trainer

This model is a fine-tuned version of GroNLP/hateBERT on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.5228
• Accuracy: {'accuracy': 0.7989466452942523}

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: 0.001
• train_batch_size: 10
• eval_batch_size: 10
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 20
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.4295	1.0	2217	0.6655	{'accuracy': 0.7348294023356996}
0.3365	2.0	4434	0.5471	{'accuracy': 0.7874971376230822}
0.2882	3.0	6651	0.5133	{'accuracy': 0.8014655369819098}
0.2574	4.0	8868	0.5228	{'accuracy': 0.7989466452942523}

Framework versions

• PEFT 0.10.0
• Transformers 4.39.3
• Pytorch 2.2.2+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2