---
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-hate-mr
  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-hate-mr

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: 0.0281
- Accuracy: 0.9938
- Precision: 0.9938
- Recall: 0.9938
- F1: 0.9938

## 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: 32
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.6832        | 0.9836 | 30   | 0.6742          | 0.5084   | 0.7524    | 0.5072 | 0.3498 |
| 0.5977        | 2.0    | 61   | 0.8033          | 0.5253   | 0.6631    | 0.5242 | 0.3960 |
| 0.5943        | 2.9836 | 91   | 0.6655          | 0.6482   | 0.6846    | 0.6487 | 0.6304 |
| 0.3755        | 4.0    | 122  | 0.7484          | 0.6916   | 0.6983    | 0.6918 | 0.6891 |
| 0.4144        | 4.9836 | 152  | 0.6091          | 0.6988   | 0.6992    | 0.6988 | 0.6987 |
| 0.2831        | 6.0    | 183  | 0.7688          | 0.7205   | 0.7330    | 0.7208 | 0.7169 |
| 0.1818        | 6.9836 | 213  | 0.9114          | 0.7277   | 0.7361    | 0.7279 | 0.7254 |
| 0.0987        | 8.0    | 244  | 1.0269          | 0.7205   | 0.7207    | 0.7205 | 0.7204 |
| 0.0523        | 8.9836 | 274  | 1.1469          | 0.7301   | 0.7344    | 0.7303 | 0.7290 |
| 0.0329        | 9.8361 | 300  | 1.3097          | 0.7253   | 0.7301    | 0.7255 | 0.7240 |


### Framework versions

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