---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: roberta-twitter-hate
  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-twitter-hate

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4968
- Accuracy: 0.761
- Precision: 0.6722
- Recall: 0.8595
- F1: 0.7544

## 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: 32
- eval_batch_size: 32
- 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 | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 1.0   | 282  | 0.4968          | 0.761    | 0.6722    | 0.8595 | 0.7544 |
| 0.425         | 2.0   | 564  | 0.5053          | 0.761    | 0.6767    | 0.8431 | 0.7508 |
| 0.425         | 3.0   | 846  | 0.5244          | 0.777    | 0.7082    | 0.8126 | 0.7568 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.7.1+cu126
- Datasets 2.19.1
- Tokenizers 0.19.1