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--- |
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license: mit |
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base_model: microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract |
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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: BiomedNLP-CIViC-evidence-level-finetuned |
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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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# BiomedNLP-CIViC-evidence-level-finetuned |
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This model is a fine-tuned version of [microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract](https://huggingface.co/microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.5745 |
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- F1: 0.8312 |
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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: 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: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| No log | 1.0 | 73 | 1.5464 | 0.8260 | |
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| No log | 2.0 | 146 | 1.7265 | 0.7844 | |
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| No log | 3.0 | 219 | 1.6166 | 0.8260 | |
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| No log | 4.0 | 292 | 1.5619 | 0.8260 | |
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| No log | 5.0 | 365 | 1.5745 | 0.8312 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.2 |
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- Datasets 2.21.0 |
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- Tokenizers 0.15.0 |
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