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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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- precision |
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- recall |
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model-index: |
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- name: fine-tuned-DatasetQAS-Squad-ID-with-indobert-large-p2-without-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-large-p2-without-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: 1.7843 |
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- Exact Match: 45.4462 |
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- F1: 62.3862 |
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- Precision: 63.7620 |
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- Recall: 67.9874 |
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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: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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: 16 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Exact Match | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:-----------:|:-------:|:---------:|:-------:| |
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| 1.7808 | 0.5 | 1024 | 1.8192 | 39.1225 | 56.2210 | 57.3004 | 64.1431 | |
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| 1.598 | 1.0 | 2048 | 1.6753 | 42.0808 | 59.2251 | 60.4591 | 66.8518 | |
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| 1.4195 | 1.5 | 3072 | 1.6611 | 43.5599 | 60.7862 | 62.5640 | 66.8640 | |
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| 1.4262 | 2.0 | 4096 | 1.6420 | 45.0474 | 62.2214 | 63.9056 | 67.8747 | |
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| 1.1907 | 2.5 | 5120 | 1.6686 | 44.6319 | 61.3804 | 62.6910 | 68.0916 | |
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| 1.2017 | 3.0 | 6144 | 1.6597 | 45.4130 | 62.6561 | 63.9677 | 68.6391 | |
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| 1.0831 | 3.5 | 7168 | 1.7486 | 45.3714 | 62.2018 | 63.5154 | 68.2643 | |
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| 1.0256 | 4.0 | 8192 | 1.6899 | 45.6955 | 62.5503 | 64.2337 | 67.9408 | |
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| 0.9378 | 4.5 | 9216 | 1.7843 | 45.4462 | 62.3862 | 63.7620 | 67.9874 | |
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### Framework versions |
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- Transformers 4.27.0 |
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- Pytorch 2.0.0+cu117 |
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- Datasets 2.2.0 |
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- Tokenizers 0.13.2 |
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