rbc33/spam_not_spam

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spamnotspam

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: 0.0573
• —Accuracy: 0.9865

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: 0.002
• —trainbatchsize: 2
• —evalbatchsize: 2
• —seed: 42
• —optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
• —lrschedulertype: linear
• —num_epochs: 2

Training results

Framework versions

• —Transformers 4.47.0
• —Pytorch 2.5.1+cu124
• —Datasets 3.1.0
• —Tokenizers 0.21.0