---
library_name: transformers
license: mit
base_model: cardiffnlp/twitter-roberta-large-hate-latest
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: twitter-roberta-large-hate-latest-offensive-eval-kn
  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-large-hate-latest-offensive-eval-kn

This model is a fine-tuned version of [cardiffnlp/twitter-roberta-large-hate-latest](https://huggingface.co/cardiffnlp/twitter-roberta-large-hate-latest) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7861
- Accuracy: 0.7427
- Precision: 0.4604
- Recall: 0.3928
- F1: 0.3901

## 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: 16
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.8805        | 0.9968 | 157  | 0.8450          | 0.7339   | 0.3531    | 0.3488 | 0.3407 |
| 0.7579        | 2.0    | 315  | 0.7816          | 0.7607   | 0.5057    | 0.4154 | 0.4200 |
| 0.7177        | 2.9968 | 472  | 0.7848          | 0.7571   | 0.4702    | 0.4043 | 0.4209 |
| 0.6914        | 4.0    | 630  | 0.8011          | 0.7446   | 0.4242    | 0.4029 | 0.4077 |
| 0.5218        | 4.9841 | 785  | 0.8166          | 0.7429   | 0.4122    | 0.4146 | 0.4115 |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0