bert-agent-scam-classifier-v1.0

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:

• Loss: 0.0039
• Accuracy: {'accuracy': 0.996875}
• Precision: {'precision': 0.996894409937888}
• Recall: {'recall': 0.996875}
• F1: {'f1': 0.9968749694821237}

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: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
No log	1.0	160	0.0032	{'accuracy': 0.996875}	{'precision': 0.996894409937888}	{'recall': 0.996875}	{'f1': 0.9968749694821237}
No log	2.0	320	0.0033	{'accuracy': 0.996875}	{'precision': 0.996894409937888}	{'recall': 0.996875}	{'f1': 0.9968749694821237}
No log	3.0	480	0.0034	{'accuracy': 0.996875}	{'precision': 0.996894409937888}	{'recall': 0.996875}	{'f1': 0.9968749694821237}
0.0354	4.0	640	0.0034	{'accuracy': 0.996875}	{'precision': 0.996894409937888}	{'recall': 0.996875}	{'f1': 0.9968749694821237}
0.0354	5.0	800	0.0039	{'accuracy': 0.996875}	{'precision': 0.996894409937888}	{'recall': 0.996875}	{'f1': 0.9968749694821237}

Framework versions

• Transformers 4.41.2
• Pytorch 2.3.0+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1