distilbert-base-uncased-OMDENA-cllbck-augmentation
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0373
- Accuracy: 0.9909
- Precision: 0.9914
- Recall: 0.9909
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: 0.0002
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall |
|---|---|---|---|---|---|---|
| 0.3742 | 1.0 | 326 | 0.0618 | 0.9851 | 0.9860 | 0.9851 |
| 0.0442 | 2.0 | 652 | 0.0373 | 0.9909 | 0.9914 | 0.9909 |
| 0.0207 | 3.0 | 978 | 0.0384 | 0.9909 | 0.9911 | 0.9910 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3