---
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-roman-urdu-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-roman-urdu-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: 0.4537
- Accuracy: 0.9016
- Precision: 0.9015
- Recall: 0.9007
- F1: 0.9011

## 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     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.4956        | 0.9912 | 56   | 0.4878          | 0.8215   | 0.8208    | 0.8202 | 0.8205 |
| 0.3268        | 2.0    | 113  | 0.3194          | 0.8652   | 0.8699    | 0.8611 | 0.8632 |
| 0.2555        | 2.9912 | 169  | 0.3241          | 0.8839   | 0.8894    | 0.8798 | 0.8822 |
| 0.1832        | 4.0    | 226  | 0.3184          | 0.8914   | 0.8930    | 0.8891 | 0.8904 |
| 0.1283        | 4.9912 | 282  | 0.3375          | 0.8976   | 0.9028    | 0.8939 | 0.8962 |
| 0.0815        | 6.0    | 339  | 0.3645          | 0.8939   | 0.8937    | 0.8955 | 0.8937 |
| 0.0961        | 6.9912 | 395  | 0.3691          | 0.9001   | 0.9004    | 0.8988 | 0.8995 |
| 0.0544        | 8.0    | 452  | 0.4781          | 0.8901   | 0.8895    | 0.8910 | 0.8899 |
| 0.0404        | 8.9912 | 508  | 0.4209          | 0.9089   | 0.9104    | 0.9068 | 0.9081 |
| 0.0359        | 9.9115 | 560  | 0.4259          | 0.9051   | 0.9051    | 0.9042 | 0.9046 |


### Framework versions

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