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