---
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-abusive-comments-ta
  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-abusive-comments-ta

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: 0.8852
- Accuracy: 0.7283
- Precision: 0.5073
- Recall: 0.3724
- F1: 0.3960

## 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-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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.1012        | 1.0   | 186  | 1.0154          | 0.7177   | 0.3787    | 0.3191 | 0.3198 |
| 0.9155        | 2.0   | 372  | 0.9336          | 0.7204   | 0.4450    | 0.3350 | 0.3497 |
| 0.7858        | 3.0   | 558  | 0.9033          | 0.7419   | 0.4941    | 0.3805 | 0.4130 |
| 0.5357        | 4.0   | 744  | 0.9495          | 0.7245   | 0.4971    | 0.4223 | 0.4381 |
| 0.5788        | 5.0   | 930  | 0.9960          | 0.7083   | 0.4491    | 0.4524 | 0.4408 |
| 0.3806        | 6.0   | 1116 | 1.1853          | 0.7298   | 0.5253    | 0.4417 | 0.4663 |
| 0.2375        | 7.0   | 1302 | 1.3106          | 0.7251   | 0.4946    | 0.4278 | 0.4439 |
| 0.187         | 8.0   | 1488 | 1.4710          | 0.7157   | 0.4674    | 0.4343 | 0.4480 |
| 0.0777        | 9.0   | 1674 | 1.6748          | 0.7110   | 0.4842    | 0.4221 | 0.4442 |
| 0.0589        | 10.0  | 1860 | 1.7426          | 0.7164   | 0.4840    | 0.4431 | 0.4594 |


### Framework versions

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