| --- |
| library_name: peft |
| tags: |
| - generated_from_trainer |
| datasets: |
| - /workspace/axolotl/datasets/chemistry_data.csv |
| base_model: /workspace/axolotl/llama-8B |
| model-index: |
| - name: root/outputs/fine_tuned_model |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) |
| <details><summary>See axolotl config</summary> |
|
|
| axolotl version: `0.6.0` |
| ```yaml |
| base_model: /workspace/axolotl/llama-8B |
| model_type: AutoModelForCausalLM |
| tokenizer_type: AutoTokenizer |
| load_in_8bit: false |
| load_in_4bit: true |
| strict: false |
| datasets: |
| - path: /workspace/axolotl/datasets/chemistry_data.csv |
| type: alpaca |
| format: csv |
| prompt_template: '### Instruction: {instruction} |
| |
| ### Input: {input} |
| |
| ### Response: {output}' |
| dataset_prepared_path: null |
| val_set_size: 0.1 |
| output_dir: /root/outputs/fine_tuned_model |
| adapter: qlora |
| lora_model_dir: null |
| sequence_len: 2048 |
| sample_packing: true |
| eval_sample_packing: false |
| pad_to_sequence_len: true |
| lora_r: 16 |
| lora_alpha: 8 |
| lora_dropout: 0.05 |
| lora_target_modules: null |
| lora_target_linear: true |
| lora_fan_in_fan_out: null |
| wandb_project: null |
| wandb_entity: null |
| wandb_watch: null |
| wandb_name: null |
| wandb_log_model: null |
| gradient_accumulation_steps: 4 |
| micro_batch_size: 1 |
| num_epochs: 10 |
| max_steps: 10000000 |
| optimizer: paged_adamw_32bit |
| lr_scheduler: cosine |
| learning_rate: 0.0002 |
| train_on_inputs: false |
| group_by_length: false |
| bf16: auto |
| fp16: null |
| tf32: false |
| gradient_checkpointing: true |
| early_stopping_patience: 3 |
| save_strategy: steps |
| save_steps: 20 |
| evaluation_strategy: steps |
| eval_steps: 20 |
| load_best_model_at_end: true |
| save_total_limit: 3 |
| metric_for_best_model: loss |
| greater_is_better: false |
| resume_from_checkpoint: null |
| local_rank: null |
| logging_steps: 1 |
| xformers_attention: null |
| flash_attention: true |
| warmup_steps: 10 |
| debug: null |
| deepspeed: null |
| weight_decay: 0.0 |
| fsdp: null |
| fsdp_config: null |
| special_tokens: |
| pad_token: <|end_of_text|> |
| mlflow_tracking_uri: https://mlflow-dev.qpiai-pro.tech |
| mlflow_experiment_name: llama-8B-chemistry |
| hf_mlflow_log_artifacts: 'true' |
| local_files_only: true |
|
|
| ``` |
|
|
| </details><br> |
|
|
| |
|
|
| This model was trained from scratch on the /workspace/axolotl/datasets/chemistry_data.csv dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.9859 |
|
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| More information needed |
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| More information needed |
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| More information needed |
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| The following hyperparameters were used during training: |
| - learning_rate: 0.0002 |
| - train_batch_size: 1 |
| - eval_batch_size: 1 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 4 |
| - optimizer: Use OptimizerNames.PAGED_ADAMW with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_steps: 10 |
| - training_steps: 9890 |
|
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| |
|
|
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:------:|:----:|:---------------:| |
| | 2.2045 | 0.0010 | 1 | 2.3167 | |
| | 2.1303 | 0.0202 | 20 | 2.0805 | |
| | 1.9063 | 0.0404 | 40 | 2.0458 | |
| | 2.0275 | 0.0606 | 60 | 2.0337 | |
| | 2.1621 | 0.0807 | 80 | 2.0254 | |
| | 1.8073 | 0.1009 | 100 | 2.0203 | |
| | 2.1245 | 0.1211 | 120 | 2.0177 | |
| | 1.9644 | 0.1413 | 140 | 2.0137 | |
| | 1.9735 | 0.1615 | 160 | 2.0123 | |
| | 2.2691 | 0.1817 | 180 | 2.0095 | |
| | 1.9491 | 0.2019 | 200 | 2.0075 | |
| | 2.0258 | 0.2221 | 220 | 2.0057 | |
| | 1.7861 | 0.2422 | 240 | 2.0050 | |
| | 1.9007 | 0.2624 | 260 | 2.0006 | |
| | 1.9219 | 0.2826 | 280 | 2.0009 | |
| | 2.0698 | 0.3028 | 300 | 1.9978 | |
| | 1.6277 | 0.3230 | 320 | 1.9976 | |
| | 1.7718 | 0.3432 | 340 | 1.9964 | |
| | 1.8223 | 0.3634 | 360 | 1.9958 | |
| | 2.1197 | 0.3835 | 380 | 1.9953 | |
| | 2.1519 | 0.4037 | 400 | 1.9969 | |
| | 2.0659 | 0.4239 | 420 | 1.9952 | |
| | 1.7126 | 0.4441 | 440 | 1.9947 | |
| | 2.1095 | 0.4643 | 460 | 1.9924 | |
| | 1.6791 | 0.4845 | 480 | 1.9918 | |
| | 1.9868 | 0.5047 | 500 | 1.9908 | |
| | 1.9909 | 0.5249 | 520 | 1.9899 | |
| | 2.2069 | 0.5450 | 540 | 1.9917 | |
| | 2.0763 | 0.5652 | 560 | 1.9895 | |
| | 1.9251 | 0.5854 | 580 | 1.9891 | |
| | 1.982 | 0.6056 | 600 | 1.9879 | |
| | 2.054 | 0.6258 | 620 | 1.9875 | |
| | 1.7292 | 0.6460 | 640 | 1.9875 | |
| | 1.7901 | 0.6662 | 660 | 1.9891 | |
| | 1.9179 | 0.6863 | 680 | 1.9868 | |
| | 1.6178 | 0.7065 | 700 | 1.9874 | |
| | 1.7637 | 0.7267 | 720 | 1.9859 | |
| | 1.6946 | 0.7469 | 740 | 1.9868 | |
| | 1.8821 | 0.7671 | 760 | 1.9862 | |
| | 2.1346 | 0.7873 | 780 | 1.9859 | |
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|
| - PEFT 0.14.0 |
| - Transformers 4.47.0 |
| - Pytorch 2.3.1+cu121 |
| - Datasets 3.1.0 |
| - Tokenizers 0.21.0 |
