test_results

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

• Loss: 0.3388
• Accuracy: 0.8628

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 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: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	57	0.5293	0.8053
No log	2.0	114	0.3820	0.8628
No log	3.0	171	0.3388	0.8628

Framework versions

• Transformers 4.51.3
• Pytorch 2.3.1+cu118
• Datasets 3.6.0
• Tokenizers 0.21.1