---
library_name: transformers
license: mit
base_model: w11wo/indonesian-roberta-base-sentiment-classifier
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: results
  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. -->

# results

This model is a fine-tuned version of [w11wo/indonesian-roberta-base-sentiment-classifier](https://huggingface.co/w11wo/indonesian-roberta-base-sentiment-classifier) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2566
- Accuracy: 0.9217
- F1 Macro: 0.9216
- F1 Weighted: 0.9216
- Precision Macro: 0.9222
- Recall Macro: 0.9217
- Precision Weighted: 0.9222
- Recall Weighted: 0.9217

## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1 Macro | F1 Weighted | Precision Macro | Recall Macro | Precision Weighted | Recall Weighted |
|:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|:-----------:|:---------------:|:------------:|:------------------:|:---------------:|
| 0.2227        | 1.0438 | 500  | 0.2626          | 0.9228   | 0.9227   | 0.9227      | 0.9236          | 0.9227       | 0.9236             | 0.9228          |
| 0.2623        | 2.0877 | 1000 | 0.2595          | 0.9217   | 0.9216   | 0.9216      | 0.9220          | 0.9217       | 0.9220             | 0.9217          |
| 0.2573        | 3.1315 | 1500 | 0.2587          | 0.9217   | 0.9216   | 0.9216      | 0.9222          | 0.9217       | 0.9222             | 0.9217          |
| 0.2262        | 4.1754 | 2000 | 0.2566          | 0.9217   | 0.9216   | 0.9216      | 0.9222          | 0.9217       | 0.9222             | 0.9217          |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 2.14.4
- Tokenizers 0.21.1