164 lines
4.0 KiB
Markdown
164 lines
4.0 KiB
Markdown
---
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license: apache-2.0
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tags:
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- axolotl
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- generated_from_trainer
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base_model: mistralai/Mistral-7B-v0.1
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model-index:
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- name: einstein-v2-test-model
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results: []
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---
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# Version 2 of [Weyaxi/Einstein-7B](https://hf.co/Weyaxi/Einstein-7B)
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
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<details><summary>See axolotl config</summary>
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axolotl version: `0.4.0`
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```yaml
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base_model: mistralai/Mistral-7B-v0.1
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model_type: MistralForCausalLM
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tokenizer_type: LlamaTokenizer
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is_mistral_derived_model: true
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load_in_8bit: false
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load_in_4bit: false
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strict: false
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datasets:
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- path: merged_all.json
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ds_type: json
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type: alpaca
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conversation: chatml
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dataset_prepared_path: last_run_prepared
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val_set_size: 0.005
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output_dir: ./einstein-v2-test-model
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sequence_len: 8192
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sample_packing: true
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pad_to_sequence_len: true
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eval_sample_packing: false
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wandb_project: huggingface
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wandb_entity:
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wandb_watch:
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wandb_name:
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wandb_log_model:
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hub_model_id: Weyaxi/einstein-v2-test-model
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save_safetensors: true
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gradient_accumulation_steps: 4
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micro_batch_size: 1
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num_epochs: 1
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optimizer: adamw_bnb_8bit
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lr_scheduler: cosine
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learning_rate: 0.000005
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train_on_inputs: false
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group_by_length: false
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bf16: true
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fp16: false
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tf32: false
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gradient_checkpointing: true
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early_stopping_patience:
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resume_from_checkpoint:
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local_rank:
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logging_steps: 1
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xformers_attention:
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flash_attention: true
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warmup_steps: 10
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evals_per_epoch: 4
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eval_table_size:
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eval_table_max_new_tokens: 128
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saves_per_epoch: 2
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debug:
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deepspeed: zero3_bf16.json
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weight_decay: 0.0
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fsdp:
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fsdp_config:
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special_tokens:
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bos_token: "<s>"
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eos_token: "<|im_end|>"
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unk_token: "<unk>"
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tokens:
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- "<|im_start|>"
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```
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</details><br>
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# einstein-v2-test-model
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This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.3838
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-06
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- train_batch_size: 1
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- eval_batch_size: 1
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 8
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 32
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- total_eval_batch_size: 8
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 10
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- num_epochs: 1
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 1.0376 | 0.0 | 1 | 1.9459 |
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| 0.5117 | 0.25 | 59 | 1.4740 |
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| 0.5293 | 0.5 | 118 | 1.4116 |
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| 0.5243 | 0.76 | 177 | 1.3838 |
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### Framework versions
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- Transformers 4.38.0.dev0
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- Pytorch 2.1.2+cu118
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- Datasets 2.16.1
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- Tokenizers 0.15.0
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Weyaxi__Einstein-v2-7B)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |63.48|
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|AI2 Reasoning Challenge (25-Shot)|62.37|
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|HellaSwag (10-Shot) |83.46|
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|MMLU (5-Shot) |62.08|
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|TruthfulQA (0-shot) |50.52|
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|Winogrande (5-shot) |79.32|
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|GSM8k (5-shot) |43.14|
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