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---
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
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