network-threat_classifier-distilbert-base-uncased – AI Model by Ankitgoe | AlphaNeural AI

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Ankitgoe/
network-threat_classifier-distilbert-base-uncased

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google-bert/bert-base-uncased

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network-threat_classifier-distilbert-base-uncased

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

Loss: 0.8950
Accuracy: 0.715

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: 0.002
train_batch_size: 32
eval_batch_size: 32
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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.2079	1.0	125	0.4624	0.745
0.5508	2.0	250	0.8657	0.66
0.3098	3.0	375	0.5308	0.7
0.0933	4.0	500	0.8408	0.7
0.343	5.0	625	0.8979	0.675
0.3235	6.0	750	0.7056	0.705
0.2124	7.0	875	0.6523	0.655
0.1377	8.0	1000	0.7769	0.735
0.0439	9.0	1125	0.8804	0.73
0.158	10.0	1250	0.8950	0.715

Framework versions

PEFT 0.18.0
Transformers 4.57.3
Pytorch 2.9.0+cu126
Datasets 4.4.2
Tokenizers 0.22.1