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--- |
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base_model: mistralai/Mistral-7B-Instruct-v0.2 |
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library_name: peft |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: finetune/outputs/climate |
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results: [] |
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--- |
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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: `0.4.1` |
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```yaml |
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base_model: mistralai/Mistral-7B-Instruct-v0.2 |
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model_type: AutoModelForCausalLM |
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tokenizer_type: AutoTokenizer |
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load_in_8bit: false |
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load_in_4bit: true |
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strict: false |
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chat_template: chatml |
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datasets: |
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- path: Howard881010/climate |
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type: alpaca |
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train_on_split: train |
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dataset_prepared_path: |
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val_set_size: 0.05 |
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output_dir: ./finetune/outputs/climate |
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adapter: qlora |
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lora_model_dir: |
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sequence_len: 2048 |
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sample_packing: false |
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pad_to_sequence_len: true |
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lora_r: 32 |
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lora_alpha: 16 |
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lora_dropout: 0.05 |
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lora_target_modules: |
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lora_target_linear: true |
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lora_fan_in_fan_out: |
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wandb_project: finetune |
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wandb_entity: |
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wandb_watch: |
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wandb_name: climate |
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wandb_log_model: |
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gradient_accumulation_steps: 2 |
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micro_batch_size: 1 |
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num_epochs: 10 |
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optimizer: paged_adamw_32bit |
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lr_scheduler: cosine |
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learning_rate: 0.0002 |
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train_on_inputs: false |
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group_by_length: false |
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bf16: auto |
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fp16: |
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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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eval_sample_packing: False |
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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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saves_per_epoch: 1 |
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debug: |
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deepspeed: |
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weight_decay: 0.0 |
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fsdp: |
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fsdp_config: |
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# For finetune |
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seed: 42 |
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``` |
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</details><br> |
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://rosewandb.ucsd.edu/cht028/finetune/runs/8a5o02qn) |
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# finetune/outputs/climate |
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This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0009 |
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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: 0.0002 |
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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: 2 |
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- total_train_batch_size: 16 |
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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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 1.7628 | 0.0056 | 1 | 1.9544 | |
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| 1.1905 | 0.2542 | 45 | 1.2650 | |
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| 1.0583 | 0.5085 | 90 | 1.1289 | |
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| 0.9094 | 0.7627 | 135 | 0.9717 | |
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| 0.6033 | 1.0169 | 180 | 0.7865 | |
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| 0.6043 | 1.2712 | 225 | 0.6347 | |
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| 0.3525 | 1.5254 | 270 | 0.4456 | |
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| 0.1879 | 1.7797 | 315 | 0.2918 | |
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| 0.1367 | 2.0339 | 360 | 0.1608 | |
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| 0.1627 | 2.2881 | 405 | 0.1098 | |
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| 0.1465 | 2.5424 | 450 | 0.0722 | |
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| 0.1019 | 2.7966 | 495 | 0.0458 | |
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| 0.161 | 3.0508 | 540 | 0.0354 | |
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| 0.0597 | 3.3051 | 585 | 0.0189 | |
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| 0.1038 | 3.5593 | 630 | 0.0130 | |
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| 0.0754 | 3.8136 | 675 | 0.0078 | |
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| 0.0632 | 4.0678 | 720 | 0.0051 | |
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| 0.0364 | 4.3220 | 765 | 0.0032 | |
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| 0.1342 | 4.5763 | 810 | 0.0019 | |
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| 0.0776 | 4.8305 | 855 | 0.0014 | |
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| 0.0337 | 5.0847 | 900 | 0.0012 | |
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| 0.0591 | 5.3390 | 945 | 0.0011 | |
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| 0.0171 | 5.5932 | 990 | 0.0010 | |
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| 0.0732 | 5.8475 | 1035 | 0.0010 | |
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| 0.0538 | 6.1017 | 1080 | 0.0010 | |
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| 0.0234 | 6.3559 | 1125 | 0.0010 | |
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| 0.1259 | 6.6102 | 1170 | 0.0009 | |
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| 0.1216 | 6.8644 | 1215 | 0.0009 | |
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| 0.0687 | 7.1186 | 1260 | 0.0009 | |
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| 0.1172 | 7.3729 | 1305 | 0.0009 | |
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| 0.1007 | 7.6271 | 1350 | 0.0009 | |
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| 0.1372 | 7.8814 | 1395 | 0.0009 | |
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| 0.0925 | 8.1356 | 1440 | 0.0009 | |
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| 0.0342 | 8.3898 | 1485 | 0.0009 | |
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| 0.0688 | 8.6441 | 1530 | 0.0009 | |
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| 0.0576 | 8.8983 | 1575 | 0.0009 | |
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| 0.0575 | 9.1525 | 1620 | 0.0009 | |
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| 0.0707 | 9.4068 | 1665 | 0.0009 | |
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| 0.1519 | 9.6610 | 1710 | 0.0009 | |
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| 0.0666 | 9.9153 | 1755 | 0.0009 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.43.1 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
