| --- |
| library_name: transformers |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: AR_200_41 |
| 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. --> |
|
|
| # AR_200_41 |
|
|
| This model was trained from scratch on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.5234 |
| - Accuracy: 0.5250 |
|
|
| ## 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: 0.0006 |
| - train_batch_size: 32 |
| - eval_batch_size: 32 |
| - seed: 41 |
| - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 1000 |
| - num_epochs: 10.0 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------:| |
| | 0.5298 | 1.0 | 2845 | 1.9969 | 0.3939 | |
| | 0.4512 | 2.0 | 5690 | 1.8217 | 0.4384 | |
| | 0.4173 | 3.0 | 8535 | 1.7295 | 0.4640 | |
| | 0.3977 | 4.0 | 11380 | 1.6786 | 0.4796 | |
| | 0.3841 | 5.0 | 14225 | 1.6362 | 0.4906 | |
| | 0.3747 | 6.0 | 17070 | 1.6065 | 0.4991 | |
| | 0.3677 | 7.0 | 19915 | 1.5772 | 0.5071 | |
| | 0.3586 | 8.0 | 22760 | 1.5534 | 0.5143 | |
| | 0.3504 | 9.0 | 25605 | 1.5324 | 0.5215 | |
| | 0.3437 | 10.0 | 28450 | 1.5234 | 0.5250 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.51.3 |
| - Pytorch 2.5.1+cu121 |
| - Datasets 3.6.0 |
| - Tokenizers 0.21.1 |
| |
