur|MKrsR&bV*np?el zT^jyfC6zo1X?t%)kgj;^ukVMVQ_-a75rpc=3bi{)gaTnNy}I3>S>;FLlF&%F>F~9B z*2(t|41jD@3*gYSSqwvS!M&0mpYB*0%htJNI6%i&r&)!}{9u+LN zb7NKWUmCP>&gqlWua!p9;698#u;iigG9YQVjv`lOPokck29Vqelw_m!Fr#-mMbW5J zO*WdmUb}R=fwt-~x|DNX<_M%AIcA@coC$)0#{4=acN|tHKW?sa8w?sp*%KYsscC_CCDIQDQ zEdj5pfdt-y$I|jdtT}!IRK>iJ>d6yS${8bGGdM&%*o7DnUi7r*JaO=GfdyoT5hlVL zMY#c0pL$kX;H%UWW(zu^+(hhqJmHZYQ9C*3n;>L(X*bP`Y#x7Z_mF%JbC#9RziYgX zRO_0LlE|#jm0k_`G5rG{)DGP&Ugt@WIL=9qA4k8S0?y5h{olGM{@=R9)>)m{$P+3I zrKVVtSmP%QeJn`{x~p%F;JR587C&9vlXeM)l0+Gg;gVvSxPwFH@{RH`v%i$CQcJix z3=0`KGD0<58uLvJ{6Y9*b7V}3O9vNdo$NI1JXhSpJ=TW1Ri_ zWr0kVR)N(%uJ{jRBnat;V+&cxtpsK$s}uH(bt;G#i@4F7USK99q))U}+x49&;2ZsN z)CcceFOs>xHJ4b+V1VKAgq}^*?hxS=WKi`;Dl_U{Qc@H;jr>n()@BBYlx}ix6JraF z&eAOZd`~)=R)+PaZK-c|X1b4jx#s)g13EjFoP)I&@*@cdz|Zaxyg&0HDCRjQlq(&) zryFunuoM4%S>7M`vNH9w3M%Lw00n`IjyLm|5T{2mHzde&U|vf&6@Ired|@d-fo*p) zV_r(`l*L=^YNYyw^I?Sd3ZP5N&=O6De)$S$$E@^>J|F(Z}boaxApF@ z-VA0HsSsG{F_O&>h|3YETe6y)S?^xZJ@P$It{0Hu`fD5ZnOg*gtA^#j0*rllCspjg zm!g|d>A%wgbQpp4SSC)qYBEx^jLt7GQMgF~@<3tbJo4>(TNgD>fchKOpp^(6z&6|r zAUP^;B^EwQ==ky^Am;p(`1u|n4g0+d!$w9u9 zU6f1X;KmM~&k+INbM;ZtmhfZ`geGI(w zp8(Nfk|{uqKyIZT7~xHh|3cIs7HBNgj`#SCT);!Op=%x(k)(-b(KnwfeXgB1`)R1< zt+RN!ul|DADS(HJY!>YQl@sabiU?rC0+0%Z*h5BKnnIu$YS$(pBt$6|*M-kUdN)Rj zb4(EFDAlY^B4qMe3T3)2ZUY(F7Kt}w)Jfj_HR*w1IqS09-W9(7-;`Z)As7h)t%Kjj zcl~EuAU|Dr!0Lg6ET0I=Y9|LU++4O%aEm!b_U%X(caQGH%IQUPcn`ArZ;=p-B+{^B zOaEx%xUrW`|5VQ%8~?Xoo=hxZfcyq&4H04w;caODh(W;O3jvsyEv4LAZDw%Hgs0K1 zh%EWv`^Z{FIK2Gi)*Y_*=245^2!s5;g=?JyHmK+otlPP_zl^7WIzV%oyue@@$F6W1 zLBrWPIyx@gUM}j~K4(k2q^+wA0;wFMv*^A;R+kdH4Cqk)Qep8Ag0xH}-v<(urRFXi zJg?D3goPubWVsJ$JnDJ_6$Am|KHI_$aX7c=ClaiLPDU8i+zZ0(02#d(X9e3xR`cT$ z3EPMqNg(w)f&^`^&S(!TzCtGqmSnHXk6&2*e@{uUS)@10n>-lUz&)BW)F5%bH3wA< zo@Z$`gZ6K)cx;BhP|vipo+wpMeyE7NAiSZ@VJ+LaTz9*2uc+=TE0$ym|fCUNP6)05vJ7Fi+7X(kxQz_z+o!YdQDZ-{CbR@csbx z{^V&8{OTibS<0UkN+W!*;qz+Cdhv1K;9~n13kcz5b3lA`f~qGeEe#Dzlkxsh#LvpX zdSCcX6mQ3i$9071Z;&-k@y=QT~q#ech`gGn`<@jXv3%815|9?6rHd?yKN)l z5)!n~#v@qN&5b(YoIsQX`XNWK)1f=47mzu9`I@O(gp=|V-IW{uT(ib|ej>y}%kvfa z%(5vN=7o!%YmAW!MBNC&@z;Tos&MoND#!Q#0GmlGU(F#`^3oLQ5d?E5qN=Kjoj$L< zBq~&(p2cOH?I-@};-C&+aHl^tPxjk91tNb6RP)^Q?hmnCB)`8hBOKzlVWY$Jas^cr zfU1(L)?)@@Z0hk4bXUP%m4@q=BHM0*Z9X#I?r1%e`sAuGLt2RSHO)Wk-skgasPDeR zua);Zi&jLl$HZ6=KyaG~F`(@`nhy$e6h49mDWuv4SfaZq-#*`0-#!!%cQ;mYvwGCm zb{>f!%AWp04Tv^MKtGw?n^?aKmzZ@$%AXKbqJt>pZQCwt{ULSJxUH7h`w1`2)B-Pk z2J^%?9NK<&<);bukE!6e8{_b-k+ZLnvtE0sw>Im@$T%Mx=(!Pb*zzg-oJ_W6Aq}qp z#lvEhl#VVLS;BB3FknDxNrkKzu0hibJcnLr1VgcjwD&-f)b@uWdpP&)t9bKqWSP1# zHN;o1*es};Igl>2h2~C}g#KVid8TM=GxUF)b4-8Z!T>|m=E%t|ulz6;Hm{u=7#xg( zFMlDt3#NTEcoz*gNaoi=RU}8NDko~_R|1*)vYeyFIGo5?KJ9w(frT&EMUP&3JZPD& z{HVI=Oszn$G>-ez7^Zn+yMdz}q!0i-B3#8B#HbB}-v{_eGKGNeI1no* zrli~l%QtE#ylkuFR$z007~VM5=IG0X%hCF&Es4zCpoG(HEOf;)Db)(YuhaH^J;YH} zAK4a>wvpUB*Zg*y#^<4|0`v>brSN=!&kY|k7X_#! zI~W5;Yo&t0_UD$AYFk0jBR`XQe^Q9B|DrEX{z{$vy7K%tC^ZB8B@(jLyK3a z560|bG9QZ5EK^f3x8# znP!O8L~q0O&j;Wr(FNoo$*fbCyIgDzH{x-_bAX^c&X{}tPfJq0r{)<1SNiVfrQDj0 z(no+pUWm^(KVOPx@_zy-b#kg?Wv$Lf8r zl*pFwu z6VSA=Hp**yINqZG?Kt+udv#P5Ys}sIsKFSw?~)>(vO?zGb6S-#(<)}QBCh@IHP7yQ zlri-Z++@I>QQ85PU1M;W4uK!{G5;^0PD$_?o^#|9uFIMqoU3DL80L6YR@RQCTug_H zSbvm2HF%WB=*2a^8woGM^?fOXZ2X7~MzmX($+S zh>3b>09CH&t}%~`;o9#7Q*Tso@=7J;0UTuFjh8I)Q=qXZ(|c@)$L*HzIh82%Y(uA) z?BEblzyKmGtwzp;_)$nNlsm9v5Xs{v>fp|Q!r>YK&x+`dmEBxS$WkT=&y$yJ2h@q# zKLMiP6QTQVmn$Iw)|I!3OMaMm)#stat%KHoEvXeXxOX5Xft0(TzmtFURR7ctkW=|) zgz>tVo8Qh9RW*iVR6%_Hdp!jI-)TG0eVzp+Owb94&XoK8cYVy`Y< z4|@a!P8Nx4i4nz`8#1XeygYeUK+>2*4v(;5L8CXxj^b-enNjvOPk0xOXvSZ zSdYzl%)FkV`xuz4Jh%JLfz9ld>+~UG$~QZ!^2Nj!C&t?pxzI@dxs@9W#WdmUtVe3o zE3}G2+gZetTd;^c_KjUWB~CPO@atJQGVFM(Q6i|i{AXmygTVX7+zy|zZrE%Oa$4-0 z=UM+@LHiAK1$bZivDrI?GguaUv#0pHgUPY;z_=fY*`qrQAkOX+4yK3uf+~Pn2W^EN zZhd*)e%TC#{=cAq+@53FT69&7WX?T+7P}*f#i*A0#ADq5Sk}WNV&QXQuc%N94BKF1 zKFS%y+`0&OlMy5gt`26#rlm1~NfLaJG}d(ow-MX2~!$LcG9zTTK;_g=^D(%^woSuBB+k0*}|BsBFwTaM^C z3elNp6&@}$iCTVvI-mw&`=T|`W`|~DnW~Jd4ES2Q@V3YBQ zb=THEx4ECjY~Bf+z`65euYxw4GUFSKNnvma`~M9O_FexTpny6s(ezr-(_ZHte`-Z% zuB?hℑKkK#aKPeZ*O~ClICkC0W{wini~VX~8-N*ZqzJnbSD^v$VI*7cnu>Uz-6I zgVNp6CQq>V{@~QaF9zJz04v6MI?P8$XYqq-t`z08@%fcE>L;t%wRRzLd z7!88&PNVK}$dNi&1>~60LeI?rP7pw{X<6M$Hq)BfZ19)x-irx^3x2G&N#)x4B;1&9 zoksfYz)b(dfpG`mHd+&@pCd<*$fZ_n!o$zsc{@Z`mkiAV`wj*#2~_!PZtMR973I{v zDl!p5ojf2&D)GuND~0IAvdT;=mB$A0AYl^@)vqw)VdWQmeMbd(FT{SbYHYKB)iLiJ zgj)F|&3B!!eyv@lYD-&Q`R|VG2D9DPA2|DK^G)9%ZWmYpwnRlg+tT27gwz_x;T$!F z-Jj!Stf-jrXr(eN`j>KgX4 zm5ngSjN}DR=DFrgJV;>#o%kcrv-Z$yfFeBS%A1EohHg$a4ai$1(vEqW9x*=y1jy>7 zHz>G_uKMsl*bN}JcXHkH#Hw8t7}NjT&1^TKbSl3ws%?cP z=y)P@ZWeS^x2d75-buz+Jy#g+J%H@WxHNwmP+TmLg<-^9IV=3+IAmOS6^h7HKpu>g z8mv}D_^BGC%IZ53eC00wman))%Tv)`+Nd z)I`^JS5w_)zZyxIImR&l1%TN9{RXKp_zlgtG4;KP4}PaC*?oMzR{I0KbQ#%_ae+ba zLf;Ojsi!~&2ORqA=Uj-R5Du$1wZ&s-z_7^}rhQpxqUG4M+;}iSreFuiEpC_jEmnr2jkkoCWk{>$C4XiU&I$gXkyX zqn{Z5Xq*}Ob66zt+L{EAkNeLvV|UG@sl0ZoC`3Ma6NPbH?*1@(cj?rVIVitRf9iBK zWaPnF5_(})Z#}om?l>a%9e3^gD}FTjF5&=AKczqpv;O6@Z5jSzn|vNS^iv zIHbUd+7=UsH?+>_3Yu9tbHd=|y}vN}t!`DpHr@t4avKloL_Nth7rmx?7_K%$YNV&9 zu95II@nc^M0)&6u4~B&ME@99tK@Y^#c%KC$+m!r-3};^W^pUUv?F;$f&Owi*yRl_v zLk`=CRP{x-#6_fuH%ufhOF0=nE5rVFWd+p9imBWT!bGrj;&T{1wQVCB-$A#7UW{+j7lRn|8 z?Ny)udK*fbu>G}@3>NNQvTiE*b-vN0*9|I*g%REff7h)v)~}fk7KRtgBkx6JHY${_?-Tixbu@2=(WNl55I9eq52j}DWzuFyRU3mZ-v~Z!dNq0-`;+hsn_uA_aLc&|1K;=Ea$2cS(Bf1^iZ z@Pcu!bl}X^qDrBc;#*|sq?X#VT=AbubTn3>e~|{QhVx9Sd8c1Anux>k1zI}YNP-A6 z%f`13Pkm!a&(B4cE>s>o)7ym61Jz5|RZ(WU%O<2Nf99+B4~7@;IKp3dFo2}RG!VmD zvo;cD>M_Oo5IQV&umzrQyd}vt_!@QPnkZG_(&C@sbT2`<3blSX%^RW1AH8RiNpn?q$rhUEX0boar5{5N-0s|=r(*7Ok^Gvs+?j&#~dV^rxH zplHnRV%~rDhEkG#k{+njyS@{uaS7y+V;i{8S@-VU$CmMSKu?vhp;xDQt&@+&TsZrY z*4foXFe^y^V#1Yt1%HQZ%Q>wMqWt=f@Luw|c`veV0x~FiuG80F?X{*c(mJXtU*`9aBlQZ9;$Qqs@Z;ehFiUg zt6vR}xnL}m_I&@qWpgYOA63_*c;Dut5d@-5zZ-k*4LVNS45=F7ik0np9{@aQX)SnUBdQIxX5>H2v52}Pp=^ka9)|NHVE3oBJ2cPXwqh8>WL zPm2rlU@d8>ZU_niTECbT?k|v7M&yfD)ce|Q%F>+us*ZOs*oTWJ*d0+U;b~Sjs-K39 za5!N*S8#y5ip-|RsXThYTUfdB1YzGrgj%st^_$8OpD7 zugXtH*1U2>lqxE5=YaAX+x@DyZ8VM}c-Uzn%f~Puw$B-aLo?vLXMPei9S`E2-|%v@ zB0^(9KCq7r*S%E%CM7)m@DlgPY~e^~K3+!n{D!2Q-4CKc=;}3O=?&8T++a`8FwT?X zcI>Yffbwv^1+{}*eReVJ&kWV%bC)qX=(9oNWF!o>nkSF^srMr7@>Tz7HbpyGM+zSaPj;4%@fh|8MhyVAVGZBA|_riI^*3-dRPf+%izv;HSnQ zyIH;7{hSt@F24iBB8z~VsBvRdj(l16LaW~nu7WP{-$l?sH*}?%3Q0^hw^`lEFhp!6 z5R=saF`8**$3eblzfCZ0>bqx6ar+IcY-fbW9CYN{&)=a+Y@4HBZa~h)*ap=!)jBIkDrZg_a?tND88$Vzkj#Rc6`va@dFJWD|k z6J3I$T$J$06Fken*xa1KfsHTmsdKpQ+4(ku@UNWoSjbN}@QyGe&1~EzP62_#LdT0I9AXpNCl9fdJxveAc6T&!2*Q6R? zq*HU9X#JLbx2i}(m^j+N0P?*x)GLDaLbINi)j|38NAnMN%Ue#myuTl$M&Z>_EU(1= zr!CBr7J88!!v&E4%5~;S1+13}JIEwv627rHYIbwspL+NlUl1BlXq9aYB#d_+vR**^ zo&g^DL4R1He_ca!^s`Q$*fV=@ z(EPuN9c*ArmG<|KcI(`r*>^oWJIRh?c-!tUQc^ju%`)i3s8N>Ub@8XyzRTL4%tG#x zA|(Ap0*3>&XUBLzDfPK|+)SYlI+GtOWyXufJgfYi(SRT7FEl-^LPl*fP3XkwpFa@~ z9?N&{n2~W%@3?&%=g?NuEhqfzc$AcE4ZHLrU{*GxQcTu%3ouT&f zR{Y${WK;W2;1K82-#tz=c|I=CQ`G8f-ZB4tpCo{izJ~Vbc!iH9Pg=BNiDEl||K_5J z6YVKF7&Vx`p}9Ca*(h>t}|E z@E%U|2}~2_%o*T@ngwknjmLOMO&pclASv&_*?QP_HZbn@zocxxo_{^p^z7#92S1zR zV)5Rdwav3hu?-C`ea{N;S(x$q?0 z%C)3K5lIL> ze`I;@c!xeZ0|PcM6lzmog0{BeJB@a*@<%^stLv8^zZ14S8yQ_x00*@urP!!B`CBba z>44EqWIWO5p{|$6fEsGL@4u-51tpH6a9 zn&E|3cT{1veBylC;+BnYkXIp>NaLzH0n-IEHK;ChSLQW2tJCG{Jb5pN;e{_ik@7$c z5|HC)j070COQ!=tY6jpb6U1qvS)dS~Y1*U$hP|i}WK-WPDI=~yVu>NON3HPI@5g^v zeM%Jwu)dk_FI#9}_2Inj+$Xe7w8Wu5EDGdfV&MHo)1v{Pt%N*A0J?}F7DCO<&8^_D z;@Ue7AiafA<2XbS@|%9c2`@dj>~%+WPGoM*xk;xij>p zD8DlyI(UOO8AC?%CZyiq{|U84O^b3jyZ_>>xmo^Rtg!di)VlZL(dGTklLQ!yO3nYm z^rBvBNqPgq2GIB@NE6pUupmkV@frsN)}m@PDGqr1271wGY9~;Ln??FgbZ1I3*>x;s zgT$yo(8@F^QTaJE_Eo@<=bk0(ahp%V)A_%n`axB<`7Ue-q`%OE(YlW;4Do)`hU6># z9BP=mx4$ZafY@s_^`xgXDun@j6`%Ptz4cCZhl{KRW=A#4Sl+!0|0DYAlRlcP3V1O3 zI;ZB#xmWBVWMmTFd~<14P((x%Vv~RvESUy47~Zte^KNxzd^#RFp2$CIUYj-?;53lh z2oY$ak#16LnOUKjyyuqv(g}bMSppiTai01&hcaSqj5^OEWuI9_E1zbi`25^6!dCsV z#mVHw9x)*`=(3m(%%JJCKL#f-P#ouuYN@mTK8pr@3sf=M;gXb^a$#Dd>uwBTMFLz==xo-SB28IQ&Tf#V+X!MPu5lKZ%@x19znd~wD*bhA%N39ZRDw73B+ka^JDLghQoF(0JH<2H^W(bpgpK_0bD zqM@tuwqv()l>h$v2zfq9VGyV{7G1;Vb^tTcQD}x7@l~Hv55hMJ1jast#K8ZIv*4FJ zW+vRfJz@E3GCj`p(71BLp5>naTlm%OX{G5;%f2EtIR@7$uKJ1sRQmGi!4TwOEpEkb zjxNv8tdwfpX(9aiN;yugdVHZ;g}xz=gjPxq)SMJ#WcMKcOIP>d)NV@3DadRz4f&47 zpn%qx9YQA5Ar-T9#=LZ_ZDIld|7f=}Z~XqwuNhapSYc>ip@DXnmi?>E#TPHlaA0tY z;dd*5v6(dA01gHgAm$l%DP`7SOnETC?FCk*@geS^h4Jehp7`LS!Cb-l|*yWbky$n$^0^I>n=}pjlj)LQ@Rt zUpWUoDb473AU6~OnGEA)euPhVerxxG+!z}5@)*yk6D9Fe=WLjXBMFY`|6cI0t|a_+ zAoVB&FdPwBwEw>nSg&-xZOFTwLp{Hcj+Fqs6W^ILymE5P2M0Btlw3SRgy|WJz%K0y zT`j8bI=Q(24IWY+T+V|T44Yx8VvL`MH!0*XT@k{nMvUj*(Inmn@gUTV?r*O?ml-5` z%Dp?UZDrS4?y8fF3N7zSxFX8In-wh2^g#>$_{zT zRgho&%A!g=izykz0%!>R;Sk6*;FVA^UxIicnshlEjYKWZ!ZS+GF%w!cYv{AWK--ge z%{@XLukHQdc$-*385Vp`LbuEGMA;3QT!z)ZIW#hXCc}VR>!7(N>Do)e%EqT}Q5BE> z8V$hCbNT_a<=J(laG2Ycz6Rr*dZ{-4;x?Kl4S_gCzp5aMrs*$4&c{5cprJJt8a0oK zyDMz$Bl?xe-7n<**k9JQ(g>?>N32rvIO3+{*URILV1}u?4kjh;maLlN29PN);2LcB zRxLoKhgWT9yC?zqK~G&9-U|l^l#Uk*8~znJQVk1 zusK|F^hVGgcb?YjbCLzJ={_GqEbV`Hf~_x?`MVYb6Kd$24lPu~sgOcKErO8CWa9P-!0(MEEsy`{*U@v|WAIPByv7o1c;;7x&N>^T>}~|S#Hlo_a*v{$h|XvcMn%ndg8~z- z;jg;HzAe8+Ai9GJljbLs<_BRdT4iMO1=sQV4T!wUgcdx9RSRDI6%~E|Dx$)UFkJ(L z1lu|SHyiMP$BxVy8M`>5Xz{7zCP+;G%a%T6{yPTChbi4Hoa>VdTNsR-Vj_X-0^~~b zvib&*m?Z6zKL5OtSQ}156t-R+C$IdIL|eacFW`zc?sG(Oz0Y8F{m=CuvMDxAI%hRCYoO1Metut= zbFLx75mF~WjbrR}zWo#4MEOIcGV>jW)e}7Mcnq${MqC6HoeGB zrD)Iwh7XUDMUVl-N|I9UzF4xd50teYzgOxqa8-!Uk3SVvooSpX-Z?y6#>fPJ$8n6ik%*?j0?fgL2Re0L%ZD z5N;W_Jd$*Lr{m)OLR$ic=_Btc^Iv2Y(y7^{toy)o1IdL!j+NK$6q=6{&gQ8uxA@c9lO=898IqI5A#b!^4 zp$B>jTAkp4ibCkw?p?M*hy9=5+>x506Z2U*K zKU{SS7HQ(M3GKXeFu&)jv9&gWzwe<(r~Ji>?V5)&=B*Veh#vr6#<1g|iqGF`e+2Ss zV?|*d7yN{N5Y>Llq(A4Deo`UCelKIStb}#4hN#l&tXioL5f(%AKM7n9z2FX<^MC5jPnsPwW~zXcMt~^}~{NCMHWK@OZq~SZHoFAKD9s?vZU6L;od$ zcA`XzAEo42sR3A~9KfiX?EBE6M!`$0kYt_erNfW#QyG0iZT;XXg%M;ip7l;{;EQW- z`(VJ0`1kFg;qFMO9Y0tzH5F?&v%V8=Y!_Dl+DtW=sB-+T=c@fjqiv_c+zR#Tn=+#59Gv;L9H^_fGSUqC zdJFMf&hq$2*a7a%%>`S?A<(RNssmgT8i)HNSLAl5LUQsWC~)`Fht3p~mk`o;8GIHL zo_ujJynv>-;dGtvsCmFMM7(hLAPlr|D9Y(MJQw@UU~U;&gLKg|wBLS41pIdgz1zP- zr+RzqVxr*!XrFwP=)v-yJ&=838ofZ*q}Wy2h*UPyJf?zl!&^3%FQmytq=Q!^ksFMe zLrQ3B4eAkOt_cbm;|6cE7i+hy=U*emu$yciy3zOfOf#L6qCXQs9nf3`sFFmyD9Q55 zy+v0-Fv?x@j_pLf#VJMu%@@tel4n^7Pb)xnYpanw@8n}}%wBDPRZtiwCeU#F(Pc22Z)hhv0G6CVkl5@iq6Yuf(E1j352Y4RVOxL zV3VT*p8#orx;l(%jSrrA-TX-cH1EdNy1M4&N5KdnUtmz-F7bPD!|vbJyfO&cUXkiYlsn zrw3UH&DRb(#u0Q06JD->Lp_`wAFW3=_s@a;(u>4i&ylEWm#ljPO8$&3zC=lg;L+XD zN(BNq{NVF%pm+tx-}!5DhCCot0;D;*gqC$B%jI)XscpB8wyUtcn@1-yJWn$jC{2tE zi%#F?$|nMg_vP;Ml?N6NtZ}F^@UVzmhmL}U-$a*`3bVvu&Jh$d;(ZSRUUtds^=$8Z zbwu@qDa=pkvB@C>IY25XC@Hu0w)7!Wvo$kf^IOM%lLtoylYidx?}PMuTA`U2JmWhF zAODGGPTa>9$zqBQz-*#v5)btNLsWAVa=Q_WS(Q~qv`hIo?HwOf|28Z%%L!DF)bgjk z2s&B5-iA{%pE7oYlj?nrfm&_UP9}Iaa^lPY5u`RQHT|{|SYOx1*8sryU?-JvbGvC; z1-MGFR_I}#z2a#g|702vT|w1;J!0$EKHPjM6F?dMsJHdWCaU7Rl96T8! z(7nFO{|_yu9m~-x@@>w5mz>vR?9({PgVOv*iGS^}oOOR=)S-HTiE3`*aCN37M|Pkr zzu}izspBCj3<2)IV=k}n%)Jy(=Jz6uf-h5v{6YE0V%k{|fkbExG6u<)7WJ*l=4c>K zRW4AZ`jLl^t>CPMsU0TM*U^BjD=xncxLm3}fy|=RPhIaf{WYs5P%Hk!4%~J&D(!Nj2yT0+aC@z>~e&!#UZHSvGe%0odRUpaq*UwSqJ;www zq?7fCR4)8pCI+Rjf7;fR-K#IzJSwRrOQ%!kv~}$Yt~2!4<~;T6b=SL3gNpE*9a)Y0 z%1ketux1eIYntE}sJG1-sQJsACG!!azd?nsDnOV)BJAXq$5WFk{tc$;;IQX8@{>)s zjcbP&L(#iFr8jDVz0f0f;8UUvsXF!Q`c}~FC0fq4WS0_(_Y{@AK89HU)XjB04}hht z+rAw@jLumAe8PzhTM**I7htB`_n)wQfAEeMepfVT&O1^IB%=;BpMT)*xL<@QfdLtY z@Q4BKM01;aAW4|>Lh7iZ;V}#Oobg(3?Iwd2E&iU^dTk!gEvl4TE+6->2r2)n4hb?) zBg22k{L(NmA_c4hwhZIp&`KM3#^QHJy{6Rubvn1UPv0Hc4ErycU^&zgxG#_fBj#c* zZst58?ayfE_R8_&r-cz` z)-gh7^*;_6R3((!#9v-wLgq}IxZ!5TJZ6rRePVh4s%4~he>Et@>6##lh`Vm`0oW4F zHuPE{n)b=K^K#26cZFw>y&Cd4p*hZ?_TZ(M^x~s@`}r9yy-Cx!M(IF!L~k(7$?TU* z;%?JxA$TWWrVjJ$YTn!seahI})0SSDG(gT5P)T~uJ_EDhbC27^h);k?@uEK0Tr-V$ zB2Q-}1%WYlFg}4g$J|_aGs!$5^_OKrUh6M6%F1fS4!`WlgiUV<*Ni6fPZ{^G?GziE zj)snf9?I5It?ntTc0<4+Qowt3&|mzsWza(x>E+KMNTgBkLb|;LYu$|8$J#c?aO}~# zA%BUQ{<~Ao5yhH0a$MI!$wlf^M%R)U#G?%_i*>|%yh6@0N|simEBlug{&&g}Ti$W3 zlDU2FkcE7J<$DD&TT7*hn)}+8UIle@$f?6K*uM;xZ}6Xrgysq=|NWex9hZAInfA=o zw9D7scGicEtHlNva^GWqbO0jN-(%&IwVmqp4qP7Jj`9AEeE%ur$v+-zBK5!(&Py+ax&07N~BV z`|lDhT8tu&S`8mO*6;l=zwVTJp^x7b&t*htc$%JRm?W9$XI`TB72z9|UsH;HZtG;? zVyeW(xpzD{W;GUhaZ@(PllAUCNV{rR%lv= zW3ucCl9)8$Ki;(zP{c{FdH5{6n29KsllKd{SLEuIH@?x;a)-FYFd*m84dN6Zj@hiF zh^ZCBwr$Jc#J$p20xWh!x6?!77at-8ZiyUOHNg3LYHKcd6}Ps8YY!{xFR1$N{4 zg|HewPS#6%cmnWc_VyhD35ORSsSf(4J@JG$(q-vn^vRShNQC%gwI>&wZ7N3HeY~$+ zw)G-*QPwp&pj?fz)FAR(uw~HpVfEHQm*@QI?6U_W?(A(wn3KPk6*j_}h)#Bo0-9|? ztytcEoTpk?cRFKG7cxhsS@7UFL08(T)RinGPlEfKTvMqGhT;;TAEi%8zlAm*mMGrh z-81ceoU_8){kbc?Bm2DP?-b!_lW;Fing(0SPJP4g=6{6M>4_O)_WQ$2a{s#VV{IOc zJ|9_3fbA@(hqiMT$n zur4Afp%>%UVr0{`5fjG2JfvgVG%dn_H_tTucU3ob5R z(vM=q29Kn^h@h}I z-+-D4?C`ZGUw0pTSfgwDkD30_+{fZ2@pYm>3nnS;Of}NC8e``x+5XYN1#=V;yw*qpz8HujD4~J&_ zwpAXj3I0&@>(La!m1(lM#N^G^1ZlohMt;b+K0o+dDPQIZ-eVT3YfQJxb5an2=Y$lY zyHS>Jbb}&{GS+`#5T6H@fAs_}+?wBvF>Qi(+Bfc31z8nP99K@pWE5#ry{wvg6#APA z!BM1h_{Qqvt2{E|6~GQ+O_=pFijpn1cM0;NJMLp_M}-ITkr+}IuZ6ofvM5l7ckD%B5Ej%!P&vciVeZ_7V-lCT6cx$; zG-ZMzZFIk}ldwrxP&8P8PPImzC_ecTmk90~r~JIWNi$XVDwRQhzq)K!Wll#NPwZ*a znjhkBr@n4Qw)(OO=??5~n=lRr1kF=koTt*tHQKCXma4yf%$HU}c4U58(jYMC!w&}G z^7%CE0}mCJ#;e&W=X+nYzB&?l-zTH3ldj*T!M|GNXC*Drxu-~VX<^8uA~|AF*1}I0 z9^bFKk;Vd8gD_dwnEGzc2U>DRdwR=PG^m?f1%ncrM5>uGkHr(D6fn`&7%G`vF1qWR zM8t+}y~}E(T-^6<=3n~@3Ep6Xx-`=w{(98sY_Fa!Qqvnk5+#o(#*l9o9?9?26J+rD zDoOMqxpihM_a24}ul@KAF#%DEMU92YbNK`O4#{X!ACBB2t^xh`KO`5rUYYXHP}zyk z6Ld)4r;qtK%EsMPD@`+Wxp(Fh3mw_iX9Hh*?%}& z<&z-WKb&JUXHiWKTjHsHP2K>zW~pTK=|awd1O#fth2PPnxibu!v6AS?oSn^NVYDPS zry%KDwfmXQMn!4$o?b6Uan+?G$(pa71jF;>*L4SR>-1yq?sJ4O5%Oxw9+F?YZX6g4 z`|_jD@6^$75fVqndR)hgFspJ7XZdEY{WdRR-V`L^ye>k@y+qc%!?t~RK@i6$pl4Me z;`%~s_8{QAoedpFF>`Hr`c8plOw?EHvRivN`Z)EnIq!iR{fX7YatRvYIuU=wyo;?0 zlhrD84Q{~NVKRq``Go8(-Q-@6KK#=9>6pZa^1SPJilLZ@+F*mIMNyA84fmou_g?%i z8(~Q6cpG?ogDWUOBiAw(YBdgbf1DwD?!`(LzqZ+=DFj>c1|D64!3 zA2RgI8GhBeU@Yvk?CcN_j=6czg(1DdljKjxGifw|$)fLm`C^SAft2F6t)uDrGkP%w zhD=H=Nr7&AV=`ax=!HvX8-*^e$m#q4;E=sbE4Zw98qAE*m-S)@663_s#khf2$vo!b zxBp>{Otp}1FZg%aF{Zb_(5Yr@g-gc_g`7#Pbje)TAK0 zKkF|yUmFtF8sekFY1T+e$ToFzs+FsW@?U%zq!?#KsBg73nzFmU|LpG7*|mK2hYp1@ z_Z1^ppgEX*(?}aHvBYB1Ghp0WM7#G*G|RDb;jG!W)xE6sr@Qt6AsX-mY&l%^z5COl z+K;^(Gx5~QyT2K4`a(C+Tit{i=f=wXa(w4S6>5a7qwjlmzy$AXkye%wWx85?mxl_~ zg%YqQ*c&e(k zm&rS68D;Hbky^!;dA;+g$tsa?&}y}W7;df}J-GMjbZ!*XF7z>e9WN8BHLKmDTP zUF}%BmkHJ=9|uK&>3Y$vJ^NWXV)YM9)2&J7g}psj&_;$HYj!qO$b5D2N%b*V+0|8(n6DNn4sUix^R1aoj7@wpUkGyL`WHKiHg|eWOPy9j;9w^JE!bXO-X0*ahd; z@Q-+0iMeBY$feD(PhzgJazinutvUjfEBY*5Npeeh|66X&79&cy*#lQ4Urgp?J73}T z++F5$bRQKgAgC-F3aHnhTxfpRYxaYXRr*g;?a+wpHMZ{7SEhL%>D3>pi11_CH@N(S z8ZKmYv1eZvTnyPe`+RXs(VPoU&EA;5(lbK;sa3f9TRPh>;$#E(=>qOrHGTwHcB0*F zbiUbqW6-3#_!D{+4QOLg@?MEc_b-V zPvqd+Du4?SpSe41R=0-f{3wI}3ZvJZRBX0ZG&S&Zo#?nK@h z1HIDJcn%V@w&$f-&u2Y;T635^m)!TOS)_wW<8p*AZu^eox5gRzwq9wOjAN4L3;n~P ztCy_&92fNy>>{tt8WSOKc4T<$EtoVBe@MexH4(G$Q^%`6P;zc6=v&-vH2CJPZ$;?T z#TxE-&%%LH(-BS^7$ruEh1oik3ZYTTEkX)aD8ezY+KeqbdGe9-s2~vq z`?%1u#uwj{zuv_?Hx*YH(~TU*=HZ0oi8U)Rdw8Zkx_{-z2A9A!d(Rga@GGwwXYad1 zj}KGNH}6c{r*HheOv!#s&k?@S?02sZTADVA2RyMv4VG>eenLk}@(jO(Pv^gZMSz4EG#f=)dWOiIn!A&SKg6OszQ}tX z-A@SpJwtMd5N4D2ubIU*Kk_;!yu0T3#Ua-+;x!)rZpQip1)9#?|EIAtfu^$U`uLGT zrSfFvm@+?^$rKqQvj!#e6qzzs=FDEhF^|cdRFWi-dFVKD3=bh*i9i*(^tOx=pkSq#iY*spwPP+8l6~hdSIewKzP( z$+&|Q-}+705YzAL=k>f7$A7W9^pN!~Yv@65 zOJnj6Y3;lBuHTGnnXAmRJR5QAz!{S!yV13mk>cz_9QLWU>#{OID zbc`%LW>GSp<`q+aB+$TBC+C)?{?h$r^nl*``6bh z)u%tax`b2i$S@_}T5oUCdDiM#ukl_kz@&g@QZ|BZwqY9*j-u3`|2RbJ%}O2Nxbz}y zRzaW0(b!kY+0w)`l@?)`noxVuulR|m43x3MrKnZ@x>09C1GHgcaWHXid zw5)SR-Ogj|_4J?%yqYiySbO?ZKvo*zu0^NbjPpMy)O-Wf<+)TY`gy+`4f1|5CcHSF zMy%5#`xx{XEu2V1k1X zx?wc0M2=_3^owU18gwLu-bDCQL#@FcUlMwj)Y z5_K5G2MJNiBqo%YMp`gIv7lRh(^TqI;9sPknX@NYrM?aZ7Q||n^M@$LT6Ef4r5sf1 zw^a-BH7vH18)|+r0>zQ#Dygxo<(2FrPpqH` z#RP>J6{qOmm-bPLGvi`~(95Iu^5j0~_rL8ZzBu)`@yTIpr8p5qeun2Cy3IHEN?!Ds zUmrQq(qEUOm-jW>l$`jQrP=vr(Eurn?It;?je@&LPEVs+zgS(*X$BDTYccV1xefhc zed)W$--w+GPx!r`WSP6p(%gc28Qur>{(Gu%i1G`=k1S7JE* z;<&1k!8H-q>kK^)OC%-0dd{(Za(J{fG3Fm}Mx`S&iuEP2`jY53N(QG@6GM*r^JU+i z`9~!4Ge#Ts>oc|vs53&E%fqJuRp2vL6VppBtRo4XKh)`e;O5h3e6=px9h7Haq>Jn9 zTxpU%V1k}eGHuc2uBE)3h%4-yxekMTdBRGU8KgK-mxCv5z74~l+oSz8_vZFGvm%qd zVzk*m^b zt{-GX=maEEq*;ZQzrO++Qz%(~ac{RPIT8n_5TYK(E@uZ4Sq~pQYJ306rwWvme0_cI zH|~^IHn)R{kS732ra>Cgw8n+;a)nvc3?V6LIgcLgBSAD#vU4z)KC5FIAMe$B>fKbv z6)Or1O?YT=@rf-Evmuluol%@31HqF1Ou@17m+ont4M3Nb1SmZMyLJQ^)s7!28KB7` z9*Ai3^gjdpq*K>o+}_FOW^DD8PXK6{EvO<5+AH^UMw(r&dWF zYAm$Bc06z8EZWw)G>7h>&6O+6c2z7te*8$~>?aa6%+1Za3!GhD*#}^wYeXhMR(>ge z_;7B}BOh)Zk3)jNKlXb*+4_;y5=s1&+I;u!-N9gZi3F>7WqJDc_4V~d>kDWE1_ln! zEG{lS8*>xB)9F}^n+rftCF4hP#xCeySd0m19)J(*NbOM%pFYjxq~A|5JUsmH$rJqz z>5PmFop+R~CMLs$@AmGTJ_CI*%oJglyYU)m^v37Uhk@J#3D0aD*+1I>iei))B;tkW z8i;9yd1l)|WdR^9KT;I4C(MkWXrB<+uJ3U^? z_INA0?Rj~52+=k$G7=5?t)zn8t+JuHfzeT#{O_WEVgSej__bKbYPmJ3ion?cBc7K* z!^a*t@EsvWNd!vF-}?0&iKfj8DZ`%~wg5}@MOfdsqMM$Kgd;wjhN-SP9og{K)^HKFBbsphaf}`D=P3ni^IThYs;UYC^rLC#c&lr zeR{O^y|>=r%^ap`TYJ6=7=HbFq|#bEm@6J{s-{LU{`{IA+jp0suXA&Nr2<+Zt9^n( zp5X&yp;17`aa;O;d<#|R;#jqyWvzmkpAx5RFxmIAi3uJNC|`ohcCz5zBywfl?SS<> zQP_VtycH))Ez%YN;&&G3j6WwV2>|vS^mCfYC4Sn6F%@CLv=(W^z(Y-)mInc624-fb zAndzJ>m)c61z}kXocZoLK?Q{-81l^l#-FWn=M2(N{IWqN2fV1M;m7x0m$6%(#}N`JtnBWy1%6(uHa%ov*CE9rkjGe<#;tKQ?9g{zB8J3tJLO-v5dnB{#N ze`N>lVqDxIgu}#yZv31@giR!xR&`^dUS@J)eYLh_`^fjkpGQ9guUV#NWRSX2c>U&z zVvLQARlRuaPaKb(N<94yV^3Sz^vkT?V>V7zuhls{FYic>zHH&o=S@uw_k}XBlTYU^fN*9TH0W_$J4-P_;^Ks)J6rZB5+I%` zCT`r5R!~be*IhNjMh47})HNqBklGR*O?An{L}yqf)J~Q`7xVVq|Jp*%M*l3S1S3!?Cgxt`Rdy5G^`Wc(w0W!rerY*5pZuGMQqQ ziZ-u7^R5iY=KC;0qM}i~j(Tyq=>K5qyNhA@{qK%|w;i`gz zw+maiz&FI2v>xEy>f}4g2`++r`5ryz;=l9hy-JBE(t%~KuAx(xqD7r$kW#QlqptD) zAT4)z0k**o(`0nl-09T2vWwAZgnuXRZ)oo9Zcd)JvO0>>qAVYd`$Wu|LGER}^Ml!K zqMi{;2%C`y5lBkRUqeHYr@z%v3Zxwb3Lct))>oh+-egtmz0S3}%mp)q!rE+Fx7Q|< zJmv4@AA<~um)mIV2psWx_4p!+QTagYdk?pN$xmrdmK_?SqN=JtAZPPvT7_l+1iOyM z+CaMtx$0}s@;dm+B5`u(SFPzQZ+=iLqbj{{5Ca))v{?nf_)dH7Z23b&tPHC3en7o@ zyWs`zm%>pUqVETI+kxv0F_r0zI^4}m3mMwBR4;P zejLym1_lNtWPci-j~C7#NT!n_y>XC&7)3($PRq`!cq343{kE0~RUVVg>F)xYtPsN) z;&NZ;thcwf*5)mEhctw8(Kj?$g6)^VQp5qw5Bi~#o}NAh@e$3L5@FJ-zlHF~pmd)C zb7&*lB<5U!2FwtqiUBqs=GpDYEcOG$T(f;};g(-UocGK#%pjwRIA338x?<)AaGF zUa2Q}vOqd0?&9jY3@~t1;rYRgn(Mnt~L=Y+K}aEryfS{E^AF(=7HP6LM-aJXh`_e=sbg2lBC3y+;%jdI=-KD53wa&XpMo uMK=0muiE}^tNug311EbU@ju+RXP26B*o)s$U3vopKRRa(HJ_^6g#Qaf4RP`S literal 0 HcmV?d00001 diff --git a/vocab.json b/vocab.json new file mode 100644 index 0000000..6c49fc6 --- /dev/null +++ b/vocab.json @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:ca10d7e9fb3ed18575dd1e277a2579c16d108e32f27439684afa0e10b1440910 +size 2776833