---
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-hinglish-binary
  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-hinglish-binary

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: 0.8288
- Accuracy: 0.6779
- Precision: 0.6455
- Recall: 0.6188
- F1: 0.6218

## 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: 4
- total_train_batch_size: 128
- 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     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.6392        | 0.9709 | 25   | 0.6656          | 0.6376   | 0.3188    | 0.5    | 0.3894 |
| 0.63          | 1.9806 | 51   | 0.7095          | 0.6403   | 0.8197    | 0.5038 | 0.3975 |
| 0.6117        | 2.9903 | 77   | 0.6043          | 0.6921   | 0.6720    | 0.6174 | 0.6176 |
| 0.5974        | 4.0    | 103  | 0.6540          | 0.6730   | 0.6787    | 0.5667 | 0.5369 |
| 0.5512        | 4.9709 | 128  | 0.6216          | 0.6948   | 0.6745    | 0.6228 | 0.6243 |
| 0.5162        | 5.9806 | 154  | 0.6164          | 0.7057   | 0.6873    | 0.6394 | 0.6438 |
| 0.4525        | 6.9903 | 180  | 0.6715          | 0.6948   | 0.6757    | 0.6211 | 0.6221 |
| 0.4207        | 8.0    | 206  | 0.7581          | 0.7084   | 0.6844    | 0.6562 | 0.6620 |
| 0.3381        | 8.9709 | 231  | 0.7439          | 0.6812   | 0.6560    | 0.6575 | 0.6567 |
| 0.3016        | 9.7087 | 250  | 0.7481          | 0.7030   | 0.6762    | 0.6649 | 0.6688 |


### Framework versions

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