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--- |
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library_name: transformers |
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license: mit |
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base_model: indobenchmark/indobert-large-p2 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: results |
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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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# results |
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This model is a fine-tuned version of [indobenchmark/indobert-large-p2](https://huggingface.co/indobenchmark/indobert-large-p2) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Accuracy: 0.8 |
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- F1 Weighted: 0.7852 |
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- Loss: 0.7316 |
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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: 2.7820079535067715e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 17 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Accuracy | F1 Weighted | Validation Loss | |
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|:-------------:|:-----:|:----:|:--------:|:-----------:|:---------------:| |
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| No log | 1.0 | 6 | 0.24 | 0.1029 | 1.2189 | |
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| 1.2118 | 2.0 | 12 | 0.32 | 0.2521 | 1.1035 | |
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| 1.2118 | 3.0 | 18 | 0.64 | 0.5214 | 1.0049 | |
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| 1.0516 | 4.0 | 24 | 0.68 | 0.6394 | 0.8500 | |
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| 1.0014 | 5.0 | 30 | 0.64 | 0.628 | 0.8799 | |
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| 1.0014 | 6.0 | 36 | 0.68 | 0.6835 | 0.7949 | |
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| 1.1235 | 7.0 | 42 | 0.72 | 0.6931 | 0.8320 | |
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| 1.1235 | 8.0 | 48 | 0.64 | 0.6368 | 0.7677 | |
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| 1.0837 | 9.0 | 54 | 0.8 | 0.7852 | 0.7316 | |
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| 0.9824 | 10.0 | 60 | 0.76 | 0.7324 | 0.7318 | |
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| 0.9824 | 11.0 | 66 | 0.72 | 0.6966 | 0.7191 | |
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| 0.8334 | 12.0 | 72 | 0.76 | 0.7346 | 0.7128 | |
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| 0.8334 | 13.0 | 78 | 0.68 | 0.6430 | 0.7165 | |
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| 0.7175 | 14.0 | 84 | 0.68 | 0.6430 | 0.7259 | |
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| 0.6813 | 15.0 | 90 | 0.68 | 0.6430 | 0.7139 | |
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| 0.6813 | 16.0 | 96 | 0.72 | 0.6981 | 0.6977 | |
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| 0.6765 | 17.0 | 102 | 0.72 | 0.6981 | 0.6941 | |
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### Framework versions |
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- Transformers 4.56.2 |
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- Pytorch 2.8.0+cu126 |
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- Datasets 4.0.0 |
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- Tokenizers 0.22.1 |
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