---
license: mit
base_model: ayameRushia/bert-base-indonesian-1.5G-sentiment-analysis-smsa
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: best_berita_bert_model_fold_5
  results: []
---

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# best_berita_bert_model_fold_5

This model is a fine-tuned version of [ayameRushia/bert-base-indonesian-1.5G-sentiment-analysis-smsa](https://huggingface.co/ayameRushia/bert-base-indonesian-1.5G-sentiment-analysis-smsa) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0859
- Accuracy: 0.9833
- Precision: 0.9834
- Recall: 0.9830
- F1: 0.9832

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.5542        | 1.0   | 601  | 0.3531          | 0.9142   | 0.9204    | 0.9129 | 0.9108 |
| 0.266         | 2.0   | 1202 | 0.1554          | 0.9625   | 0.9634    | 0.9620 | 0.9618 |
| 0.1215        | 3.0   | 1803 | 0.0859          | 0.9833   | 0.9834    | 0.9830 | 0.9832 |
| 0.0721        | 4.0   | 2404 | 0.1634          | 0.9725   | 0.9736    | 0.9721 | 0.9720 |
| 0.0227        | 5.0   | 3005 | 0.4132          | 0.9484   | 0.9527    | 0.9475 | 0.9470 |
| 0.0242        | 6.0   | 3606 | 0.2816          | 0.9609   | 0.9632    | 0.9602 | 0.9599 |
| 0.0083        | 7.0   | 4207 | 0.2295          | 0.9717   | 0.9731    | 0.9712 | 0.9712 |
| 0.0           | 8.0   | 4808 | 0.1644          | 0.9792   | 0.9800    | 0.9788 | 0.9789 |
| 0.0002        | 9.0   | 5409 | 0.1868          | 0.9784   | 0.9792    | 0.9780 | 0.9781 |
| 0.0           | 10.0  | 6010 | 0.1901          | 0.9784   | 0.9792    | 0.9780 | 0.9781 |


### Framework versions

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