---
license: mit
base_model: ayameRushia/roberta-base-indonesian-sentiment-analysis-smsa
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: best_roberta_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_roberta_model_fold_1

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: 1.0321
- Accuracy: 0.8708
- Precision: 0.8700
- Recall: 0.8338
- F1: 0.8483

## 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   | 251  | 0.4388          | 0.8648   | 0.8750    | 0.8070 | 0.8273 |
| 0.4884        | 2.0   | 502  | 0.5608          | 0.8469   | 0.8258    | 0.8076 | 0.8143 |
| 0.4884        | 3.0   | 753  | 0.8603          | 0.8529   | 0.8604    | 0.7834 | 0.8026 |
| 0.1197        | 4.0   | 1004 | 0.7872          | 0.8648   | 0.8456    | 0.8444 | 0.8433 |
| 0.1197        | 5.0   | 1255 | 1.0494          | 0.8429   | 0.8142    | 0.8253 | 0.8155 |
| 0.0154        | 6.0   | 1506 | 1.0147          | 0.8688   | 0.8585    | 0.8296 | 0.8404 |
| 0.0154        | 7.0   | 1757 | 1.0059          | 0.8688   | 0.8618    | 0.8297 | 0.8426 |
| 0.0078        | 8.0   | 2008 | 1.0833          | 0.8549   | 0.8359    | 0.8251 | 0.8265 |
| 0.0078        | 9.0   | 2259 | 1.1080          | 0.8668   | 0.8612    | 0.8235 | 0.8369 |
| 0.0036        | 10.0  | 2510 | 1.0321          | 0.8708   | 0.8700    | 0.8338 | 0.8483 |


### Framework versions

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