---
base_model: GroNLP/hateBERT
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: hateBERT-hate-offensive-normal-speech-lr-2e-05
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# hateBERT-hate-offensive-normal-speech-lr-2e-05

This model is a fine-tuned version of [GroNLP/hateBERT](https://huggingface.co/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