modernbert-spam-classifier

This model is a fine-tuned version of deepvk/RuModernBERT-base on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0166
• Accuracy: 0.9958
• F1: 0.9958

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: 512
• eval_batch_size: 512
• 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: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.0172	1.0	570	0.0151	0.9955	0.9955
0.0066	2.0	1140	0.0166	0.9958	0.9958

Framework versions

• Transformers 4.51.0
• Pytorch 2.4.1
• Datasets 3.5.0
• Tokenizers 0.21.1