---
library_name: transformers
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: roberta-issue-classifier
  results: []
datasets:
- JyotiNayak/political_ideologies
language:
- en
---



# roberta-issue-classifier

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on [this](https://huggingface.co/datasets/JyotiNayak/political_ideologies) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0945
- Accuracy: 0.9844
- F1: 0.9844

## Model description

Issue Type Mapping: {'economic': 0, 'environmental': 1, 'family/gender': 2, 'geo-political and foreign policy': 3, 'political': 4, 'racial justice and immigration': 5, 'religious': 6, 'social, health and education': 7}

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.5661        | 0.625 | 100  | 0.4350          | 0.9437   | 0.9436 |
| 0.112         | 1.25  | 200  | 0.1488          | 0.975    | 0.9750 |
| 0.0335        | 1.875 | 300  | 0.1262          | 0.9781   | 0.9781 |
| 0.1009        | 2.5   | 400  | 0.1328          | 0.9781   | 0.9781 |
| 0.032         | 3.125 | 500  | 0.0945          | 0.9844   | 0.9844 |
| 0.0074        | 3.75  | 600  | 0.0944          | 0.9781   | 0.9781 |


### Framework versions

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