---
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: 0.3507
- Accuracy: 0.9056
- F1 Macro: 0.9055
- F1 Weighted: 0.9055
- Precision Macro: 0.9057
- Recall Macro: 0.9056
- Precision Weighted: 0.9057
- Recall Weighted: 0.9056

## 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: 4e-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
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1 Macro | F1 Weighted | Precision Macro | Recall Macro | Precision Weighted | Recall Weighted |
|:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|:-----------:|:---------------:|:------------:|:------------------:|:---------------:|
| 0.4024        | 1.8519 | 500  | 0.2951          | 0.9      | 0.9002   | 0.9002      | 0.9011          | 0.9000       | 0.9011             | 0.9             |
| 0.3394        | 3.7037 | 1000 | 0.3384          | 0.8944   | 0.8946   | 0.8946      | 0.8960          | 0.8944       | 0.8960             | 0.8944          |
| 0.2395        | 5.5556 | 1500 | 0.3507          | 0.9056   | 0.9055   | 0.9055      | 0.9057          | 0.9056       | 0.9057             | 0.9056          |
| 0.2222        | 7.4074 | 2000 | 0.3621          | 0.9      | 0.9000   | 0.9000      | 0.9003          | 0.9          | 0.9003             | 0.9             |
| 0.1813        | 9.2593 | 2500 | 0.3718          | 0.8963   | 0.8963   | 0.8963      | 0.8963          | 0.8963       | 0.8963             | 0.8963          |


### Framework versions

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