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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-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: 1.5397 |
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- Exact Match: 47.8725 |
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- F1: 64.1189 |
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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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| 1.8628 | 0.5 | 463 | 1.7727 | 40.7249 | 56.9043 | |
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| 1.6706 | 1.0 | 926 | 1.6163 | 44.3912 | 61.0635 | |
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| 1.5058 | 1.5 | 1389 | 1.5655 | 45.4339 | 61.5089 | |
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| 1.4661 | 2.0 | 1852 | 1.5130 | 46.9055 | 63.5850 | |
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| 1.3171 | 2.5 | 2315 | 1.5077 | 47.1914 | 63.4762 | |
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| 1.3258 | 3.0 | 2778 | 1.4981 | 47.6034 | 64.3797 | |
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| 1.1835 | 3.5 | 3241 | 1.5171 | 47.7043 | 64.1444 | |
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| 1.1946 | 4.0 | 3704 | 1.5333 | 47.6539 | 64.3327 | |
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| 1.0904 | 4.5 | 4167 | 1.5397 | 47.8725 | 64.1189 | |
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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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