---
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