| | --- |
| | license: apache-2.0 |
| | library_name: peft |
| | tags: |
| | - trl |
| | - sft |
| | - generated_from_trainer |
| | base_model: mistralai/Mistral-7B-Instruct-v0.2 |
| | model-index: |
| | - name: sqlm |
| | 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. --> |
| |
|
| | # sqlm |
| |
|
| | 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. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.3168 |
| |
|
| | ## 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: 200 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:------:|:----:|:---------------:| |
| | | 0.5858 | 0.0333 | 20 | 0.4605 | |
| | | 0.395 | 0.0667 | 40 | 0.3820 | |
| | | 0.352 | 0.1 | 60 | 0.3551 | |
| | | 0.3695 | 0.1333 | 80 | 0.3410 | |
| | | 0.3281 | 0.1667 | 100 | 0.3359 | |
| | | 0.3304 | 0.2 | 120 | 0.3325 | |
| | | 0.3435 | 0.2333 | 140 | 0.3292 | |
| | | 0.3416 | 0.2667 | 160 | 0.3275 | |
| | | 0.3331 | 0.3 | 180 | 0.3221 | |
| | | 0.328 | 0.3333 | 200 | 0.3168 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - PEFT 0.10.0 |
| | - Transformers 4.40.0 |
| | - Pytorch 2.2.2+cu121 |
| | - Datasets 2.19.0 |
| | - Tokenizers 0.19.1 |
