| --- |
| tags: |
| - generated_from_trainer |
| datasets: |
| - indonlu |
| metrics: |
| - accuracy |
| - f1 |
| model-index: |
| - name: distilled-optimized-indobert-classification |
| results: |
| - task: |
| name: Text Classification |
| type: text-classification |
| dataset: |
| name: indonlu |
| type: indonlu |
| args: smsa |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.9 |
| - name: F1 |
| type: f1 |
| value: 0.8994069293432798 |
| --- |
| |
| <!-- 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-optimized-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: 0.7397 |
| - Accuracy: 0.9 |
| - F1: 0.8994 |
|
|
| ## 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: 4.315104717136378e-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: 9 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
| | 0.128 | 1.0 | 688 | 0.8535 | 0.8913 | 0.8917 | |
| | 0.1475 | 2.0 | 1376 | 0.9171 | 0.8913 | 0.8913 | |
| | 0.0997 | 3.0 | 2064 | 0.7799 | 0.8960 | 0.8951 | |
| | 0.0791 | 4.0 | 2752 | 0.7179 | 0.9032 | 0.9023 | |
| | 0.0577 | 5.0 | 3440 | 0.6908 | 0.9063 | 0.9055 | |
| | 0.0406 | 6.0 | 4128 | 0.7613 | 0.8992 | 0.8986 | |
| | 0.0275 | 7.0 | 4816 | 0.7502 | 0.8992 | 0.8989 | |
| | 0.023 | 8.0 | 5504 | 0.7408 | 0.8976 | 0.8969 | |
| | 0.0169 | 9.0 | 6192 | 0.7397 | 0.9 | 0.8994 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.18.0 |
| - Pytorch 1.10.0+cu111 |
| - Datasets 2.1.0 |
| - Tokenizers 0.12.1 |
|
|
