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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: 1.0515 |
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- Exact Match: 65.9686 |
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- F1: 71.4684 |
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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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| 6.1822 | 0.49 | 36 | 2.5004 | 49.8691 | 49.8691 | |
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| 3.6893 | 0.98 | 72 | 1.9896 | 49.8691 | 49.8691 | |
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| 2.2116 | 1.48 | 108 | 1.8516 | 49.2147 | 49.7070 | |
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| 2.2116 | 1.97 | 144 | 1.7367 | 50.1309 | 52.0399 | |
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| 1.9945 | 2.46 | 180 | 1.5956 | 51.7016 | 56.3444 | |
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| 1.7443 | 2.95 | 216 | 1.4508 | 54.9738 | 59.4030 | |
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| 1.5782 | 3.45 | 252 | 1.3234 | 59.9476 | 65.0857 | |
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| 1.5782 | 3.94 | 288 | 1.2652 | 58.1152 | 63.9949 | |
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| 1.4004 | 4.44 | 324 | 1.1784 | 62.0419 | 67.5268 | |
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| 1.241 | 4.93 | 360 | 1.1573 | 60.4712 | 66.5284 | |
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| 1.241 | 5.42 | 396 | 1.1217 | 62.4346 | 67.8923 | |
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| 1.1603 | 5.91 | 432 | 1.0997 | 63.3508 | 68.7351 | |
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| 1.0849 | 6.41 | 468 | 1.0832 | 64.3979 | 69.5781 | |
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| 1.0209 | 6.9 | 504 | 1.0773 | 64.0052 | 69.3072 | |
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| 1.0209 | 7.4 | 540 | 1.0500 | 65.0524 | 70.4355 | |
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| 0.9802 | 7.89 | 576 | 1.0644 | 65.3141 | 70.7507 | |
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| 0.9536 | 8.38 | 612 | 1.0516 | 65.5759 | 70.9704 | |
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| 0.9536 | 8.87 | 648 | 1.0395 | 65.4450 | 71.2117 | |
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| 0.9319 | 9.37 | 684 | 1.0411 | 65.8377 | 71.3692 | |
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| 0.9091 | 9.86 | 720 | 1.0515 | 65.9686 | 71.4684 | |
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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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