hateBERT-finetuned

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

• Loss: 0.7774
• Accuracy: 0.7967
• F1: 0.8416

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: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.4449	1.0	1548	0.4935	0.7909	0.8432
0.3465	2.0	3096	0.5296	0.7944	0.8375
0.2789	3.0	4644	0.7774	0.7967	0.8416

Framework versions

• Transformers 4.16.2
• Pytorch 1.12.1+cu113
• Datasets 1.18.3
• Tokenizers 0.13.2