| --- |
| license: cc-by-sa-4.0 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - fin |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: fin2 |
| 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: 0.9362745098039216 |
| - name: Recall |
| type: recall |
| value: 0.7609561752988048 |
| - name: F1 |
| type: f1 |
| value: 0.8395604395604396 |
| - name: Accuracy |
| type: accuracy |
| value: 0.9742916119346969 |
| --- |
| |
| <!-- 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. --> |
|
|
| # fin2 |
|
|
| This model is a fine-tuned version of [nlpaueb/sec-bert-base](https://huggingface.co/nlpaueb/sec-bert-base) on the fin dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2405 |
| - Precision: 0.9363 |
| - Recall: 0.7610 |
| - F1: 0.8396 |
| - Accuracy: 0.9743 |
|
|
| ## 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 | 0.2186 | 0.7980 | 0.6454 | 0.7137 | 0.9653 | |
| | No log | 2.0 | 258 | 0.2109 | 0.9487 | 0.7371 | 0.8296 | 0.9734 | |
| | No log | 3.0 | 387 | 0.2531 | 0.9746 | 0.7649 | 0.8571 | 0.9743 | |
| | 0.1166 | 4.0 | 516 | 0.2345 | 0.9403 | 0.7530 | 0.8363 | 0.9741 | |
| | 0.1166 | 5.0 | 645 | 0.2405 | 0.9363 | 0.7610 | 0.8396 | 0.9743 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.25.1 |
| - Pytorch 1.13.0+cu116 |
| - Datasets 2.7.1 |
| - Tokenizers 0.13.2 |
|
|
