mccoole/bert-tiny-finetuned-enron-spam-detection

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bert-tiny-finetuned-enron-spam-detection

This model is a fine-tuned version of google/bert_uncased_L-2_H-128_A-2 on an unknown dataset. It achieves the following results on the evaluation set:

• —Loss: 0.0633
• —Precision: 0.9861
• —Recall: 0.9851
• —Accuracy: 0.9855
• —F1: 0.9856

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
• —trainbatchsize: 16
• —evalbatchsize: 32
• —seed: 42
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —num_epochs: 4

Training results

Framework versions

• —Transformers 4.31.0
• —Pytorch 2.0.1+cu118
• —Datasets 2.13.1
• —Tokenizers 0.13.3