mrm8488/bert-tiny-finetuned-enron-spam-detection

<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->

BERT-Tiny fine-tuned on Enron Spam Detection

This model is a fine-tuned version of google/bert_uncased_L-2_H-128_A-2 (aka BERT-Tiny) on an SetFit/enron_spam for Spam Dectection downstream task.

It achieves the following results on the evaluation set:

• —Loss: 0.0593
• —Precision: 0.9851
• —Recall: 0.9871
• —Accuracy: 0.986
• —F1: 0.9861

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 4.23.1
• —Pytorch 1.12.1+cu113
• —Datasets 2.6.1
• —Tokenizers 0.13.1