cesullivan99/sms-spam-weighted

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sms-spam-weighted

This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

• —Loss: 0.2336
• —Accuracy: 0.989
• —F1: 0.9575

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: 5e-05
• —trainbatchsize: 8
• —evalbatchsize: 8
• —seed: 42
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —num_epochs: 10

Training results

Framework versions

• —Transformers 4.28.0
• —Pytorch 2.0.1+cu118
• —Datasets 2.12.0
• —Tokenizers 0.13.3