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license: mit |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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model-index: |
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- name: fine-tuned-DatasetQAS-IDK-MRC-with-indobert-base-uncased-with-ITTL-without-freeze-LR-1e-05 |
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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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# fine-tuned-DatasetQAS-IDK-MRC-with-indobert-base-uncased-with-ITTL-without-freeze-LR-1e-05 |
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This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0883 |
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- Exact Match: 65.4450 |
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- F1: 70.8022 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 32 |
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- total_train_batch_size: 128 |
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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 | Exact Match | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:-----------:|:-------:| |
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| 6.2828 | 0.49 | 36 | 2.6576 | 49.7382 | 49.7756 | |
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| 3.794 | 0.98 | 72 | 1.9936 | 49.8691 | 49.8691 | |
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| 2.2086 | 1.47 | 108 | 1.8469 | 49.2147 | 49.5992 | |
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| 2.2086 | 1.96 | 144 | 1.7445 | 50.5236 | 51.9107 | |
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| 2.0123 | 2.46 | 180 | 1.6178 | 49.8691 | 54.4031 | |
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| 1.7802 | 2.95 | 216 | 1.4800 | 54.8429 | 58.8765 | |
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| 1.5945 | 3.44 | 252 | 1.3337 | 57.5916 | 62.8748 | |
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| 1.5945 | 3.93 | 288 | 1.3153 | 58.2461 | 63.4667 | |
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| 1.4083 | 4.42 | 324 | 1.2184 | 59.8168 | 65.4478 | |
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| 1.2513 | 4.91 | 360 | 1.2348 | 58.3770 | 64.1649 | |
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| 1.2513 | 5.4 | 396 | 1.1415 | 62.6963 | 68.0081 | |
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| 1.161 | 5.89 | 432 | 1.1463 | 62.6963 | 67.6633 | |
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| 1.0755 | 6.38 | 468 | 1.1126 | 63.4817 | 68.7554 | |
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| 1.0099 | 6.87 | 504 | 1.0823 | 63.4817 | 68.9182 | |
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| 1.0099 | 7.37 | 540 | 1.0547 | 66.2304 | 71.2423 | |
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| 0.9815 | 7.86 | 576 | 1.0835 | 63.4817 | 69.1031 | |
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| 0.9464 | 8.35 | 612 | 1.0644 | 66.3613 | 71.4374 | |
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| 0.9464 | 8.84 | 648 | 1.0642 | 65.9686 | 71.2813 | |
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| 0.9325 | 9.33 | 684 | 1.0786 | 65.4450 | 70.8541 | |
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| 0.913 | 9.82 | 720 | 1.0883 | 65.4450 | 70.8022 | |
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### Framework versions |
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- Transformers 4.27.4 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.2.0 |
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- Tokenizers 0.13.2 |
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