---
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_4
  results: []
---

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# best_berita_bert_model_fold_4

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: 0.2443
- Accuracy: 0.9700
- Precision: 0.9703
- Recall: 0.9720
- F1: 0.9703

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.5455        | 1.0   | 601  | 0.3023          | 0.9217   | 0.9239    | 0.9245 | 0.9220 |
| 0.223         | 2.0   | 1202 | 0.2608          | 0.9517   | 0.9517    | 0.9527 | 0.9521 |
| 0.1061        | 3.0   | 1803 | 0.2175          | 0.9650   | 0.9651    | 0.9668 | 0.9653 |
| 0.0728        | 4.0   | 2404 | 0.3553          | 0.9509   | 0.9524    | 0.9539 | 0.9511 |
| 0.0342        | 5.0   | 3005 | 0.3587          | 0.9584   | 0.9592    | 0.9611 | 0.9585 |
| 0.0209        | 6.0   | 3606 | 0.5005          | 0.9409   | 0.9436    | 0.9446 | 0.9408 |
| 0.0159        | 7.0   | 4207 | 0.2443          | 0.9700   | 0.9703    | 0.9720 | 0.9703 |
| 0.0003        | 8.0   | 4808 | 0.3148          | 0.9659   | 0.9664    | 0.9681 | 0.9661 |
| 0.0           | 9.0   | 5409 | 0.3239          | 0.9650   | 0.9655    | 0.9673 | 0.9652 |
| 0.0           | 10.0  | 6010 | 0.3287          | 0.9659   | 0.9663    | 0.9681 | 0.9661 |


### Framework versions

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