---
library_name: transformers
license: mit
base_model: cahya/bert-base-indonesian-1.5G
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: bert-base-indonesian-1.5G-multilabel-indonesian-hate-speech-modified-v3
  results: []
---

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# bert-base-indonesian-1.5G-multilabel-indonesian-hate-speech-modified-v3

This model is a fine-tuned version of [cahya/bert-base-indonesian-1.5G](https://huggingface.co/cahya/bert-base-indonesian-1.5G) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2123
- F1: 0.7965
- Roc Auc: 0.8744
- Accuracy: 0.7115

## 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: 2e-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: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.2695        | 1.0   | 1317 | 0.2122          | 0.7390 | 0.8253  | 0.6234   |
| 0.1976        | 2.0   | 2634 | 0.2010          | 0.7734 | 0.8606  | 0.6446   |
| 0.1602        | 3.0   | 3951 | 0.1976          | 0.7902 | 0.8779  | 0.6864   |
| 0.1263        | 4.0   | 5268 | 0.2062          | 0.7930 | 0.8660  | 0.7175   |
| 0.1022        | 5.0   | 6585 | 0.2123          | 0.7965 | 0.8744  | 0.7115   |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.7.0+cu128
- Datasets 3.6.0
- Tokenizers 0.21.1