| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: bert-large-cased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: bert-large-cased-binary-classification |
| 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. --> |
|
|
| # bert-large-cased-binary-classification |
|
|
| This model is a fine-tuned version of [bert-large-cased](https://huggingface.co/bert-large-cased) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.1857 |
| - Accuracy: 0.7548 |
| - F1 Macro: 0.7312 |
| - Precision Macro: 0.7580 |
| - Recall Macro: 0.7246 |
| - Auc: 0.7883 |
|
|
| ## 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: 2e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - 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: 10 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Precision Macro | Recall Macro | Auc | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------------:|:------------:|:------:| |
| | No log | 1.0 | 79 | 0.6805 | 0.5987 | 0.3818 | 0.7987 | 0.5039 | 0.6079 | |
| | No log | 2.0 | 158 | 0.6254 | 0.6497 | 0.6490 | 0.6611 | 0.6655 | 0.7395 | |
| | No log | 3.0 | 237 | 0.6803 | 0.7166 | 0.6941 | 0.7087 | 0.6900 | 0.7563 | |
| | No log | 4.0 | 316 | 0.7502 | 0.7166 | 0.7106 | 0.7093 | 0.7153 | 0.7784 | |
| | No log | 5.0 | 395 | 1.1857 | 0.7548 | 0.7312 | 0.7580 | 0.7246 | 0.7883 | |
| | No log | 6.0 | 474 | 1.4866 | 0.7548 | 0.7312 | 0.7580 | 0.7246 | 0.7798 | |
| | 0.3165 | 7.0 | 553 | 1.5617 | 0.7420 | 0.7319 | 0.7322 | 0.7316 | 0.7829 | |
| | 0.3165 | 8.0 | 632 | 1.6626 | 0.7452 | 0.7311 | 0.7366 | 0.7280 | 0.7762 | |
| | 0.3165 | 9.0 | 711 | 1.7303 | 0.7611 | 0.7423 | 0.7595 | 0.7363 | 0.7768 | |
| | 0.3165 | 10.0 | 790 | 1.7471 | 0.7452 | 0.7294 | 0.7376 | 0.7255 | 0.7765 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.57.1 |
| - Pytorch 2.8.0+cu126 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.1 |
| |
