| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: google-bert/bert-base-cased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| model-index: |
| - name: financial_classifier |
| 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. --> |
|
|
| # financial_classifier |
| |
| This model is a fine-tuned version of [google-bert/bert-base-cased](https://huggingface.co/google-bert/bert-base-cased) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.8641 |
| - F1: 0.8449 |
| |
| ## 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: 1e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 10 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:------:| |
| | 0.6009 | 1.0 | 243 | 0.5979 | 0.6961 | |
| | 0.2856 | 2.0 | 486 | 0.3836 | 0.8682 | |
| | 0.241 | 3.0 | 729 | 0.4665 | 0.8457 | |
| | 0.2022 | 4.0 | 972 | 0.5101 | 0.8620 | |
| | 0.1361 | 5.0 | 1215 | 0.5907 | 0.8586 | |
| | 0.1032 | 6.0 | 1458 | 0.7144 | 0.8393 | |
| | 0.0775 | 7.0 | 1701 | 0.7369 | 0.8651 | |
| | 0.0221 | 8.0 | 1944 | 0.7892 | 0.8591 | |
| | 0.0278 | 9.0 | 2187 | 0.8709 | 0.8352 | |
| | 0.0405 | 10.0 | 2430 | 0.8641 | 0.8449 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.52.4 |
| - Pytorch 2.6.0+cu124 |
| - Datasets 3.6.0 |
| - Tokenizers 0.21.2 |
| |
