| --- |
| library_name: peft |
| license: apache-2.0 |
| base_model: TheBloke/Mistral-7B-Instruct-v0.2-GPTQ |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: shawgpt-ft |
| 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. --> |
|
|
| # shawgpt-ft |
|
|
| This model is a fine-tuned version of [TheBloke/Mistral-7B-Instruct-v0.2-GPTQ](https://huggingface.co/TheBloke/Mistral-7B-Instruct-v0.2-GPTQ) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.7413 |
|
|
| ## 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: 0.0002 |
| - train_batch_size: 4 |
| - eval_batch_size: 4 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 16 |
| - optimizer: Use paged_adamw_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 2 |
| - num_epochs: 10 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:------:|:----:|:---------------:| |
| | 4.5918 | 0.9231 | 3 | 3.9644 | |
| | 4.0441 | 1.8462 | 6 | 3.4429 | |
| | 3.4677 | 2.7692 | 9 | 2.9817 | |
| | 2.2518 | 4.0 | 13 | 2.5502 | |
| | 2.6491 | 4.9231 | 16 | 2.2852 | |
| | 2.3093 | 5.8462 | 19 | 2.0790 | |
| | 2.0483 | 6.7692 | 22 | 1.9019 | |
| | 1.429 | 8.0 | 26 | 1.7849 | |
| | 1.8173 | 8.9231 | 29 | 1.7459 | |
| | 1.2673 | 9.2308 | 30 | 1.7413 | |
| |
| |
| ### Framework versions |
| |
| - PEFT 0.14.0 |
| - Transformers 4.46.3 |
| - Pytorch 2.5.1+cu121 |
| - Datasets 3.2.0 |
| - Tokenizers 0.20.3 |
