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---
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
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