| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: bert-base-uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - f1 |
| model-index: |
| - name: results |
| 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. --> |
|
|
| # results |
|
|
| This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.8221 |
| - Accuracy: 0.8578 |
| - F1: 0.9007 |
|
|
| ## 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: 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: 3 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
| |:-------------:|:------:|:----:|:---------------:|:--------:|:------:| |
| | 0.0601 | 0.2174 | 50 | 1.0957 | 0.8137 | 0.8774 | |
| | 0.1259 | 0.4348 | 100 | 0.7100 | 0.8284 | 0.8864 | |
| | 0.0279 | 0.6522 | 150 | 0.6962 | 0.8456 | 0.8885 | |
| | 0.0589 | 0.8696 | 200 | 0.6800 | 0.8603 | 0.9019 | |
| | 0.0544 | 1.0870 | 250 | 0.8519 | 0.8284 | 0.8818 | |
| | 0.0383 | 1.3043 | 300 | 0.7663 | 0.8578 | 0.8968 | |
| | 0.0126 | 1.5217 | 350 | 0.8467 | 0.8505 | 0.8920 | |
| | 0.0077 | 1.7391 | 400 | 0.8421 | 0.8578 | 0.8993 | |
| | 0.0874 | 1.9565 | 450 | 0.7528 | 0.8578 | 0.8961 | |
| | 0.0005 | 2.1739 | 500 | 0.8270 | 0.8652 | 0.9050 | |
| | 0.0009 | 2.3913 | 550 | 0.8435 | 0.8554 | 0.8981 | |
| | 0.0387 | 2.6087 | 600 | 0.8534 | 0.8652 | 0.9053 | |
| | 0.0495 | 2.8261 | 650 | 0.8221 | 0.8578 | 0.9007 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.0.0 |
| - Pytorch 2.10.0+cu128 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.2 |
| |
