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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: malaysia-news-classification-bert-malay |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# malaysia-news-classification-bert-malay |
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This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0311 |
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- Accuracy: 0.7601 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 3e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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- mixed_precision_training: Native AMP |
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## Label Mappings |
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This model can predict the following labels: |
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- `0`: Election |
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- `1`: Political Issue |
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- `2`: Corruption |
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- `3`: Democracy |
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- `4`: Economic Growth |
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- `5`: Economic Disparity |
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- `6`: Economic Subsidy |
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- `7`: Ethnic Discrimination |
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- `8`: Ethnic Relation |
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- `9`: Ethnic Culture |
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- `10`: Religious Issue |
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- `11`: Business and Finance |
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- `12`: Sport |
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- `13`: Food |
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- `14`: Entertainment |
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- `15`: Environmental Issue |
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- `16`: Domestic News |
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- `17`: World News |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| No log | 1.0 | 225 | 1.0295 | 0.7104 | |
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| No log | 2.0 | 450 | 0.9205 | 0.7409 | |
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| 1.1064 | 3.0 | 675 | 0.8432 | 0.7590 | |
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| 1.1064 | 4.0 | 900 | 0.8552 | 0.7695 | |
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| 0.5596 | 5.0 | 1125 | 0.8836 | 0.7612 | |
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| 0.5596 | 6.0 | 1350 | 0.9057 | 0.7665 | |
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| 0.3499 | 7.0 | 1575 | 0.9766 | 0.7590 | |
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| 0.3499 | 8.0 | 1800 | 0.9974 | 0.7640 | |
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| 0.2144 | 9.0 | 2025 | 1.0211 | 0.7612 | |
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| 0.2144 | 10.0 | 2250 | 1.0311 | 0.7601 | |
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### Framework versions |
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- Transformers 4.18.0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.12.1 |
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