---
base_model: facebook/roberta-hate-speech-dynabench-r4-target
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: facebook-hate-speech-fine-tuned
  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. -->

# facebook-hate-speech-fine-tuned

This model is a fine-tuned version of [facebook/roberta-hate-speech-dynabench-r4-target](https://huggingface.co/facebook/roberta-hate-speech-dynabench-r4-target) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1943
- Accuracy: 0.9636
- Precision Macro: 0.8675
- Recall Macro: 0.8731
- F1 Macro: 0.8703
- Precision Micro: 0.9636
- Recall Micro: 0.9636
- F1 Micro: 0.9636

## 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision Macro | Recall Macro | F1 Macro | Precision Micro | Recall Micro | F1 Micro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:------------:|:--------:|:---------------:|:------------:|:--------:|
| 0.2628        | 1.0   | 199  | 0.1203          | 0.9585   | 0.8840          | 0.7939       | 0.8318   | 0.9585          | 0.9585       | 0.9585   |
| 0.071         | 2.0   | 398  | 0.1640          | 0.9673   | 0.9144          | 0.8369       | 0.8709   | 0.9673          | 0.9673       | 0.9673   |
| 0.1483        | 3.0   | 597  | 0.1943          | 0.9636   | 0.8675          | 0.8731       | 0.8703   | 0.9636          | 0.9636       | 0.9636   |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1