---
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_1
  results: []
---

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# 22best_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: 1.3730
- Accuracy: 0.8302
- Precision: 0.8319
- Recall: 0.8468
- F1: 0.8309

## 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  | 0.7262          | 0.7123   | 0.7513    | 0.7032 | 0.6764 |
| No log        | 2.0   | 212  | 0.6140          | 0.8019   | 0.8154    | 0.8273 | 0.8032 |
| No log        | 3.0   | 318  | 1.0427          | 0.7594   | 0.7665    | 0.7740 | 0.7618 |
| No log        | 4.0   | 424  | 0.9092          | 0.8208   | 0.8191    | 0.8333 | 0.8214 |
| 0.4074        | 5.0   | 530  | 1.4762          | 0.7830   | 0.8110    | 0.8148 | 0.7838 |
| 0.4074        | 6.0   | 636  | 1.3960          | 0.7925   | 0.7954    | 0.8034 | 0.7923 |
| 0.4074        | 7.0   | 742  | 1.3455          | 0.8255   | 0.8282    | 0.8421 | 0.8258 |
| 0.4074        | 8.0   | 848  | 1.3730          | 0.8302   | 0.8319    | 0.8468 | 0.8309 |
| 0.4074        | 9.0   | 954  | 1.3804          | 0.8302   | 0.8319    | 0.8468 | 0.8309 |
| 0.0158        | 10.0  | 1060 | 1.3823          | 0.8302   | 0.8319    | 0.8468 | 0.8309 |


### Framework versions

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