---
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_5
  results: []
---

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# 22best_berita_roberta_model_fold_5

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: 1.0203
- Accuracy: 0.8578
- Precision: 0.8590
- Recall: 0.8528
- F1: 0.8538

## 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  | 1.1381          | 0.5403   | 0.7643    | 0.5153 | 0.4656 |
| No log        | 2.0   | 212  | 1.0541          | 0.7536   | 0.7980    | 0.7549 | 0.7368 |
| No log        | 3.0   | 318  | 0.8831          | 0.7867   | 0.8067    | 0.7938 | 0.7852 |
| No log        | 4.0   | 424  | 1.2855          | 0.7630   | 0.8040    | 0.7730 | 0.7635 |
| 0.4634        | 5.0   | 530  | 0.9810          | 0.8483   | 0.8576    | 0.8458 | 0.8472 |
| 0.4634        | 6.0   | 636  | 1.1545          | 0.8341   | 0.8493    | 0.8254 | 0.8260 |
| 0.4634        | 7.0   | 742  | 1.0520          | 0.8483   | 0.8509    | 0.8443 | 0.8451 |
| 0.4634        | 8.0   | 848  | 1.0203          | 0.8578   | 0.8590    | 0.8528 | 0.8538 |
| 0.4634        | 9.0   | 954  | 1.0454          | 0.8578   | 0.8588    | 0.8530 | 0.8542 |
| 0.0229        | 10.0  | 1060 | 1.0505          | 0.8578   | 0.8588    | 0.8530 | 0.8542 |


### Framework versions

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