| --- |
| library_name: transformers |
| base_model: ProsusAI/finbert |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: category-finbert |
| 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-finbert |
|
|
| This model is a fine-tuned version of [ProsusAI/finbert](https://huggingface.co/ProsusAI/finbert) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 2.2288 |
| - Accuracy: 0.5391 |
| - Macro F1: 0.1796 |
| - Weighted F1: 0.4589 |
|
|
| ## 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 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:| |
| | 4.2041 | 1.0 | 836 | 2.9954 | 0.4063 | 0.0880 | 0.2977 | |
| | 2.6344 | 2.0 | 1672 | 2.4037 | 0.5040 | 0.1556 | 0.4178 | |
| | 2.1611 | 3.0 | 2508 | 2.2288 | 0.5391 | 0.1796 | 0.4589 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.0.0.dev0 |
| - Pytorch 2.9.0+cu126 |
| - Datasets 4.3.0 |
| - Tokenizers 0.22.1 |
| |
