| --- |
| library_name: transformers |
| license: mit |
| base_model: simpliTax/bert-automap-pbt-fine-tuned |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: category-v9 |
| 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. --> |
|
|
| # category-v9 |
|
|
| This model is a fine-tuned version of [simpliTax/bert-automap-pbt-fine-tuned](https://huggingface.co/simpliTax/bert-automap-pbt-fine-tuned) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.9912 |
| - Accuracy: 0.5912 |
| - Macro F1: 0.1862 |
| - Weighted F1: 0.5219 |
|
|
| ## 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: 13 |
| - optimizer: Use 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 | Macro F1 | Weighted F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:| |
| | 3.9677 | 1.0 | 738 | 2.7093 | 0.4737 | 0.1143 | 0.3833 | |
| | 2.7378 | 2.0 | 1476 | 2.1501 | 0.5706 | 0.1695 | 0.4986 | |
| | 1.9325 | 3.0 | 2214 | 1.9912 | 0.5912 | 0.1862 | 0.5219 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.0.0.dev0 |
| - Pytorch 2.9.0+cu126 |
| - Datasets 4.3.0 |
| - Tokenizers 0.22.1 |
| |
