---
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_3
  results: []
---

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# 22best_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: 0.9238
- Accuracy: 0.8815
- Precision: 0.8816
- Recall: 0.8882
- F1: 0.8802

## 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  | 0.4861          | 0.8009   | 0.8185    | 0.7929 | 0.7946 |
| No log        | 2.0   | 212  | 0.6104          | 0.7820   | 0.8077    | 0.7810 | 0.7751 |
| No log        | 3.0   | 318  | 0.6139          | 0.8246   | 0.8276    | 0.8147 | 0.8144 |
| No log        | 4.0   | 424  | 1.1299          | 0.8294   | 0.8478    | 0.8432 | 0.8281 |
| 0.4919        | 5.0   | 530  | 0.9623          | 0.8531   | 0.8547    | 0.8608 | 0.8511 |
| 0.4919        | 6.0   | 636  | 0.8674          | 0.8768   | 0.8771    | 0.8825 | 0.8750 |
| 0.4919        | 7.0   | 742  | 0.9238          | 0.8815   | 0.8816    | 0.8882 | 0.8802 |
| 0.4919        | 8.0   | 848  | 0.9191          | 0.8673   | 0.8658    | 0.8712 | 0.8649 |
| 0.4919        | 9.0   | 954  | 1.0218          | 0.8673   | 0.8681    | 0.8712 | 0.8647 |
| 0.0165        | 10.0  | 1060 | 1.0294          | 0.8720   | 0.8725    | 0.8769 | 0.8699 |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1