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---
library_name: transformers
license: mit
base_model: flax-community/indonesian-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: indonesian-roberta-hate-speech-detection
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. -->
# indonesian-roberta-hate-speech-detection
This model is a fine-tuned version of [flax-community/indonesian-roberta-base](https://huggingface.co/flax-community/indonesian-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4118
- Accuracy: 0.826
- Auc: 0.903
- Precision: 0.8257
- Recall: 0.8257
- F1: 0.8256
## 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: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- 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: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Auc | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:|:---------:|:------:|:------:|
| 0.6653 | 1.0 | 188 | 0.5515 | 0.724 | 0.798 | 0.7243 | 0.7237 | 0.7238 |
| 0.5131 | 2.0 | 376 | 0.4578 | 0.783 | 0.875 | 0.7874 | 0.7830 | 0.7815 |
| 0.4307 | 3.0 | 564 | 0.4418 | 0.795 | 0.904 | 0.8137 | 0.7949 | 0.7928 |
| 0.3668 | 4.0 | 752 | 0.3804 | 0.835 | 0.916 | 0.8354 | 0.8349 | 0.8349 |
| 0.2991 | 5.0 | 940 | 0.4464 | 0.82 | 0.918 | 0.8345 | 0.8202 | 0.8190 |
| 0.2467 | 6.0 | 1128 | 0.4350 | 0.838 | 0.926 | 0.8482 | 0.8382 | 0.8375 |
| 0.2064 | 7.0 | 1316 | 0.4284 | 0.844 | 0.93 | 0.8515 | 0.8442 | 0.8438 |
| 0.1602 | 8.0 | 1504 | 0.4545 | 0.851 | 0.928 | 0.8520 | 0.8509 | 0.8509 |
| 0.1476 | 9.0 | 1692 | 0.4832 | 0.848 | 0.933 | 0.8545 | 0.8482 | 0.8479 |
| 0.117 | 10.0 | 1880 | 0.4632 | 0.855 | 0.932 | 0.8549 | 0.8549 | 0.8549 |
| 0.0925 | 11.0 | 2068 | 0.5501 | 0.86 | 0.933 | 0.8617 | 0.8602 | 0.8602 |
| 0.0811 | 12.0 | 2256 | 0.6097 | 0.849 | 0.933 | 0.8528 | 0.8489 | 0.8487 |
| 0.0702 | 13.0 | 2444 | 0.6568 | 0.85 | 0.933 | 0.8525 | 0.8495 | 0.8494 |
| 0.0588 | 14.0 | 2632 | 0.7092 | 0.844 | 0.93 | 0.8484 | 0.8442 | 0.8440 |
| 0.0572 | 15.0 | 2820 | 0.7012 | 0.855 | 0.933 | 0.8575 | 0.8549 | 0.8548 |
| 0.047 | 16.0 | 3008 | 0.7549 | 0.851 | 0.933 | 0.8545 | 0.8509 | 0.8507 |
| 0.0433 | 17.0 | 3196 | 0.7754 | 0.856 | 0.932 | 0.8593 | 0.8562 | 0.8561 |
| 0.044 | 18.0 | 3384 | 0.7868 | 0.85 | 0.932 | 0.8548 | 0.8502 | 0.8500 |
| 0.0408 | 19.0 | 3572 | 0.7890 | 0.855 | 0.932 | 0.8589 | 0.8549 | 0.8547 |
| 0.0412 | 20.0 | 3760 | 0.7870 | 0.855 | 0.932 | 0.8589 | 0.8549 | 0.8547 |
### Framework versions
- Transformers 4.52.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
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