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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: 1.0942 |
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- Exact Match: 64.3979 |
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- F1: 69.8535 |
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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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| 6.1478 | 0.49 | 36 | 2.4099 | 49.8691 | 49.8691 | |
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| 3.581 | 0.98 | 72 | 1.9550 | 49.8691 | 49.8691 | |
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| 2.195 | 1.48 | 108 | 1.8446 | 49.3455 | 49.8564 | |
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| 2.195 | 1.97 | 144 | 1.7512 | 49.4764 | 51.2613 | |
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| 2.0071 | 2.46 | 180 | 1.6324 | 49.6073 | 52.3994 | |
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| 1.8105 | 2.95 | 216 | 1.5278 | 52.7487 | 55.8533 | |
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| 1.6668 | 3.45 | 252 | 1.3938 | 56.6754 | 60.5142 | |
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| 1.6668 | 3.94 | 288 | 1.3243 | 56.9372 | 62.8755 | |
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| 1.4715 | 4.44 | 324 | 1.2475 | 60.6021 | 66.5376 | |
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| 1.3112 | 4.93 | 360 | 1.2257 | 59.4241 | 65.0059 | |
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| 1.3112 | 5.42 | 396 | 1.1793 | 60.9948 | 66.2895 | |
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| 1.2443 | 5.91 | 432 | 1.1485 | 63.4817 | 69.0854 | |
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| 1.1586 | 6.41 | 468 | 1.1178 | 64.1361 | 69.5844 | |
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| 1.0895 | 6.9 | 504 | 1.1404 | 63.0890 | 68.6016 | |
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| 1.0895 | 7.4 | 540 | 1.0862 | 65.7068 | 70.8093 | |
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| 1.054 | 7.89 | 576 | 1.0959 | 64.7906 | 70.2001 | |
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| 1.0231 | 8.38 | 612 | 1.1036 | 64.3979 | 69.7053 | |
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| 1.0231 | 8.87 | 648 | 1.0698 | 65.8377 | 71.1488 | |
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| 0.9985 | 9.37 | 684 | 1.0777 | 66.0995 | 71.3149 | |
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| 0.9736 | 9.86 | 720 | 1.0942 | 64.3979 | 69.8535 | |
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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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