| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: bert-base-uncased |
| | tags: |
| | - generated_from_trainer |
| | 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 the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.2290 |
| | - Micro f1: 0.7075 |
| | - Macro f1: 0.6540 |
| |
|
| | ## 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: 3e-05 |
| | - train_batch_size: 4 |
| | - eval_batch_size: 32 |
| | - 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: constant |
| | - num_epochs: 20 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Micro f1 | Macro f1 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:| |
| | | 0.4348 | 1.0 | 56 | 0.3544 | 0.0 | 0.0 | |
| | | 0.3297 | 2.0 | 112 | 0.3156 | 0.3816 | 0.1501 | |
| | | 0.2897 | 3.0 | 168 | 0.2885 | 0.3684 | 0.1382 | |
| | | 0.2501 | 4.0 | 224 | 0.2668 | 0.5465 | 0.2805 | |
| | | 0.211 | 5.0 | 280 | 0.2335 | 0.56 | 0.2879 | |
| | | 0.1765 | 6.0 | 336 | 0.2264 | 0.5876 | 0.3426 | |
| | | 0.1497 | 7.0 | 392 | 0.2205 | 0.6102 | 0.3650 | |
| | | 0.1221 | 8.0 | 448 | 0.1988 | 0.6919 | 0.5777 | |
| | | 0.0964 | 9.0 | 504 | 0.2068 | 0.6701 | 0.5927 | |
| | | 0.0753 | 10.0 | 560 | 0.1951 | 0.6927 | 0.5971 | |
| | | 0.0614 | 11.0 | 616 | 0.1945 | 0.7136 | 0.6779 | |
| | | 0.0495 | 12.0 | 672 | 0.2035 | 0.6866 | 0.6138 | |
| | | 0.0387 | 13.0 | 728 | 0.2069 | 0.6977 | 0.6563 | |
| | | 0.0347 | 14.0 | 784 | 0.2082 | 0.7238 | 0.6668 | |
| | | 0.0318 | 15.0 | 840 | 0.2161 | 0.6957 | 0.6380 | |
| | | 0.028 | 16.0 | 896 | 0.2075 | 0.7143 | 0.6687 | |
| | | 0.0235 | 17.0 | 952 | 0.2149 | 0.7130 | 0.6650 | |
| | | 0.0212 | 18.0 | 1008 | 0.2201 | 0.7170 | 0.6655 | |
| | | 0.019 | 19.0 | 1064 | 0.2196 | 0.7256 | 0.6686 | |
| | | 0.0169 | 20.0 | 1120 | 0.2290 | 0.7075 | 0.6540 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.55.4 |
| | - Pytorch 2.8.0+cu126 |
| | - Datasets 4.0.0 |
| | - Tokenizers 0.21.4 |
| | |
