Synthetic Data for Scam Detection
Collection
24 items
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Updated
This model is a fine-tuned version of google-bert/bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
---|---|---|---|---|---|---|---|
No log | 1.0 | 160 | 0.0118 | {'accuracy': 0.996875} | {'precision': 0.996894409937888} | {'recall': 0.996875} | {'f1': 0.9968749694821237} |
No log | 2.0 | 320 | 0.0107 | {'accuracy': 0.996875} | {'precision': 0.996894409937888} | {'recall': 0.996875} | {'f1': 0.9968749694821237} |
No log | 3.0 | 480 | 0.0091 | {'accuracy': 0.996875} | {'precision': 0.996894409937888} | {'recall': 0.996875} | {'f1': 0.9968749694821237} |
0.0304 | 4.0 | 640 | 0.0182 | {'accuracy': 0.996875} | {'precision': 0.996894409937888} | {'recall': 0.996875} | {'f1': 0.9968749694821237} |
0.0304 | 5.0 | 800 | 0.0188 | {'accuracy': 0.996875} | {'precision': 0.996894409937888} | {'recall': 0.996875} | {'f1': 0.9968749694821237} |
Base model
google-bert/bert-base-uncased