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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: gacha_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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# gacha_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: 0.4437 |
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- Accuracy: 0.8065 |
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- F1: 0.7877 |
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- Precision: 0.8105 |
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- Recall: 0.7662 |
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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: 10 |
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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 | 1.0 | 215 | 0.4437 | 0.8065 | 0.7877 | 0.8105 | 0.7662 | |
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| No log | 2.0 | 430 | 0.4728 | 0.8042 | 0.7766 | 0.8343 | 0.7264 | |
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| 0.343 | 3.0 | 645 | 0.7781 | 0.8089 | 0.7940 | 0.8020 | 0.7861 | |
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| 0.343 | 4.0 | 860 | 0.9427 | 0.8089 | 0.7842 | 0.8324 | 0.7413 | |
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| 0.0974 | 5.0 | 1075 | 1.1330 | 0.8089 | 0.7807 | 0.8439 | 0.7264 | |
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| 0.0974 | 6.0 | 1290 | 1.2451 | 0.8019 | 0.7781 | 0.8187 | 0.7413 | |
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| 0.0187 | 7.0 | 1505 | 1.2750 | 0.8205 | 0.7958 | 0.8523 | 0.7463 | |
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| 0.0187 | 8.0 | 1720 | 1.3551 | 0.8135 | 0.7849 | 0.8538 | 0.7264 | |
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| 0.0187 | 9.0 | 1935 | 1.3652 | 0.8205 | 0.7979 | 0.8444 | 0.7562 | |
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| 0.0018 | 10.0 | 2150 | 1.4262 | 0.8112 | 0.7817 | 0.8529 | 0.7214 | |
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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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