distilbert-base-uncased-spam-test
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0238
- Accuracy: 0.9933
- F1: 0.9933
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: 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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.1739 | 1.0 | 260 | 0.0391 | 0.9894 | 0.9894 |
| 0.0181 | 2.0 | 520 | 0.0238 | 0.9933 | 0.9933 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.10.1+cu102
- Datasets 2.4.0
- Tokenizers 0.12.1