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update model card README.md
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README.md
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---
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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-TYDI-QA-ID-with-indobert-large-p2-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-TYDI-QA-ID-with-indobert-large-p2-with-ITTL-without-freeze-LR-1e-05
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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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- Loss: 1.1732
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- Exact Match: 60.2113
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- F1: 73.6360
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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: 8
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 16
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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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| 6.3258 | 0.5 | 19 | 3.5172 | 10.7394 | 21.8207 |
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| 6.3258 | 0.99 | 38 | 2.7869 | 18.3099 | 28.8508 |
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| 3.5421 | 1.5 | 57 | 2.3403 | 23.4155 | 35.8166 |
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| 3.5421 | 1.99 | 76 | 2.0205 | 30.2817 | 42.8646 |
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| 3.5421 | 2.5 | 95 | 1.7202 | 38.7324 | 51.9337 |
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| 2.0678 | 2.99 | 114 | 1.4839 | 44.5423 | 59.5131 |
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| 2.0678 | 3.5 | 133 | 1.3583 | 50.5282 | 64.3127 |
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| 1.4302 | 3.99 | 152 | 1.2706 | 52.2887 | 66.7363 |
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| 1.4302 | 4.5 | 171 | 1.2389 | 55.1056 | 69.3028 |
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| 1.4302 | 4.99 | 190 | 1.2065 | 55.8099 | 69.9972 |
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| 1.0965 | 5.5 | 209 | 1.1840 | 56.8662 | 70.7353 |
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| 1.0965 | 5.99 | 228 | 1.1887 | 58.4507 | 71.9049 |
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| 1.0965 | 6.5 | 247 | 1.1797 | 58.6268 | 72.5495 |
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| 0.9291 | 6.99 | 266 | 1.1685 | 59.6831 | 73.0495 |
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| 0.9291 | 7.5 | 285 | 1.1713 | 59.1549 | 73.1298 |
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| 0.839 | 7.99 | 304 | 1.1721 | 60.0352 | 73.0300 |
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| 0.839 | 8.5 | 323 | 1.1735 | 60.0352 | 73.5065 |
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| 0.839 | 8.99 | 342 | 1.1725 | 60.2113 | 73.6033 |
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| 0.7854 | 9.5 | 361 | 1.1738 | 60.2113 | 73.6432 |
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| 0.7854 | 9.99 | 380 | 1.1732 | 60.2113 | 73.6360 |
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### Framework versions
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- Transformers 4.26.1
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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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