---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: malaysia-news-classification-bert-malay
  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. -->

# malaysia-news-classification-bert-malay

This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0311
- Accuracy: 0.7601

## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

## Label Mappings
This model can predict the following labels:
- `0`: Election
- `1`: Political Issue
- `2`: Corruption
- `3`: Democracy
- `4`: Economic Growth
- `5`: Economic Disparity
- `6`: Economic Subsidy
- `7`: Ethnic Discrimination
- `8`: Ethnic Relation
- `9`: Ethnic Culture
- `10`: Religious Issue
- `11`: Business and Finance
- `12`: Sport
- `13`: Food
- `14`: Entertainment
- `15`: Environmental Issue
- `16`: Domestic News
- `17`: World News

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 225  | 1.0295          | 0.7104   |
| No log        | 2.0   | 450  | 0.9205          | 0.7409   |
| 1.1064        | 3.0   | 675  | 0.8432          | 0.7590   |
| 1.1064        | 4.0   | 900  | 0.8552          | 0.7695   |
| 0.5596        | 5.0   | 1125 | 0.8836          | 0.7612   |
| 0.5596        | 6.0   | 1350 | 0.9057          | 0.7665   |
| 0.3499        | 7.0   | 1575 | 0.9766          | 0.7590   |
| 0.3499        | 8.0   | 1800 | 0.9974          | 0.7640   |
| 0.2144        | 9.0   | 2025 | 1.0211          | 0.7612   |
| 0.2144        | 10.0  | 2250 | 1.0311          | 0.7601   |


### Framework versions

- Transformers 4.18.0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.12.1