| --- |
| license: mit |
| tags: |
| - generated_from_trainer |
| datasets: |
| - indonlu |
| metrics: |
| - accuracy |
| - f1 |
| model-index: |
| - name: indobert-classification |
| results: |
| - task: |
| name: Text Classification |
| type: text-classification |
| dataset: |
| name: indonlu |
| type: indonlu |
| args: smsa |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.9396825396825397 |
| - name: F1 |
| type: f1 |
| value: 0.9393057427148881 |
| --- |
| |
| <!-- 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. --> |
|
|
| # indobert-classification |
|
|
| This model is a fine-tuned version of [indobenchmark/indobert-base-p1](https://huggingface.co/indobenchmark/indobert-base-p1) on the indonlu dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3707 |
| - Accuracy: 0.9397 |
| - F1: 0.9393 |
|
|
| ## 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: 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: 5 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
| | 0.2458 | 1.0 | 688 | 0.2229 | 0.9325 | 0.9323 | |
| | 0.1258 | 2.0 | 1376 | 0.2332 | 0.9373 | 0.9369 | |
| | 0.059 | 3.0 | 2064 | 0.3389 | 0.9365 | 0.9365 | |
| | 0.0268 | 4.0 | 2752 | 0.3412 | 0.9421 | 0.9417 | |
| | 0.0097 | 5.0 | 3440 | 0.3707 | 0.9397 | 0.9393 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.18.0 |
| - Pytorch 1.11.0+cu113 |
| - Datasets 2.1.0 |
| - Tokenizers 0.12.1 |
|
|
