---
license: mit
base_model: ayameRushia/roberta-base-indonesian-sentiment-analysis-smsa
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: 22best_berita_roberta_model_fold_2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# 22best_berita_roberta_model_fold_2

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: 0.5228
- Accuracy: 0.8396
- Precision: 0.8466
- Recall: 0.8449
- F1: 0.8396

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 1.0   | 106  | 0.6002          | 0.7594   | 0.7946    | 0.7514 | 0.7518 |
| No log        | 2.0   | 212  | 0.5228          | 0.8396   | 0.8466    | 0.8449 | 0.8396 |
| No log        | 3.0   | 318  | 1.1057          | 0.7877   | 0.8315    | 0.7948 | 0.7870 |
| No log        | 4.0   | 424  | 1.1409          | 0.8208   | 0.8436    | 0.8303 | 0.8223 |
| 0.3962        | 5.0   | 530  | 1.2078          | 0.8066   | 0.8101    | 0.8118 | 0.8061 |
| 0.3962        | 6.0   | 636  | 1.6439          | 0.7877   | 0.8159    | 0.7772 | 0.7847 |
| 0.3962        | 7.0   | 742  | 1.4679          | 0.8160   | 0.8250    | 0.8073 | 0.8115 |
| 0.3962        | 8.0   | 848  | 1.2632          | 0.8396   | 0.8440    | 0.8335 | 0.8367 |
| 0.3962        | 9.0   | 954  | 1.2872          | 0.8396   | 0.8455    | 0.8328 | 0.8364 |
| 0.0113        | 10.0  | 1060 | 1.2936          | 0.8396   | 0.8455    | 0.8328 | 0.8364 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1