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README.md
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@@ -69,7 +69,7 @@ though this is still an important clinical task.
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Use the code below to get started with the model.
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from transformers import AutoTokenizer, AutoModelForSequenceClassification
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model = AutoModelForSequenceClassification.from_pretrained("semaj83/scibert_finetuned_ctmatch")
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## Training Details
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#### Training Hyperparameters
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max_sequence_length=512
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batch_size=8
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padding='max_length'
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truncation=True
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use_trainer=True
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fp16=True
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early_stopping=True
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`
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sklearn classifier table on random test split:
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precision recall f1-score support
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macro avg 0.70 0.66 0.67 7939
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weighted avg 0.79 0.80 0.79 7939
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`
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## Model Card Authors
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Use the code below to get started with the model.
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```
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from transformers import AutoTokenizer, AutoModelForSequenceClassification
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model = AutoModelForSequenceClassification.from_pretrained("semaj83/scibert_finetuned_ctmatch")
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```
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## Training Details
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#### Training Hyperparameters
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`max_sequence_length=512
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batch_size=8
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padding='max_length'
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truncation=True
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use_trainer=True
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fp16=True
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early_stopping=True
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`
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sklearn classifier table on random test split:
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```
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precision recall f1-score support
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macro avg 0.70 0.66 0.67 7939
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weighted avg 0.79 0.80 0.79 7939
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```
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## Model Card Authors
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