| --- |
| library_name: transformers |
| base_model: AlexeySorokin/ossbert-onc-unlab-bs64-5epochs |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: trainer_output |
| 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. --> |
|
|
| # trainer_output |
| |
| This model is a fine-tuned version of [AlexeySorokin/ossbert-onc-unlab-bs64-5epochs](https://huggingface.co/AlexeySorokin/ossbert-onc-unlab-bs64-5epochs) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3650 |
| - Accuracy: 95.6576 |
| - Sentence accuracy: 59.4495 |
| |
| ## 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: 5e-05 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 25 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Sentence accuracy | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------:|:-----------------:| |
| | 1.0698 | 1.0 | 546 | 0.3788 | 92.1082 | 43.1193 | |
| | 0.3296 | 2.0 | 1092 | 0.2647 | 94.0969 | 51.9266 | |
| | 0.2081 | 3.0 | 1638 | 0.2419 | 94.4745 | 52.6606 | |
| | 0.1458 | 4.0 | 2184 | 0.2334 | 94.9906 | 53.9450 | |
| | 0.1071 | 5.0 | 2730 | 0.2254 | 95.1290 | 55.7798 | |
| | 0.0806 | 6.0 | 3276 | 0.2527 | 95.1919 | 57.7982 | |
| | 0.0599 | 7.0 | 3822 | 0.2556 | 95.3052 | 56.6972 | |
| | 0.042 | 8.0 | 4368 | 0.2634 | 95.3556 | 57.4312 | |
| | 0.0343 | 9.0 | 4914 | 0.2695 | 95.4940 | 57.6147 | |
| | 0.0237 | 10.0 | 5460 | 0.2970 | 95.3304 | 57.9817 | |
| | 0.0152 | 11.0 | 6006 | 0.2884 | 95.5444 | 58.7156 | |
| | 0.0102 | 12.0 | 6552 | 0.2950 | 95.5318 | 58.1651 | |
| | 0.0088 | 13.0 | 7098 | 0.3069 | 95.6199 | 57.4312 | |
| | 0.0049 | 14.0 | 7644 | 0.3217 | 95.7080 | 58.7156 | |
| | 0.0056 | 15.0 | 8190 | 0.3223 | 95.6576 | 58.8991 | |
| | 0.0044 | 16.0 | 8736 | 0.3220 | 95.7709 | 58.5321 | |
| | 0.0036 | 17.0 | 9282 | 0.3391 | 95.7206 | 59.2661 | |
| | 0.0035 | 18.0 | 9828 | 0.3515 | 95.5066 | 58.3486 | |
| | 0.0035 | 19.0 | 10374 | 0.3600 | 95.4940 | 58.3486 | |
| | 0.0022 | 20.0 | 10920 | 0.3650 | 95.6576 | 59.4495 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.57.3 |
| - Pytorch 2.10.0+cu128 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.2 |
|
|
