| --- |
| base_model: mistralai/Mistral-7B-Instruct-v0.3 |
| datasets: |
| - generator |
| library_name: peft |
| license: apache-2.0 |
| tags: |
| - trl |
| - sft |
| - generated_from_trainer |
| model-index: |
| - name: mistral_7b_cosine_lr |
| 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_7b_cosine_lr |
| |
| This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3) on the generator dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 5.3993 |
| |
| ## 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: 0.003 |
| - train_batch_size: 3 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - gradient_accumulation_steps: 8 |
| - total_train_batch_size: 24 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_ratio: 0.03 |
| - lr_scheduler_warmup_steps: 15 |
| - num_epochs: 4 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:------:|:----:|:---------------:| |
| | 11.1885 | 0.0549 | 10 | 61.4970 | |
| | 37.6512 | 0.1098 | 20 | 12.9405 | |
| | 14.576 | 0.1647 | 30 | 27.9852 | |
| | 9.5892 | 0.2196 | 40 | 6.4722 | |
| | 7.7639 | 0.2745 | 50 | 6.8158 | |
| | 6.3878 | 0.3294 | 60 | 6.3811 | |
| | 6.6118 | 0.3844 | 70 | 5.9281 | |
| | 6.006 | 0.4393 | 80 | 5.6753 | |
| | 6.1011 | 0.4942 | 90 | 5.8083 | |
| | 5.7396 | 0.5491 | 100 | 5.6193 | |
| | 5.5128 | 0.6040 | 110 | 5.4848 | |
| | 5.4599 | 0.6589 | 120 | 5.4267 | |
| | 5.5193 | 0.7138 | 130 | 5.4757 | |
| | 5.4488 | 0.7687 | 140 | 5.4422 | |
| | 5.4257 | 0.8236 | 150 | 5.3845 | |
| | 5.3938 | 0.8785 | 160 | 5.3727 | |
| | 5.3937 | 0.9334 | 170 | 5.3646 | |
| | 5.3916 | 0.9883 | 180 | 5.4825 | |
| | 5.4217 | 1.0432 | 190 | 5.3534 | |
| | 5.3915 | 1.0981 | 200 | 5.3497 | |
| | 5.3656 | 1.1531 | 210 | 5.3416 | |
| | 5.3718 | 1.2080 | 220 | 5.3691 | |
| | 5.3763 | 1.2629 | 230 | 5.4102 | |
| | 5.4039 | 1.3178 | 240 | 5.3993 | |
|
|
|
|
| ### Framework versions |
|
|
| - PEFT 0.13.2 |
| - Transformers 4.45.2 |
| - Pytorch 2.4.1+cu121 |
| - Datasets 3.0.1 |
| - Tokenizers 0.20.0 |
