bert-hate-speech-test

This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.6221
• Accuracy: 0.6828

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: 5e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6513	0.4405	200	0.6164	0.6773
0.6421	0.8811	400	0.6228	0.6773
0.6132	1.3216	600	0.6168	0.6773
0.6322	1.7621	800	0.6222	0.6828
0.6050	2.2026	1000	0.6217	0.6806
0.5978	2.6432	1200	0.6247	0.6718
0.6091	3.0	1362	0.6183	0.6663

Framework versions

• Transformers 5.13.0
• Pytorch 2.12.1+cpu
• Datasets 5.0.0
• Tokenizers 0.22.2