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---
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: 1.0710
- Accuracy: 0.9073
- F1 Macro: 0.9073
- F1 Weighted: 0.9073
- Precision Macro: 0.9074
- Recall Macro: 0.9072
- Precision Weighted: 0.9074
- Recall Weighted: 0.9073
## 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: 8.550119000665763e-05
- train_batch_size: 8
- eval_batch_size: 16
- 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: 13
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Weighted | Precision Macro | Recall Macro | Precision Weighted | Recall Weighted |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:--------:|:-----------:|:---------------:|:------------:|:------------------:|:---------------:|
| 0.0 | 1.8182 | 500 | 1.0710 | 0.9073 | 0.9073 | 0.9073 | 0.9074 | 0.9072 | 0.9074 | 0.9073 |
| 0.0281 | 3.6364 | 1000 | 1.0771 | 0.8927 | 0.8930 | 0.8931 | 0.8945 | 0.8927 | 0.8946 | 0.8927 |
| 0.0103 | 5.4545 | 1500 | 0.9934 | 0.8909 | 0.8910 | 0.8910 | 0.8914 | 0.8909 | 0.8915 | 0.8909 |
| 0.0763 | 7.2727 | 2000 | 0.8136 | 0.8891 | 0.8889 | 0.8890 | 0.8889 | 0.8890 | 0.8890 | 0.8891 |
| 0.0468 | 9.0909 | 2500 | 0.8967 | 0.8836 | 0.8835 | 0.8835 | 0.8855 | 0.8834 | 0.8854 | 0.8836 |
| 0.0429 | 10.9091 | 3000 | 0.9118 | 0.8909 | 0.8909 | 0.8909 | 0.8914 | 0.8908 | 0.8914 | 0.8909 |
| 0.0374 | 12.7273 | 3500 | 0.9128 | 0.8964 | 0.8962 | 0.8963 | 0.8965 | 0.8962 | 0.8965 | 0.8964 |
### Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 2.14.4
- Tokenizers 0.21.1
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