distilbert-scam-classification-fine-tuned-elder

This model is a fine-tuned version of BothBosu/distilbert-scam-classification-v1 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 1.6626
• Accuracy: 0.925
• Precision: 0.8889
• Recall: 0.9412
• F1: 0.9143

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: 0.004
• train_batch_size: 64
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• training_steps: 200

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.0	6.6667	20	1.8102	0.9	0.8421	0.9412	0.8889
0.0	13.3333	40	1.7751	0.9	0.8421	0.9412	0.8889
0.0	20.0	60	1.7390	0.9	0.8421	0.9412	0.8889
0.0	26.6667	80	1.7140	0.925	0.8889	0.9412	0.9143
0.0	33.3333	100	1.7016	0.925	0.8889	0.9412	0.9143
0.0	40.0	120	1.6990	0.925	0.8889	0.9412	0.9143
0.0	46.6667	140	1.6819	0.925	0.8889	0.9412	0.9143
0.0	53.3333	160	1.6602	0.925	0.8889	0.9412	0.9143
0.0	60.0	180	1.6626	0.925	0.8889	0.9412	0.9143
0.0	66.6667	200	1.6626	0.925	0.8889	0.9412	0.9143

Framework versions

• Transformers 4.40.0
• Pytorch 2.2.1+cu121
• Datasets 2.19.0
• Tokenizers 0.19.1