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README.md
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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: clinical_bert_ft
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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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# clinical_bert_ft
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This model is a fine-tuned version of [emilyalsentzer/Bio_ClinicalBERT](https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2439
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- F1: 0.8252
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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: 32
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- eval_batch_size: 32
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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: 10
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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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| 0.5938 | 1.0 | 95 | 0.2480 | 0.7084 |
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| 0.1567 | 2.0 | 190 | 0.2035 | 0.7855 |
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| 0.083 | 3.0 | 285 | 0.2002 | 0.8026 |
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| 0.0482 | 4.0 | 380 | 0.2046 | 0.8118 |
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| 0.0269 | 5.0 | 475 | 0.2230 | 0.8143 |
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| 0.0185 | 6.0 | 570 | 0.2178 | 0.8175 |
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| 0.0123 | 7.0 | 665 | 0.2269 | 0.8253 |
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| 0.0093 | 8.0 | 760 | 0.2421 | 0.8227 |
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| 0.0072 | 9.0 | 855 | 0.2446 | 0.8267 |
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| 0.006 | 10.0 | 950 | 0.2439 | 0.8252 |
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### Framework versions
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- Transformers 4.20.1
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- Pytorch 1.11.0+cu113
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- Datasets 2.3.2
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- Tokenizers 0.12.1
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