| --- |
| library_name: transformers |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: checkpoints |
| 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. --> |
|
|
| # checkpoints |
|
|
| This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 4.2659 |
|
|
| ## 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: 48 |
| - eval_batch_size: 48 |
| - seed: 42 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 96 |
| - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_steps: 2000 |
| - num_epochs: 2 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:------:|:-----:|:---------------:| |
| | 7.4032 | 0.0845 | 500 | 7.3900 | |
| | 6.6368 | 0.1689 | 1000 | 6.6176 | |
| | 6.0293 | 0.2534 | 1500 | 6.0336 | |
| | 5.4871 | 0.3379 | 2000 | 5.4602 | |
| | 5.1774 | 0.4224 | 2500 | 5.1387 | |
| | 4.9533 | 0.5068 | 3000 | 4.9452 | |
| | 4.8279 | 0.5913 | 3500 | 4.8122 | |
| | 4.7441 | 0.6758 | 4000 | 4.7194 | |
| | 4.6783 | 0.7603 | 4500 | 4.6470 | |
| | 4.6144 | 0.8447 | 5000 | 4.5846 | |
| | 4.5477 | 0.9292 | 5500 | 4.5297 | |
| | 4.4920 | 1.0137 | 6000 | 4.4871 | |
| | 4.4523 | 1.0982 | 6500 | 4.4475 | |
| | 4.3954 | 1.1826 | 7000 | 4.4127 | |
| | 4.4032 | 1.2671 | 7500 | 4.3827 | |
| | 4.4052 | 1.3516 | 8000 | 4.3571 | |
| | 4.3566 | 1.4361 | 8500 | 4.3329 | |
| | 4.3505 | 1.5205 | 9000 | 4.3124 | |
| | 4.3208 | 1.6050 | 9500 | 4.2945 | |
| | 4.3149 | 1.6895 | 10000 | 4.2829 | |
| | 4.3015 | 1.7739 | 10500 | 4.2739 | |
| | 4.2932 | 1.8584 | 11000 | 4.2682 | |
| | 4.2789 | 1.9429 | 11500 | 4.2659 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 5.0.0 |
| - Pytorch 2.8.0+cu128 |
| - Datasets 4.5.0 |
| - Tokenizers 0.22.2 |
|
|
