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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-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-IDK-MRC-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: 1.2364 |
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- Exact Match: 50.2618 |
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- F1: 57.5214 |
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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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| 6.151 | 0.49 | 36 | 2.7223 | 32.5916 | 35.4445 | |
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| 3.5424 | 0.98 | 72 | 2.0664 | 24.2147 | 31.0371 | |
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| 2.2082 | 1.48 | 108 | 1.7388 | 28.0105 | 37.2690 | |
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| 2.2082 | 1.97 | 144 | 1.4742 | 37.0419 | 45.3625 | |
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| 1.6932 | 2.46 | 180 | 1.3193 | 43.3246 | 51.1270 | |
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| 1.3154 | 2.95 | 216 | 1.2731 | 46.2042 | 53.5503 | |
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| 1.1699 | 3.45 | 252 | 1.2327 | 46.4660 | 53.5656 | |
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| 1.1699 | 3.94 | 288 | 1.1998 | 48.1675 | 55.1907 | |
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| 1.0749 | 4.44 | 324 | 1.1949 | 51.0471 | 57.7164 | |
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| 0.9423 | 4.93 | 360 | 1.1855 | 50.6545 | 57.3903 | |
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| 0.9423 | 5.42 | 396 | 1.1931 | 51.3089 | 58.5981 | |
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| 0.9036 | 5.91 | 432 | 1.2045 | 50.3927 | 57.7468 | |
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| 0.8324 | 6.41 | 468 | 1.2363 | 48.2984 | 55.5302 | |
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| 0.7846 | 6.9 | 504 | 1.2364 | 50.2618 | 57.5214 | |
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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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