---
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_1
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# best_berita_bert_model_fold_1

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: 0.1540
- Accuracy: 0.9809
- Precision: 0.9800
- Recall: 0.9827
- F1: 0.9811

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.5387        | 1.0   | 601  | 0.2991          | 0.9218   | 0.9265    | 0.9197 | 0.9223 |
| 0.2444        | 2.0   | 1202 | 0.3248          | 0.9434   | 0.9447    | 0.9490 | 0.9439 |
| 0.1184        | 3.0   | 1803 | 0.2541          | 0.9642   | 0.9633    | 0.9670 | 0.9644 |
| 0.0406        | 4.0   | 2404 | 0.1509          | 0.9784   | 0.9783    | 0.9783 | 0.9783 |
| 0.0227        | 5.0   | 3005 | 0.2544          | 0.9692   | 0.9689    | 0.9720 | 0.9696 |
| 0.0157        | 6.0   | 3606 | 0.2683          | 0.9676   | 0.9668    | 0.9709 | 0.9677 |
| 0.009         | 7.0   | 4207 | 0.1540          | 0.9809   | 0.9800    | 0.9827 | 0.9811 |
| 0.0084        | 8.0   | 4808 | 0.2116          | 0.9784   | 0.9776    | 0.9806 | 0.9786 |
| 0.0007        | 9.0   | 5409 | 0.2715          | 0.9717   | 0.9711    | 0.9746 | 0.9720 |
| 0.0           | 10.0  | 6010 | 0.2566          | 0.9717   | 0.9711    | 0.9746 | 0.9720 |


### Framework versions

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