| --- |
| base_model: mistralai/Mistral-7B-v0.1 |
| datasets: |
| - generator |
| library_name: peft |
| license: apache-2.0 |
| tags: |
| - trl |
| - sft |
| - generated_from_trainer |
| model-index: |
| - name: mistral7bit-lora-sql |
| 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. --> |
|
|
| # mistral7bit-lora-sql |
|
|
| This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the generator dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3405 |
|
|
| ## 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: 0.0003 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 1399 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 32 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_steps: 100 |
| - training_steps: 500 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:------:|:----:|:---------------:| |
| | 0.7523 | 0.0565 | 20 | 0.5037 | |
| | 0.4763 | 0.1129 | 40 | 0.4221 | |
| | 0.4231 | 0.1694 | 60 | 0.3944 | |
| | 0.4051 | 0.2258 | 80 | 0.3833 | |
| | 0.396 | 0.2823 | 100 | 0.3756 | |
| | 0.3885 | 0.3387 | 120 | 0.3717 | |
| | 0.3829 | 0.3952 | 140 | 0.3651 | |
| | 0.3752 | 0.4517 | 160 | 0.3605 | |
| | 0.3752 | 0.5081 | 180 | 0.3565 | |
| | 0.3688 | 0.5646 | 200 | 0.3551 | |
| | 0.3655 | 0.6210 | 220 | 0.3530 | |
| | 0.3596 | 0.6775 | 240 | 0.3472 | |
| | 0.3565 | 0.7339 | 260 | 0.3460 | |
| | 0.3556 | 0.7904 | 280 | 0.3448 | |
| | 0.3553 | 0.8469 | 300 | 0.3440 | |
| | 0.3496 | 0.9033 | 320 | 0.3424 | |
| | 0.3446 | 0.9598 | 340 | 0.3405 | |
| | 0.3328 | 1.0162 | 360 | 0.3402 | |
| | 0.3035 | 1.0727 | 380 | 0.3405 | |
|
|
|
|
| ### Framework versions |
|
|
| - PEFT 0.12.0 |
| - Transformers 4.44.0 |
| - Pytorch 2.2.2+cu121 |
| - Datasets 2.21.0 |
| - Tokenizers 0.19.1 |
