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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-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-TYDI-QA-ID-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: 1.2740 |
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- Exact Match: 56.0847 |
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- F1: 70.6246 |
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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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| 6.306 | 0.5 | 19 | 3.7982 | 6.5256 | 20.3655 | |
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| 6.306 | 1.0 | 38 | 2.8932 | 14.1093 | 26.0679 | |
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| 3.9254 | 1.5 | 57 | 2.4798 | 19.4004 | 32.1438 | |
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| 3.9254 | 2.0 | 76 | 2.2955 | 26.1023 | 37.6331 | |
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| 3.9254 | 2.5 | 95 | 2.1688 | 26.9841 | 39.2632 | |
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| 2.4328 | 3.0 | 114 | 2.0701 | 30.1587 | 41.3438 | |
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| 2.4328 | 3.5 | 133 | 1.9789 | 33.1570 | 45.0539 | |
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| 2.1127 | 4.0 | 152 | 1.8465 | 37.2134 | 48.9042 | |
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| 2.1127 | 4.5 | 171 | 1.7699 | 38.9771 | 50.9760 | |
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| 2.1127 | 5.0 | 190 | 1.6885 | 41.0935 | 54.1550 | |
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| 1.7875 | 5.5 | 209 | 1.5785 | 45.1499 | 58.6783 | |
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| 1.7875 | 6.0 | 228 | 1.4954 | 49.2063 | 62.7869 | |
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| 1.7875 | 6.5 | 247 | 1.4186 | 51.8519 | 65.7461 | |
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| 1.5267 | 7.0 | 266 | 1.3734 | 53.4392 | 67.6141 | |
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| 1.5267 | 7.5 | 285 | 1.3419 | 54.1446 | 68.2563 | |
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| 1.3317 | 8.0 | 304 | 1.3116 | 55.5556 | 69.1996 | |
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| 1.3317 | 8.5 | 323 | 1.2936 | 56.0847 | 69.9806 | |
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| 1.3317 | 9.0 | 342 | 1.2900 | 56.2610 | 70.1634 | |
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| 1.2556 | 9.5 | 361 | 1.2771 | 55.7319 | 70.1143 | |
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| 1.2556 | 10.0 | 380 | 1.2740 | 56.0847 | 70.6246 | |
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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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