| --- |
| 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_4 |
| 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. --> |
|
|
| [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>]() |
| # best_berita_roberta_model_fold_4 |
| |
| 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: 0.1309 |
| - Accuracy: 0.9808 |
| - Precision: 0.9814 |
| - Recall: 0.9809 |
| - F1: 0.9811 |
| |
| ## 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 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
| | 0.6294 | 1.0 | 601 | 0.2849 | 0.9217 | 0.9233 | 0.9253 | 0.9217 | |
| | 0.301 | 2.0 | 1202 | 0.3187 | 0.9409 | 0.9409 | 0.9428 | 0.9413 | |
| | 0.1565 | 3.0 | 1803 | 0.2576 | 0.9609 | 0.9609 | 0.9626 | 0.9611 | |
| | 0.0962 | 4.0 | 2404 | 0.3011 | 0.9567 | 0.9577 | 0.9593 | 0.9569 | |
| | 0.0322 | 5.0 | 3005 | 0.1309 | 0.9808 | 0.9814 | 0.9809 | 0.9811 | |
| | 0.0218 | 6.0 | 3606 | 0.2434 | 0.9667 | 0.9672 | 0.9684 | 0.9670 | |
| | 0.0127 | 7.0 | 4207 | 0.3759 | 0.9492 | 0.9509 | 0.9524 | 0.9492 | |
| | 0.0136 | 8.0 | 4808 | 0.3133 | 0.9642 | 0.9650 | 0.9664 | 0.9645 | |
| | 0.0024 | 9.0 | 5409 | 0.2968 | 0.9667 | 0.9674 | 0.9687 | 0.9671 | |
| | 0.0026 | 10.0 | 6010 | 0.2784 | 0.9684 | 0.9690 | 0.9703 | 0.9687 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.42.3 |
| - Pytorch 2.1.2 |
| - Datasets 2.20.0 |
| - Tokenizers 0.19.1 |
| |
