| --- |
| library_name: transformers |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: RU_5000_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. --> |
|
|
| # RU_5000_41 |
|
|
| This model was trained from scratch on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 3.6599 |
| - Accuracy: 0.3491 |
|
|
| ## 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 | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------:| |
| | 1.3059 | 1.0 | 1078 | 4.9954 | 0.1736 | |
| | 1.1451 | 2.0 | 2156 | 4.7373 | 0.1922 | |
| | 1.0836 | 3.0 | 3234 | 4.4236 | 0.2366 | |
| | 1.0047 | 4.0 | 4312 | 4.1600 | 0.2740 | |
| | 0.946 | 5.0 | 5390 | 3.9872 | 0.2974 | |
| | 0.9072 | 6.0 | 6468 | 3.8856 | 0.3124 | |
| | 0.8782 | 7.0 | 7546 | 3.7939 | 0.3268 | |
| | 0.8536 | 8.0 | 8624 | 3.7305 | 0.3372 | |
| | 0.8319 | 9.0 | 9702 | 3.6857 | 0.3451 | |
| | 0.8148 | 10.0 | 10780 | 3.6599 | 0.3491 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.51.3 |
| - Pytorch 2.5.1+cu121 |
| - Datasets 3.6.0 |
| - Tokenizers 0.21.1 |
| |
