Jios/bert-unformatted-network-data-test

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bert-unformatted-network-data-test

This model is a fine-tuned version of roberta-large on an unknown dataset. It achieves the following results on the evaluation set:

• —Loss: 0.0000

EXAMPLE FULL NAMES:

label0 = malicious (UDP-lag DDoS), label1 = benign

1. 1.malicious from training dataset
2. 2.benign from training dataset
3. 3.malicious outside training dataset
4. 4.malicious outside training dataset 2
5. 5.benign outside training dataset
6. 6.benign outside training dataset 2
7. 7.benign then malicious same entry
8. 8.malicious then benign same entry

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

Training results

Framework versions

• —Transformers 4.42.0.dev0
• —Pytorch 2.3.0+cu121
• —Datasets 2.19.1
• —Tokenizers 0.19.1