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

This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co./bert-base-multilingual-uncased) on tnwei/ms-newspapers dataset.
It is a fixed version of YagiASAFAS/malaysia-news-classification-bert-english, which fixed the skewness of imbalanced distribution among categories.
It achieves the following results on the evaluation set:
- Loss: 1.0191
- Accuracy: 0.7277

## 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        | 0.98  | 44   | 2.0942          | 0.4525   |
| No log        | 1.98  | 88   | 1.5309          | 0.6103   |
| No log        | 2.98  | 132  | 1.2585          | 0.6774   |
| No log        | 3.98  | 176  | 1.1239          | 0.6955   |
| No log        | 4.98  | 220  | 1.0726          | 0.7165   |
| No log        | 5.98  | 264  | 1.0592          | 0.7151   |
| No log        | 6.98  | 308  | 1.0330          | 0.7221   |
| No log        | 7.98  | 352  | 1.0473          | 0.7123   |
| No log        | 8.98  | 396  | 1.0356          | 0.7207   |
| No log        | 9.98  | 440  | 1.0191          | 0.7277   |


### Framework versions

- Transformers 4.18.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.12.1