learn_hf_phishing_not_phishing_text_classifier_rubert

This model is a fine-tuned version of DeepPavlov/rubert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.1041
• Accuracy: 0.9870

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: 0.0001
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH 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
0.5787	1.0	10	0.2982	0.9610
0.1417	2.0	20	0.1449	0.9610
0.0454	3.0	30	0.0945	0.9870
0.1515	4.0	40	0.2828	0.9610
0.0611	5.0	50	0.0820	0.9870
0.0018	6.0	60	0.0945	0.9870
0.0033	7.0	70	0.0998	0.9870
0.0006	8.0	80	0.1025	0.9870
0.0005	9.0	90	0.1037	0.9870
0.0004	10.0	100	0.1041	0.9870

Framework versions

• Transformers 4.50.3
• Pytorch 2.6.0+cu124
• Datasets 3.5.0
• Tokenizers 0.21.1