bert-small-phishing-ONNX – AI Model by onnx-community | AlphaNeural AI

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onnx-community/
bert-small-phishing-ONNX

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transformers.js

text-classification

generated_from_trainer

phishing_classifier

David-Egea/phishing-texts

David-Egea/bert-small-phishing

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bert-small-phishing (ONNX)

This is an ONNX version of David-Egea/bert-small-phishing. It was automatically converted and uploaded using this Hugging Face Space.

Usage with Transformers.js

See the pipeline documentation for text-classification: https://huggingface.co/docs/transformers.js/api/pipelines#module_pipelines.TextClassificationPipeline

bert-small-phishing

This model is a fine-tuned version of prajjwal1/bert-small on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.1006
Accuracy: 0.9766
Precision: 0.9713
Recall: 0.9669
F1: 0.9691

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.202	1.0	762	0.0941	0.9717	0.9728	0.9520	0.9623
0.077	2.0	1524	0.0964	0.9764	0.9757	0.9617	0.9686
0.0428	3.0	2286	0.0992	0.9786	0.9739	0.9695	0.9717
0.0248	4.0	3048	0.1006	0.9766	0.9713	0.9669	0.9691

Framework versions

Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2