---
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
- precision
- recall
model-index:
- name: RoBERTa_Hatespeech_Classifier
  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_Hatespeech_Classifier

This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2496
- F1: 0.9405
- Accuracy: 0.9570
- Precision: 0.9430
- Recall: 0.9379

## 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: 8
- seed: 100
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step  | Validation Loss | F1     | Accuracy | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:--------:|:---------:|:------:|
| 0.2219        | 1.0   | 5084  | 0.2074          | 0.8884 | 0.9181   | 0.8762    | 0.9010 |
| 0.1731        | 2.0   | 10168 | 0.2263          | 0.9211 | 0.9429   | 0.9201    | 0.9222 |
| 0.125         | 3.0   | 15252 | 0.2425          | 0.9360 | 0.9539   | 0.9396    | 0.9325 |
| 0.076         | 4.0   | 20336 | 0.2556          | 0.9401 | 0.9568   | 0.9438    | 0.9364 |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2