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malicious_url_multiclass_classification – AI Model by WFullen | AlphaNeural AI
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malicious_url_multiclass_classification
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peft
tensorboard
safetensors
generated_from_trainer
distilbert/distilbert-base-uncased
adapter
apache-2.0
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malicious_url_multiclass_classification
This model is a fine-tuned version of
distilbert-base-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0900
Accuracy: 0.9696
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: 0.001
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
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
Accuracy
0.1695
1.0
7122
0.1303
0.9556
0.1466
2.0
14245
0.1092
0.9625
0.136
3.0
21367
0.1112
0.9616
0.1294
4.0
28490
0.0971
0.9669
0.1124
5.0
35610
0.0900
0.9696
Framework versions
PEFT 0.8.2
Transformers 4.37.2
Pytorch 2.1.2
Datasets 2.1.0
Tokenizers 0.15.1
