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fine-tuned-DatasetQAS-TYDI-QA-ID-with-indobert-large-p2-with-ITTL-without-freeze-LR-1e-05

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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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+ - precision
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+ - recall
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+ model-index:
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+ - name: fine-tuned-DatasetQAS-TYDI-QA-ID-with-indobert-large-p2-with-ITTL-without-freeze-LR-1e-05
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+ results: []
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+ ---
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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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+
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+ # fine-tuned-DatasetQAS-TYDI-QA-ID-with-indobert-large-p2-with-ITTL-without-freeze-LR-1e-05
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+
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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: 1.2832
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+ - Exact Match: 59.3368
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+ - F1: 73.6394
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+ - Precision: 75.6497
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+ - Recall: 79.2494
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Exact Match | F1 | Precision | Recall |
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+ |:-------------:|:-----:|:----:|:---------------:|:-----------:|:-------:|:---------:|:-------:|
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+ | 6.1305 | 0.49 | 38 | 2.9545 | 18.3246 | 28.7037 | 30.7234 | 39.3266 |
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+ | 3.6666 | 0.99 | 76 | 2.0933 | 29.3194 | 41.5386 | 41.3158 | 57.3278 |
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+ | 2.2221 | 1.48 | 114 | 1.5088 | 46.0733 | 59.6910 | 61.3465 | 70.0645 |
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+ | 1.5513 | 1.97 | 152 | 1.2788 | 52.7051 | 67.6237 | 68.9352 | 76.7287 |
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+ | 1.5513 | 2.47 | 190 | 1.2375 | 56.0209 | 70.0861 | 72.2276 | 76.3275 |
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+ | 1.1584 | 2.96 | 228 | 1.1617 | 56.3700 | 70.9542 | 72.5147 | 77.8564 |
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+ | 1.0032 | 3.45 | 266 | 1.1656 | 57.9407 | 72.1620 | 73.8214 | 78.2817 |
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+ | 0.8661 | 3.95 | 304 | 1.1443 | 57.5916 | 72.5053 | 73.8808 | 80.3537 |
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+ | 0.8661 | 4.44 | 342 | 1.1663 | 58.4642 | 73.4761 | 75.0381 | 80.0108 |
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+ | 0.7541 | 4.94 | 380 | 1.1414 | 58.2897 | 73.1853 | 74.9363 | 78.6912 |
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+ | 0.6687 | 5.43 | 418 | 1.2151 | 60.0349 | 73.6810 | 75.7886 | 79.3854 |
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+ | 0.5926 | 5.92 | 456 | 1.1805 | 60.5585 | 74.6182 | 76.2757 | 81.1406 |
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+ | 0.5926 | 6.42 | 494 | 1.2740 | 60.5585 | 74.4135 | 76.4582 | 80.1876 |
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+ | 0.4761 | 6.91 | 532 | 1.2221 | 59.8604 | 74.5837 | 75.8985 | 80.5858 |
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+ | 0.4644 | 7.4 | 570 | 1.2832 | 59.3368 | 73.6394 | 75.6497 | 79.2494 |
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+
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+
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+ ### Framework versions
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+
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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