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results – AI Model by Noola | AlphaNeural AI
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transformers
safetensors
distilbert
text-classification
generated_from_trainer
cybersectony/phishing-email-detection-distilbert_v2.4.1
finetune
apache-2.0
text-embeddings-inference
endpoints_compatible
us
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results
This model is a fine-tuned version of
cybersectony/phishing-email-detection-distilbert_v2.4.1
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.0222
Accuracy: 0.9964
Precision: 0.9965
Recall: 0.9964
F1: 0.9964
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
lr_scheduler_warmup_ratio: 0.1
num_epochs: 2
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
Precision
Recall
F1
0.0213
1.0
12716
0.0208
0.9964
0.9964
0.9964
0.9964
0.0071
2.0
25432
0.0222
0.9964
0.9965
0.9964
0.9964
Framework versions
Transformers 4.57.2
Pytorch 2.9.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1
