metadata
base_model: GroNLP/hateBERT
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: hateBERT-hate-offensive-normal-speech-lr-2e-05
results: []
hateBERT-hate-offensive-normal-speech-lr-2e-05
This model is a fine-tuned version of GroNLP/hateBERT on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0207
- Accuracy: 0.9902
- Weighted f1: 0.9902
- Weighted recall: 0.9902
- Weighted precision: 0.9904
- Micro f1: 0.9902
- Micro recall: 0.9902
- Micro precision: 0.9902
- Macro f1: 0.9901
- Macro recall: 0.9903
- Macro precision: 0.9899
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted f1 | Weighted recall | Weighted precision | Micro f1 | Micro recall | Micro precision | Macro f1 | Macro recall | Macro precision |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6155 | 1.0 | 153 | 0.0889 | 0.9805 | 0.9805 | 0.9805 | 0.9806 | 0.9805 | 0.9805 | 0.9805 | 0.9801 | 0.9811 | 0.9793 |
| 0.0665 | 2.0 | 306 | 0.0368 | 0.9870 | 0.9870 | 0.9870 | 0.9870 | 0.9870 | 0.9870 | 0.9870 | 0.9864 | 0.9866 | 0.9864 |
| 0.0235 | 3.0 | 459 | 0.0264 | 0.9902 | 0.9902 | 0.9902 | 0.9904 | 0.9902 | 0.9902 | 0.9902 | 0.9901 | 0.9903 | 0.9899 |
| 0.0182 | 4.0 | 612 | 0.0414 | 0.9870 | 0.9870 | 0.9870 | 0.9873 | 0.9870 | 0.9870 | 0.9870 | 0.9865 | 0.9869 | 0.9864 |
| 0.012 | 5.0 | 765 | 0.0207 | 0.9902 | 0.9902 | 0.9902 | 0.9904 | 0.9902 | 0.9902 | 0.9902 | 0.9901 | 0.9903 | 0.9899 |
Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.6.dev0
- Tokenizers 0.13.3