| --- |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| - accuracy |
| model-index: |
| - name: bert-eval |
| 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. --> |
|
|
| # bert-eval |
|
|
| This model was trained from scratch on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2288 |
| - F1: 0.7837 |
| - Roc Auc: 0.8490 |
| - Accuracy: 0.3137 |
|
|
| ## 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 | F1 | Roc Auc | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:| |
| | 0.4067 | 1.0 | 751 | 0.2930 | 0.7145 | 0.7911 | 0.2188 | |
| | 0.2483 | 2.0 | 1502 | 0.2528 | 0.7493 | 0.8167 | 0.2777 | |
| | 0.1993 | 3.0 | 2253 | 0.2323 | 0.7772 | 0.8406 | 0.3067 | |
| | 0.1468 | 4.0 | 3004 | 0.2288 | 0.7837 | 0.8490 | 0.3137 | |
| | 0.1238 | 5.0 | 3755 | 0.2287 | 0.7837 | 0.8509 | 0.3217 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.30.2 |
| - Pytorch 2.0.1+cu118 |
| - Datasets 2.13.1 |
| - Tokenizers 0.13.3 |
|
|
