| --- |
| license: mit |
| base_model: ayameRushia/roberta-base-indonesian-sentiment-analysis-smsa |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - precision |
| - recall |
| - f1 |
| model-index: |
| - name: best_berita_roberta_model_fold_3 |
| 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. --> |
|
|
| # best_berita_roberta_model_fold_3 |
| |
| This model is a fine-tuned version of [ayameRushia/roberta-base-indonesian-sentiment-analysis-smsa](https://huggingface.co/ayameRushia/roberta-base-indonesian-sentiment-analysis-smsa) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.1247 |
| - Accuracy: 0.9833 |
| - Precision: 0.9833 |
| - Recall: 0.9836 |
| - F1: 0.9834 |
| |
| ## 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: 5e-05 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 10 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
| | 0.5662 | 1.0 | 601 | 0.3954 | 0.9142 | 0.9181 | 0.9155 | 0.9140 | |
| | 0.2162 | 2.0 | 1202 | 0.2580 | 0.9525 | 0.9532 | 0.9532 | 0.9525 | |
| | 0.1503 | 3.0 | 1803 | 0.1226 | 0.9825 | 0.9826 | 0.9827 | 0.9826 | |
| | 0.0849 | 4.0 | 2404 | 0.3352 | 0.9609 | 0.9615 | 0.9615 | 0.9609 | |
| | 0.0257 | 5.0 | 3005 | 0.1938 | 0.9725 | 0.9728 | 0.9730 | 0.9725 | |
| | 0.0277 | 6.0 | 3606 | 0.1247 | 0.9833 | 0.9833 | 0.9836 | 0.9834 | |
| | 0.0123 | 7.0 | 4207 | 0.1741 | 0.9800 | 0.9801 | 0.9803 | 0.9800 | |
| | 0.0061 | 8.0 | 4808 | 0.1870 | 0.9792 | 0.9793 | 0.9795 | 0.9792 | |
| | 0.0 | 9.0 | 5409 | 0.1793 | 0.9817 | 0.9817 | 0.9820 | 0.9817 | |
| | 0.0 | 10.0 | 6010 | 0.1802 | 0.9817 | 0.9817 | 0.9820 | 0.9817 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.41.2 |
| - Pytorch 2.1.2 |
| - Datasets 2.19.2 |
| - Tokenizers 0.19.1 |
| |
