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---
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library_name: transformers
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license: mit
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base_model: cahya/bert-base-indonesian-1.5G
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tags:
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- generated_from_trainer
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metrics:
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- f1
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- accuracy
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model-index:
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- name: bert-base-indonesian-1.5G-multilabel-indonesian-hate-speech-new
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# bert-base-indonesian-1.5G-multilabel-indonesian-hate-speech-new
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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.
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It achieves the following results on the evaluation set:
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- Loss: 0.3641
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- F1: 0.7802
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- Roc Auc: 0.8639
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- Accuracy: 0.7156
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- num_epochs: 15
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
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| 0.3106 | 1.0 | 659 | 0.2504 | 0.6779 | 0.7832 | 0.5978 |
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| 0.2235 | 2.0 | 1318 | 0.2113 | 0.7466 | 0.8392 | 0.6441 |
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| 0.1722 | 3.0 | 1977 | 0.2283 | 0.7511 | 0.8493 | 0.6581 |
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| 0.097 | 4.0 | 2636 | 0.2421 | 0.7626 | 0.8490 | 0.6874 |
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| 0.0643 | 5.0 | 3295 | 0.2727 | 0.7584 | 0.8417 | 0.6938 |
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| 0.0572 | 6.0 | 3954 | 0.2817 | 0.7662 | 0.8662 | 0.6737 |
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| 0.0304 | 7.0 | 4613 | 0.3075 | 0.7606 | 0.8475 | 0.6879 |
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| 0.021 | 8.0 | 5272 | 0.3195 | 0.7697 | 0.8626 | 0.6932 |
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| 0.0157 | 9.0 | 5931 | 0.3347 | 0.7663 | 0.8477 | 0.7052 |
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| 0.0095 | 10.0 | 6590 | 0.3353 | 0.7759 | 0.8598 | 0.7118 |
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| 0.0086 | 11.0 | 7249 | 0.3467 | 0.7768 | 0.8590 | 0.7136 |
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| 0.0063 | 12.0 | 7908 | 0.3503 | 0.7795 | 0.8644 | 0.7128 |
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| 0.0046 | 13.0 | 8567 | 0.3577 | 0.7797 | 0.8613 | 0.7153 |
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| 0.0037 | 14.0 | 9226 | 0.3622 | 0.7801 | 0.8674 | 0.7115 |
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| 0.0046 | 15.0 | 9885 | 0.3641 | 0.7802 | 0.8639 | 0.7156 |
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### Framework versions
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- Transformers 4.51.3
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- Pytorch 2.7.0+cu128
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- Datasets 3.6.0
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- Tokenizers 0.21.1
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