| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - fin |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: fin1 |
| results: |
| - task: |
| name: Token Classification |
| type: token-classification |
| dataset: |
| name: fin |
| type: fin |
| config: default |
| split: train |
| args: default |
| metrics: |
| - name: Precision |
| type: precision |
| value: 0.8315412186379928 |
| - name: Recall |
| type: recall |
| value: 0.9243027888446215 |
| - name: F1 |
| type: f1 |
| value: 0.8754716981132076 |
| - name: Accuracy |
| type: accuracy |
| value: 0.985175455057234 |
| --- |
| |
| <!-- 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. --> |
|
|
| # fin1 |
|
|
| This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the fin dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0778 |
| - Precision: 0.8315 |
| - Recall: 0.9243 |
| - F1: 0.8755 |
| - Accuracy: 0.9852 |
|
|
| ## 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: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 5 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | No log | 1.0 | 129 | 0.0860 | 0.8535 | 0.9283 | 0.8893 | 0.9904 | |
| | No log | 2.0 | 258 | 0.1513 | 0.7993 | 0.9203 | 0.8556 | 0.9799 | |
| | No log | 3.0 | 387 | 0.0977 | 0.8221 | 0.9203 | 0.8684 | 0.9831 | |
| | 0.0017 | 4.0 | 516 | 0.0783 | 0.8286 | 0.9243 | 0.8738 | 0.9848 | |
| | 0.0017 | 5.0 | 645 | 0.0778 | 0.8315 | 0.9243 | 0.8755 | 0.9852 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.25.1 |
| - Pytorch 1.13.0+cu116 |
| - Datasets 2.7.1 |
| - Tokenizers 0.13.2 |
|
|
