distilbert-spamEmail
This model is a second fine-tuned version of tony4194/ditilbert-spamEmail on an SetFit/enron_spam dataset. It achieves the following results on the evaluation set:
- Loss: 0.0621
- Accuracy: 0.9925
Model description
To detect spam messages.
Intended uses & limitations
Maximum paragraph or chunk_text is 512.
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.0083 | 1.0 | 1983 | 0.0569 | 0.9915 |
0.0012 | 2.0 | 3966 | 0.0620 | 0.993 |
0.0003 | 3.0 | 5949 | 0.0621 | 0.9925 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
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