---
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: 22best_berita_bert_model_fold_3
  results: []
---

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# 22best_berita_bert_model_fold_3

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: 1.6989
- Accuracy: 0.7915
- Precision: 0.8007
- Recall: 0.8070
- F1: 0.7911

## 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  | 0.5874          | 0.7346   | 0.7387    | 0.7359 | 0.7275 |
| No log        | 2.0   | 212  | 0.8650          | 0.7678   | 0.7865    | 0.7559 | 0.7646 |
| No log        | 3.0   | 318  | 1.0826          | 0.7725   | 0.7782    | 0.7795 | 0.7730 |
| No log        | 4.0   | 424  | 2.0331          | 0.6967   | 0.7339    | 0.7168 | 0.6891 |
| 0.3602        | 5.0   | 530  | 1.6682          | 0.7678   | 0.7803    | 0.7796 | 0.7682 |
| 0.3602        | 6.0   | 636  | 1.6989          | 0.7915   | 0.8007    | 0.8070 | 0.7911 |
| 0.3602        | 7.0   | 742  | 1.7597          | 0.7725   | 0.7742    | 0.7811 | 0.7709 |
| 0.3602        | 8.0   | 848  | 1.8278          | 0.7725   | 0.7742    | 0.7811 | 0.7709 |
| 0.3602        | 9.0   | 954  | 1.8531          | 0.7725   | 0.7742    | 0.7811 | 0.7709 |
| 0.0126        | 10.0  | 1060 | 1.8599          | 0.7725   | 0.7742    | 0.7811 | 0.7709 |


### Framework versions

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