---
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-fine-grained
  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-fine-grained

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: 0.8408
- Accuracy: 0.8023
- Precision: 0.7245
- Recall: 0.7129
- F1: 0.7177

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.9091        | 1.0   | 113  | 0.8078          | 0.7034   | 0.3788    | 0.4083 | 0.3878 |
| 1.1008        | 2.0   | 226  | 0.9036          | 0.6510   | 0.2624    | 0.3397 | 0.2841 |
| 0.7624        | 3.0   | 339  | 0.6444          | 0.7844   | 0.7015    | 0.6274 | 0.6544 |
| 0.5512        | 4.0   | 452  | 0.5075          | 0.8342   | 0.7675    | 0.7453 | 0.7463 |
| 0.5258        | 5.0   | 565  | 0.3519          | 0.8858   | 0.8263    | 0.8081 | 0.8163 |
| 0.3489        | 6.0   | 678  | 0.3154          | 0.9011   | 0.8612    | 0.8260 | 0.8399 |
| 0.3182        | 7.0   | 791  | 0.2394          | 0.9295   | 0.8985    | 0.8864 | 0.8895 |
| 0.2263        | 8.0   | 904  | 0.1722          | 0.9502   | 0.9092    | 0.9223 | 0.9143 |
| 0.2024        | 9.0   | 1017 | 0.1252          | 0.9684   | 0.9474    | 0.9441 | 0.9457 |
| 0.1757        | 10.0  | 1130 | 0.1101          | 0.9736   | 0.9592    | 0.9506 | 0.9548 |


### Framework versions

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