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WiessdornH/
trained_cyberattack_model_3

generated_from_trainer

WiessdornH/distilbert-cyber-domain

finetune

text-embeddings-inference

endpoints_compatible

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classifier_model

This model is a fine-tuned version of WiessdornH/distilbert-cyber-domain on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.1358
Accuracy: 0.9658

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: 16
eval_batch_size: 16
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	42	0.2462	0.8974
No log	2.0	84	0.1497	0.9658
No log	3.0	126	0.1358	0.9658

Framework versions

Transformers 4.56.1
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.0

WiessdornH/trained_cyberattack_model_3

classifier_model

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

WiessdornH/
trained_cyberattack_model_3