| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: bert-base-cased |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - f1 |
| | model-index: |
| | - name: bert_base_cased |
| | 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_base_cased |
| |
|
| | This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.5496 |
| | - Accuracy: 0.8505 |
| | - F1: 0.8971 |
| |
|
| | ## 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 | |
| | |:-------------:|:------:|:----:|:---------------:|:--------:|:------:| |
| | | 0.6112 | 0.2174 | 50 | 0.6030 | 0.7328 | 0.8078 | |
| | | 0.525 | 0.4348 | 100 | 0.4881 | 0.7525 | 0.8399 | |
| | | 0.5386 | 0.6522 | 150 | 0.5263 | 0.7794 | 0.8544 | |
| | | 0.4511 | 0.8696 | 200 | 0.5176 | 0.8137 | 0.875 | |
| | | 0.2806 | 1.0870 | 250 | 0.4302 | 0.8088 | 0.8660 | |
| | | 0.3622 | 1.3043 | 300 | 0.4826 | 0.8309 | 0.8816 | |
| | | 0.2892 | 1.5217 | 350 | 0.3882 | 0.8358 | 0.8793 | |
| | | 0.2732 | 1.7391 | 400 | 0.4186 | 0.8309 | 0.8856 | |
| | | 0.3847 | 1.9565 | 450 | 0.3501 | 0.8431 | 0.8865 | |
| | | 0.1997 | 2.1739 | 500 | 0.5521 | 0.8627 | 0.9060 | |
| | | 0.162 | 2.3913 | 550 | 0.6342 | 0.8407 | 0.8926 | |
| | | 0.1125 | 2.6087 | 600 | 0.5181 | 0.8578 | 0.9020 | |
| | | 0.1388 | 2.8261 | 650 | 0.5496 | 0.8505 | 0.8971 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.57.6 |
| | - Pytorch 2.9.0+cu126 |
| | - Datasets 4.0.0 |
| | - Tokenizers 0.22.2 |
| | |
