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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-TYDI-QA-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-TYDI-QA-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: 1.2784 |
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- Exact Match: 53.4392 |
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- F1: 68.7244 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 32 |
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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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| 6.1764 | 0.5 | 19 | 3.7674 | 10.4056 | 23.6332 | |
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| 6.1764 | 1.0 | 38 | 2.7985 | 19.5767 | 32.6228 | |
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| 3.8085 | 1.49 | 57 | 2.4169 | 22.0459 | 35.4084 | |
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| 3.8085 | 1.99 | 76 | 2.2811 | 25.9259 | 38.3963 | |
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| 3.8085 | 2.49 | 95 | 2.1607 | 28.0423 | 40.3901 | |
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| 2.3932 | 2.99 | 114 | 2.0488 | 31.0406 | 43.7059 | |
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| 2.3932 | 3.49 | 133 | 1.9787 | 34.3915 | 46.3655 | |
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| 2.0772 | 3.98 | 152 | 1.8661 | 37.2134 | 49.1483 | |
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| 2.0772 | 4.48 | 171 | 1.7893 | 40.2116 | 52.4989 | |
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| 2.0772 | 4.98 | 190 | 1.7014 | 41.9753 | 54.9197 | |
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| 1.7645 | 5.48 | 209 | 1.5940 | 44.2681 | 58.2134 | |
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| 1.7645 | 5.98 | 228 | 1.4972 | 46.2081 | 60.4997 | |
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| 1.7645 | 6.47 | 247 | 1.4214 | 48.8536 | 63.4371 | |
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| 1.5035 | 6.97 | 266 | 1.3676 | 50.6173 | 65.4663 | |
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| 1.5035 | 7.47 | 285 | 1.3357 | 52.2046 | 67.1759 | |
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| 1.3206 | 7.97 | 304 | 1.3149 | 53.0864 | 68.0698 | |
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| 1.3206 | 8.47 | 323 | 1.2988 | 53.4392 | 68.3971 | |
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| 1.3206 | 8.96 | 342 | 1.2894 | 53.6155 | 68.8897 | |
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| 1.2472 | 9.46 | 361 | 1.2820 | 53.4392 | 68.5835 | |
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| 1.2472 | 9.96 | 380 | 1.2784 | 53.4392 | 68.7244 | |
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### Framework versions |
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- Transformers 4.27.4 |
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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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