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README.md
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license: mit
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base_model: Amadeus99/indonesia-election-topic-classification-undersampling-large-2
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tags:
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- generated_from_trainer
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model-index:
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- name: final
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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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# final
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This model is a fine-tuned version of [Amadeus99/indonesia-election-topic-classification-undersampling-large-2](https://huggingface.co/Amadeus99/indonesia-election-topic-classification-undersampling-large-2) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.3415
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- F1 macro: 0.6715
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- Weighted: 0.7528
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- Balanced accuracy: 0.8185
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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: 5e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | F1 macro | Weighted | Balanced accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------------:|
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| 0.836 | 1.0 | 39 | 1.0747 | 0.5558 | 0.6819 | 0.7094 |
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| 0.5943 | 2.0 | 78 | 0.8587 | 0.6173 | 0.7475 | 0.8326 |
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| 0.3032 | 3.0 | 117 | 0.6988 | 0.7499 | 0.7999 | 0.8840 |
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| 0.1264 | 4.0 | 156 | 0.8485 | 0.7286 | 0.7915 | 0.8797 |
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| 0.0819 | 5.0 | 195 | 0.9576 | 0.7197 | 0.7812 | 0.8816 |
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| 0.0084 | 6.0 | 234 | 1.0325 | 0.7060 | 0.7874 | 0.8264 |
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| 0.037 | 7.0 | 273 | 1.0728 | 0.7098 | 0.7940 | 0.8261 |
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| 0.0176 | 8.0 | 312 | 1.0690 | 0.7148 | 0.7961 | 0.8350 |
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| 0.011 | 9.0 | 351 | 1.1196 | 0.7133 | 0.7913 | 0.8341 |
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| 0.003 | 10.0 | 390 | 1.1165 | 0.7133 | 0.7913 | 0.8341 |
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### Framework versions
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- Transformers 4.41.2
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- Pytorch 2.3.0+cu121
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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