distilbert-base-uncased-finetuned-scam-classification
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: 0.4129
- Accuracy: 0.9625
- F1: 0.9625
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: 1e-05
- 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: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.5637 | 1.0 | 40 | 0.4129 | 0.9625 | 0.9625 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.13.3