| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - indonlu |
| | metrics: |
| | - accuracy |
| | - f1 |
| | model-index: |
| | - name: distilled-indobert-classification |
| | results: |
| | - task: |
| | name: Text Classification |
| | type: text-classification |
| | dataset: |
| | name: indonlu |
| | type: indonlu |
| | args: smsa |
| | metrics: |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.9015873015873016 |
| | - name: F1 |
| | type: f1 |
| | value: 0.9014926755197933 |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # distilled-indobert-classification |
| |
|
| | This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the indonlu dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.6015 |
| | - Accuracy: 0.9016 |
| | - F1: 0.9015 |
| |
|
| | ## 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: 6e-05 |
| | - train_batch_size: 16 |
| | - eval_batch_size: 16 |
| | - seed: 33 |
| | - 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
| | | 1.0427 | 1.0 | 688 | 0.6306 | 0.8683 | 0.8684 | |
| | | 0.5332 | 2.0 | 1376 | 0.5621 | 0.8794 | 0.8779 | |
| | | 0.3021 | 3.0 | 2064 | 0.6785 | 0.8905 | 0.8896 | |
| | | 0.1851 | 4.0 | 2752 | 0.6085 | 0.8968 | 0.8959 | |
| | | 0.1152 | 5.0 | 3440 | 0.6015 | 0.9016 | 0.9015 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.18.0 |
| | - Pytorch 1.10.0+cu111 |
| | - Datasets 2.0.0 |
| | - Tokenizers 0.11.6 |
| |
|
