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--- |
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license: mit |
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base_model: indobenchmark/indobert-base-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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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: reward_model |
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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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# reward_model |
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This model is a fine-tuned version of [indobenchmark/indobert-base-p2](https://huggingface.co/indobenchmark/indobert-base-p2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6126 |
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- Accuracy: 0.8927 |
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- F1: 0.8906 |
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- Precision: 0.8964 |
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- Recall: 0.8878 |
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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: 16 |
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- eval_batch_size: 16 |
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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: linear |
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- num_epochs: 5 |
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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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| No log | 0.56 | 50 | 0.3455 | 0.8757 | 0.8736 | 0.8780 | 0.8713 | |
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| No log | 1.12 | 100 | 0.3013 | 0.8701 | 0.8687 | 0.8692 | 0.8683 | |
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| No log | 1.69 | 150 | 0.3773 | 0.8644 | 0.8616 | 0.8683 | 0.8588 | |
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| No log | 2.25 | 200 | 0.3923 | 0.8927 | 0.8906 | 0.8964 | 0.8878 | |
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| No log | 2.81 | 250 | 0.3634 | 0.8927 | 0.8913 | 0.8931 | 0.8900 | |
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| No log | 3.37 | 300 | 0.4554 | 0.8983 | 0.8971 | 0.8982 | 0.8963 | |
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| No log | 3.93 | 350 | 0.5317 | 0.8870 | 0.8851 | 0.8896 | 0.8827 | |
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| No log | 4.49 | 400 | 0.5834 | 0.8870 | 0.8851 | 0.8896 | 0.8827 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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