| --- |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: logs_rand |
| 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_rand |
| |
| - Loss: 0.0024 |
| - Precision: 0.8742 |
| - Recall: 0.8871 |
| - F1: 0.8806 |
| - Accuracy: 0.9992 |
| |
| ## 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: 5 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | No log | 1.0 | 57 | 0.0067 | 0.6685 | 0.6276 | 0.6474 | 0.9980 | |
| | No log | 2.0 | 114 | 0.0035 | 0.8286 | 0.8312 | 0.8299 | 0.9989 | |
| | No log | 3.0 | 171 | 0.0028 | 0.8690 | 0.8745 | 0.8717 | 0.9991 | |
| | No log | 4.0 | 228 | 0.0026 | 0.8693 | 0.8840 | 0.8766 | 0.9992 | |
| | No log | 5.0 | 285 | 0.0024 | 0.8742 | 0.8871 | 0.8806 | 0.9992 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.40.2 |
| - Pytorch 2.0.1 |
| - Datasets 2.19.1 |
| - Tokenizers 0.19.1 |
