| --- |
| license: apache-2.0 |
| library_name: peft |
| tags: |
| - trl |
| - sft |
| - generated_from_trainer |
| base_model: mistralai/Mistral-7B-Instruct-v0.1 |
| datasets: |
| - generator |
| model-index: |
| - name: mistral_instruct_generation |
| 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. --> |
|
|
| # mistral_instruct_generation |
|
|
| This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1) on the generator dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.8488 |
|
|
| ## 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: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: constant |
| - lr_scheduler_warmup_steps: 0.03 |
| - training_steps: 500 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:------:|:----:|:---------------:| |
| | 1.1973 | 0.0305 | 20 | 1.1052 | |
| | 1.0347 | 0.0610 | 40 | 0.9958 | |
| | 0.9213 | 0.0915 | 60 | 0.9600 | |
| | 0.8886 | 0.1220 | 80 | 0.9406 | |
| | 0.9314 | 0.1524 | 100 | 0.9281 | |
| | 0.9668 | 0.1829 | 120 | 0.9197 | |
| | 0.887 | 0.2134 | 140 | 0.9128 | |
| | 0.8727 | 0.2439 | 160 | 0.9066 | |
| | 0.8571 | 0.2744 | 180 | 0.9005 | |
| | 0.8833 | 0.3049 | 200 | 0.8963 | |
| | 0.8466 | 0.3354 | 220 | 0.8912 | |
| | 0.9015 | 0.3659 | 240 | 0.8865 | |
| | 0.8602 | 0.3963 | 260 | 0.8822 | |
| | 0.8989 | 0.4268 | 280 | 0.8788 | |
| | 0.8452 | 0.4573 | 300 | 0.8758 | |
| | 0.8764 | 0.4878 | 320 | 0.8730 | |
| | 0.8702 | 0.5183 | 340 | 0.8708 | |
| | 0.8758 | 0.5488 | 360 | 0.8676 | |
| | 0.8071 | 0.5793 | 380 | 0.8638 | |
| | 0.8473 | 0.6098 | 400 | 0.8618 | |
| | 0.8822 | 0.6402 | 420 | 0.8586 | |
| | 0.8742 | 0.6707 | 440 | 0.8560 | |
| | 0.8526 | 0.7012 | 460 | 0.8533 | |
| | 0.8116 | 0.7317 | 480 | 0.8511 | |
| | 0.8593 | 0.7622 | 500 | 0.8488 | |
| |
| |
| ### Framework versions |
| |
| - PEFT 0.10.0 |
| - Transformers 4.40.1 |
| - Pytorch 2.3.0+cu121 |
| - Datasets 2.19.0 |
| - Tokenizers 0.19.1 |
