| --- |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: binary_classification |
| 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. --> |
|
|
| # binary_classification |
| |
| - Loss: 0.0159 |
| - Precision: 1.0 |
| - Recall: 1.0 |
| - F1: 1.0 |
| - Accuracy: 1.0 |
| |
| ## 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: 64 |
| - eval_batch_size: 64 |
| - 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 | 9 | 0.0159 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | No log | 2.0 | 18 | 0.0030 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | No log | 3.0 | 27 | 0.0023 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | No log | 4.0 | 36 | 0.0028 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | No log | 5.0 | 45 | 0.0018 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | No log | 6.0 | 54 | 0.0011 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | No log | 7.0 | 63 | 0.0010 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | No log | 8.0 | 72 | 0.0010 | 1.0 | 1.0 | 1.0 | 1.0 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.40.2 |
| - Pytorch 2.0.1 |
| - Datasets 2.19.1 |
| - Tokenizers 0.19.1 |
