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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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datasets: |
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- pritamdeka/cord-19-abstract |
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model-index: |
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- name: PubMedBert-abstract-cord19 |
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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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# pubmedbert-abstract-cord19 |
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This model is a fine-tuned version of [microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext) on the [pritamdeka/cord-19-abstract](https://huggingface.co/datasets/pritamdeka/cord-19-abstract) dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3005 |
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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: 5e-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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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 10000 |
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- num_epochs: 3.0 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:------:|:---------------:| |
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| 1.3774 | 0.15 | 5000 | 1.3212 | |
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| 1.3937 | 0.29 | 10000 | 1.4059 | |
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| 1.6812 | 0.44 | 15000 | 1.6174 | |
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| 1.4712 | 0.59 | 20000 | 1.4383 | |
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| 1.4293 | 0.73 | 25000 | 1.4356 | |
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| 1.4155 | 0.88 | 30000 | 1.4283 | |
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| 1.3963 | 1.03 | 35000 | 1.4135 | |
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| 1.3718 | 1.18 | 40000 | 1.3948 | |
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| 1.369 | 1.32 | 45000 | 1.3961 | |
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| 1.354 | 1.47 | 50000 | 1.3788 | |
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| 1.3399 | 1.62 | 55000 | 1.3866 | |
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| 1.3289 | 1.76 | 60000 | 1.3630 | |
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| 1.3155 | 1.91 | 65000 | 1.3609 | |
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| 1.2976 | 2.06 | 70000 | 1.3489 | |
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| 1.2783 | 2.2 | 75000 | 1.3333 | |
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| 1.2696 | 2.35 | 80000 | 1.3260 | |
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| 1.2607 | 2.5 | 85000 | 1.3232 | |
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| 1.2547 | 2.64 | 90000 | 1.3034 | |
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| 1.2495 | 2.79 | 95000 | 1.3035 | |
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| 1.2404 | 2.94 | 100000 | 1.3029 | |
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### Framework versions |
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- Transformers 4.17.0.dev0 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 1.18.3 |
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- Tokenizers 0.11.0 |
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