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

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: 1.0692
- Accuracy: 0.8436
- F1 Macro: 0.8431
- F1 Weighted: 0.8433
- Precision Macro: 0.8432
- Recall Macro: 0.8434
- Precision Weighted: 0.8433
- Recall Weighted: 0.8436

## 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: 8.879626978799419e-06
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1 Macro | F1 Weighted | Precision Macro | Recall Macro | Precision Weighted | Recall Weighted |
|:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|:-----------:|:---------------:|:------------:|:------------------:|:---------------:|
| 0.035         | 1.8182 | 500  | 1.0247          | 0.8327   | 0.8321   | 0.8323      | 0.8325          | 0.8325       | 0.8325             | 0.8327          |
| 0.0829        | 3.6364 | 1000 | 1.0134          | 0.8273   | 0.8262   | 0.8263      | 0.8275          | 0.8270       | 0.8275             | 0.8273          |
| 0.1858        | 5.4545 | 1500 | 1.0692          | 0.8436   | 0.8431   | 0.8433      | 0.8432          | 0.8434       | 0.8433             | 0.8436          |
| 0.2844        | 7.2727 | 2000 | 0.9823          | 0.8255   | 0.8250   | 0.8251      | 0.8253          | 0.8253       | 0.8254             | 0.8255          |
| 0.3299        | 9.0909 | 2500 | 0.9626          | 0.8255   | 0.8251   | 0.8252      | 0.8253          | 0.8253       | 0.8254             | 0.8255          |


### Framework versions

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