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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-Squad-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-Squad-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: 1.5061 |
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- Exact Match: 48.9695 |
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- F1: 65.3139 |
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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: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 64 |
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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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| 2.0131 | 0.5 | 463 | 1.8398 | 39.7325 | 55.0682 | |
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| 1.8343 | 1.0 | 926 | 1.6799 | 42.9545 | 58.8261 | |
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| 1.6407 | 1.5 | 1389 | 1.6097 | 45.1502 | 61.1235 | |
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| 1.6021 | 2.0 | 1852 | 1.5634 | 46.0167 | 62.5172 | |
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| 1.4841 | 2.5 | 2315 | 1.5438 | 46.5971 | 63.4037 | |
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| 1.5117 | 3.0 | 2778 | 1.5080 | 47.2028 | 64.1405 | |
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| 1.3752 | 3.5 | 3241 | 1.5149 | 47.6487 | 64.3195 | |
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| 1.3491 | 4.0 | 3704 | 1.4956 | 47.8927 | 64.4993 | |
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| 1.3068 | 4.5 | 4167 | 1.4951 | 48.0861 | 64.7876 | |
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| 1.2916 | 5.0 | 4630 | 1.4895 | 48.3722 | 64.9676 | |
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| 1.2593 | 5.5 | 5093 | 1.4954 | 48.5909 | 65.1206 | |
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| 1.2032 | 6.0 | 5556 | 1.4891 | 48.5236 | 65.0831 | |
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| 1.1826 | 6.5 | 6019 | 1.4944 | 48.6077 | 65.0162 | |
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| 1.2159 | 7.0 | 6482 | 1.4870 | 48.9526 | 65.1941 | |
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| 1.1503 | 7.5 | 6945 | 1.5074 | 48.8180 | 65.3672 | |
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| 1.1683 | 8.0 | 7408 | 1.4928 | 48.7760 | 65.2063 | |
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| 1.0898 | 8.5 | 7871 | 1.5141 | 48.7844 | 65.0996 | |
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| 1.1217 | 9.0 | 8334 | 1.5061 | 48.9695 | 65.3139 | |
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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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