| --- |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: logs |
| 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. --> |
|
|
| # logs |
|
|
| - Loss: 0.0008 |
| - Precision: 0.9900 |
| - Recall: 0.995 |
| - F1: 0.9925 |
| - Accuracy: 0.9999 |
|
|
| ## 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: 5e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 8 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | No log | 1.0 | 44 | 0.0039 | 0.9701 | 0.975 | 0.9726 | 0.9991 | |
| | No log | 2.0 | 88 | 0.0018 | 0.8744 | 0.94 | 0.9060 | 0.9995 | |
| | No log | 3.0 | 132 | 0.0011 | 0.9559 | 0.975 | 0.9653 | 0.9998 | |
| | No log | 4.0 | 176 | 0.0008 | 0.9900 | 0.995 | 0.9925 | 0.9999 | |
| | No log | 5.0 | 220 | 0.0007 | 0.9803 | 0.995 | 0.9876 | 0.9999 | |
| | No log | 6.0 | 264 | 0.0007 | 0.9851 | 0.995 | 0.9900 | 0.9999 | |
| | No log | 7.0 | 308 | 0.0007 | 0.9900 | 0.995 | 0.9925 | 0.9999 | |
| | No log | 8.0 | 352 | 0.0007 | 0.9803 | 0.995 | 0.9876 | 0.9999 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.40.2 |
| - Pytorch 2.0.1 |
| - Datasets 2.19.1 |
| - Tokenizers 0.19.1 |
