---
library_name: transformers
base_model: cardiffnlp/twitter-roberta-base-hate
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: twitter-roberta-base-hate_69
  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. -->

# twitter-roberta-base-hate_69

This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-hate](https://huggingface.co/cardiffnlp/twitter-roberta-base-hate) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3841
- F1-score: 0.8519
- Accuracy: 0.8531
- Precision: 0.8508
- Recall: 0.8544

## 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: 5e-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 69
- 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
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1-score | Accuracy | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:------:|
| No log        | 1.0   | 180  | 0.3803          | 0.8198   | 0.8217   | 0.8189    | 0.8212 |
| No log        | 2.0   | 360  | 0.3648          | 0.8346   | 0.8357   | 0.8338    | 0.8379 |
| 0.3622        | 3.0   | 540  | 0.3787          | 0.8529   | 0.8531   | 0.8557    | 0.8603 |
| 0.3622        | 4.0   | 720  | 0.3777          | 0.8408   | 0.8427   | 0.8401    | 0.8417 |
| 0.3622        | 5.0   | 900  | 0.3768          | 0.8554   | 0.8566   | 0.8542    | 0.8575 |
| 0.2436        | 6.0   | 1080 | 0.3841          | 0.8519   | 0.8531   | 0.8508    | 0.8544 |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0