| --- |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| - accuracy |
| model-index: |
| - name: bert-eval-256 |
| 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-256 |
|
|
| This model was trained from scratch on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2605 |
| - F1: 0.7522 |
| - Roc Auc: 0.8283 |
| - Accuracy: 0.3007 |
|
|
| ## 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 | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:| |
| | 0.4097 | 1.0 | 751 | 0.3153 | 0.6628 | 0.7598 | 0.1638 | |
| | 0.2603 | 2.0 | 1502 | 0.2751 | 0.7205 | 0.7998 | 0.2328 | |
| | 0.2103 | 3.0 | 2253 | 0.2594 | 0.7507 | 0.8239 | 0.2837 | |
| | 0.1581 | 4.0 | 3004 | 0.2605 | 0.7522 | 0.8283 | 0.3007 | |
| | 0.1342 | 5.0 | 3755 | 0.2591 | 0.7513 | 0.8279 | 0.2897 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.30.2 |
| - Pytorch 2.0.1+cu118 |
| - Datasets 2.13.1 |
| - Tokenizers 0.13.3 |
|
|
