---
license: mit
base_model: ayameRushia/roberta-base-indonesian-sentiment-analysis-smsa
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: best_berita_roberta_model_fold_2
  results: []
---

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# best_berita_roberta_model_fold_2

This model is a fine-tuned version of [ayameRushia/roberta-base-indonesian-sentiment-analysis-smsa](https://huggingface.co/ayameRushia/roberta-base-indonesian-sentiment-analysis-smsa) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1019
- Accuracy: 0.9884
- Precision: 0.9882
- Recall: 0.9889
- F1: 0.9884

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.6027        | 1.0   | 601  | 0.4467          | 0.8943   | 0.9036    | 0.8947 | 0.8951 |
| 0.2296        | 2.0   | 1202 | 0.3961          | 0.9218   | 0.9282    | 0.9262 | 0.9213 |
| 0.1253        | 3.0   | 1803 | 0.2066          | 0.9651   | 0.9655    | 0.9670 | 0.9652 |
| 0.0869        | 4.0   | 2404 | 0.1721          | 0.9684   | 0.9691    | 0.9699 | 0.9688 |
| 0.0188        | 5.0   | 3005 | 0.1239          | 0.9842   | 0.9840    | 0.9850 | 0.9843 |
| 0.0049        | 6.0   | 3606 | 0.1186          | 0.9825   | 0.9823    | 0.9835 | 0.9826 |
| 0.0057        | 7.0   | 4207 | 0.1019          | 0.9884   | 0.9882    | 0.9889 | 0.9884 |
| 0.0043        | 8.0   | 4808 | 0.3787          | 0.9534   | 0.9549    | 0.9562 | 0.9534 |
| 0.0047        | 9.0   | 5409 | 0.2094          | 0.9759   | 0.9759    | 0.9772 | 0.9760 |
| 0.0007        | 10.0  | 6010 | 0.2093          | 0.9759   | 0.9759    | 0.9772 | 0.9760 |


### Framework versions

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