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End of training

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  2. pytorch_model.bin +1 -1
README.md ADDED
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+ ---
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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: ec_classfication_0502_dmis_lab_biobert_large_cased_v1.1_squad
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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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+ # ec_classfication_0502_dmis_lab_biobert_large_cased_v1.1_squad
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+
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+ This model is a fine-tuned version of [dmis-lab/biobert-large-cased-v1.1-squad](https://huggingface.co/dmis-lab/biobert-large-cased-v1.1-squad) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.1937
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+ - F1: 0.8352
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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: 2e-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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+ - 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: 15
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | No log | 1.0 | 59 | 0.6381 | 0.5429 |
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+ | No log | 2.0 | 118 | 0.4498 | 0.8350 |
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+ | No log | 3.0 | 177 | 0.6399 | 0.8247 |
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+ | No log | 4.0 | 236 | 0.6723 | 0.8444 |
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+ | No log | 5.0 | 295 | 1.1235 | 0.7901 |
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+ | No log | 6.0 | 354 | 1.0581 | 0.8298 |
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+ | No log | 7.0 | 413 | 1.2403 | 0.8 |
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+ | No log | 8.0 | 472 | 1.1142 | 0.8298 |
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+ | 0.1533 | 9.0 | 531 | 1.1338 | 0.8222 |
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+ | 0.1533 | 10.0 | 590 | 1.1343 | 0.8478 |
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+ | 0.1533 | 11.0 | 649 | 1.1471 | 0.8478 |
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+ | 0.1533 | 12.0 | 708 | 1.1670 | 0.8478 |
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+ | 0.1533 | 13.0 | 767 | 1.1825 | 0.8352 |
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+ | 0.1533 | 14.0 | 826 | 1.1912 | 0.8352 |
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+ | 0.1533 | 15.0 | 885 | 1.1937 | 0.8352 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.27.3
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+ - Pytorch 2.0.0+cu118
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+ - Datasets 2.11.0
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+ - Tokenizers 0.13.2
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