---
library_name: transformers
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: roberta-hate-speech-detection
  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. -->

# roberta-hate-speech-detection

This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4354
- Accuracy: 0.808
- Auc: 0.898
- Precision: 0.8081
- Recall: 0.8077
- F1: 0.8078

## 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: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Auc   | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:|:---------:|:------:|:------:|
| 0.691         | 1.0   | 188  | 0.6680          | 0.626    | 0.662 | 0.6289    | 0.6265 | 0.6222 |
| 0.6036        | 2.0   | 376  | 0.5378          | 0.726    | 0.807 | 0.7273    | 0.7257 | 0.7245 |
| 0.5107        | 3.0   | 564  | 0.5570          | 0.742    | 0.85  | 0.7668    | 0.7417 | 0.7371 |
| 0.4531        | 4.0   | 752  | 0.4833          | 0.778    | 0.88  | 0.7862    | 0.7783 | 0.7759 |
| 0.4077        | 5.0   | 940  | 0.4477          | 0.81     | 0.89  | 0.8131    | 0.8103 | 0.8101 |
| 0.3567        | 6.0   | 1128 | 0.4229          | 0.832    | 0.902 | 0.8316    | 0.8316 | 0.8316 |
| 0.3202        | 7.0   | 1316 | 0.4174          | 0.827    | 0.907 | 0.8273    | 0.8269 | 0.8269 |
| 0.299         | 8.0   | 1504 | 0.4531          | 0.822    | 0.909 | 0.8262    | 0.8222 | 0.8220 |
| 0.2625        | 9.0   | 1692 | 0.4289          | 0.839    | 0.912 | 0.8390    | 0.8389 | 0.8389 |
| 0.2457        | 10.0  | 1880 | 0.4246          | 0.846    | 0.915 | 0.8457    | 0.8455 | 0.8456 |
| 0.2173        | 11.0  | 2068 | 0.4783          | 0.844    | 0.914 | 0.8435    | 0.8435 | 0.8435 |
| 0.1956        | 12.0  | 2256 | 0.4893          | 0.845    | 0.915 | 0.8479    | 0.8449 | 0.8448 |
| 0.1761        | 13.0  | 2444 | 0.5208          | 0.837    | 0.914 | 0.8420    | 0.8369 | 0.8366 |
| 0.1627        | 14.0  | 2632 | 0.5077          | 0.842    | 0.918 | 0.8427    | 0.8415 | 0.8416 |
| 0.1482        | 15.0  | 2820 | 0.5581          | 0.835    | 0.917 | 0.8408    | 0.8349 | 0.8345 |
| 0.1437        | 16.0  | 3008 | 0.5135          | 0.854    | 0.921 | 0.8545    | 0.8542 | 0.8542 |
| 0.1315        | 17.0  | 3196 | 0.5428          | 0.846    | 0.921 | 0.8492    | 0.8462 | 0.8461 |
| 0.1209        | 18.0  | 3384 | 0.5382          | 0.853    | 0.921 | 0.8530    | 0.8529 | 0.8529 |
| 0.1186        | 19.0  | 3572 | 0.5839          | 0.844    | 0.92  | 0.8459    | 0.8435 | 0.8435 |
| 0.105         | 20.0  | 3760 | 0.5757          | 0.845    | 0.921 | 0.8468    | 0.8449 | 0.8448 |


### Framework versions

- Transformers 4.52.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1