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--- |
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license: mit |
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base_model: indobenchmark/indobert-large-p1 |
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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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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: indobert-large-p1-reddit-indonesia-sarcastic |
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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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# indobert-large-p1-reddit-indonesia-sarcastic |
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This model is a fine-tuned version of [indobenchmark/indobert-large-p1](https://huggingface.co/indobenchmark/indobert-large-p1) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4486 |
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- Accuracy: 0.7911 |
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- F1: 0.6184 |
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- Precision: 0.5690 |
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- Recall: 0.6771 |
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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: 1e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 64 |
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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: 100.0 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 0.4573 | 1.0 | 309 | 0.4251 | 0.7966 | 0.5684 | 0.6058 | 0.5354 | |
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| 0.3274 | 2.0 | 618 | 0.4458 | 0.7824 | 0.5955 | 0.5567 | 0.6402 | |
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| 0.1999 | 3.0 | 927 | 0.5890 | 0.8065 | 0.5412 | 0.6653 | 0.4561 | |
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| 0.0864 | 4.0 | 1236 | 0.8080 | 0.8023 | 0.5536 | 0.6360 | 0.4901 | |
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| 0.0391 | 5.0 | 1545 | 1.1299 | 0.7895 | 0.5293 | 0.6007 | 0.4731 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.1+cu121 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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