bnsapa/cybersecurity-ner

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cybersecurity-ner

This model is a fine-tuned version of distilbert-base-uncased on the cybersecurity-ner dataset. It achieves the following results on the evaluation set:

• —Loss: 0.2196
• —Precision: 0.7942
• —Recall: 0.7925
• —F1: 0.7933
• —Accuracy: 0.9508

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: 16
• —seed: 42
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —num_epochs: 8

Training results

Framework versions

• —Transformers 4.35.2
• —Pytorch 2.1.0+cu118
• —Datasets 2.15.0
• —Tokenizers 0.15.0