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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-TYDI-QA-ID-with-indobert-base-uncased-with-ITTL-with-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-TYDI-QA-ID-with-indobert-base-uncased-with-ITTL-with-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: 1.3132 |
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- Exact Match: 53.2628 |
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- F1: 68.3641 |
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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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| 6.3129 | 0.5 | 19 | 3.9006 | 5.6437 | 16.4748 | |
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| 6.3129 | 1.0 | 38 | 2.8272 | 17.1076 | 30.0839 | |
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| 3.8917 | 1.5 | 57 | 2.4681 | 18.8713 | 32.8962 | |
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| 3.8917 | 2.0 | 76 | 2.2891 | 25.3968 | 38.0874 | |
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| 3.8917 | 2.5 | 95 | 2.1835 | 26.9841 | 39.5053 | |
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| 2.3963 | 3.0 | 114 | 2.0885 | 28.5714 | 42.0243 | |
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| 2.3963 | 3.5 | 133 | 1.9971 | 32.4515 | 45.4085 | |
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| 2.112 | 4.0 | 152 | 1.9124 | 34.3915 | 48.2893 | |
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| 2.112 | 4.5 | 171 | 1.8358 | 37.0370 | 50.6492 | |
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| 2.112 | 5.0 | 190 | 1.7545 | 40.7407 | 54.7031 | |
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| 1.8205 | 5.5 | 209 | 1.6432 | 44.4444 | 58.2669 | |
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| 1.8205 | 6.0 | 228 | 1.5589 | 46.9136 | 60.8052 | |
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| 1.8205 | 6.5 | 247 | 1.4861 | 48.1481 | 62.5185 | |
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| 1.573 | 7.0 | 266 | 1.4381 | 49.7354 | 64.1985 | |
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| 1.573 | 7.5 | 285 | 1.3944 | 51.6755 | 66.0223 | |
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| 1.387 | 8.0 | 304 | 1.3534 | 53.2628 | 67.6841 | |
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| 1.387 | 8.5 | 323 | 1.3384 | 53.0864 | 67.8619 | |
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| 1.387 | 9.0 | 342 | 1.3344 | 52.9101 | 68.0618 | |
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| 1.2998 | 9.5 | 361 | 1.3182 | 53.2628 | 68.4149 | |
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| 1.2998 | 10.0 | 380 | 1.3132 | 53.2628 | 68.3641 | |
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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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