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bert-unformatted-network-data-test – AI Model by Jios | AlphaNeural AI
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Jios
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bert-unformatted-network-data-test
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transformers
tensorboard
safetensors
roberta
text-classification
generated_from_trainer
FacebookAI/roberta-large
finetune
mit
autotrain_compatible
endpoints_compatible
us
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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:
label_0 = malicious (UDP-lag DDoS), label_1 = benign
malicious from training dataset
benign from training dataset
malicious outside training dataset
malicious outside training dataset 2
benign outside training dataset
benign outside training dataset 2
benign then malicious same entry
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
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5
Training results
Training Loss
Epoch
Step
Validation Loss
0.0139
1.0
750
0.0000
0.0
2.0
1500
0.0000
0.0
3.0
2250
0.0000
0.0
4.0
3000
0.0000
0.0
5.0
3750
0.0000
Framework versions
Transformers 4.42.0.dev0
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1
