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  ---
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  license: mit
 
 
 
 
 
 
 
 
 
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  ---
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  This is a fine-tuned BERT-based language model to classify NLP-related research papers as "survey" or "non-survey" papers. The model is fine-tuned on a dataset of 787 survey and 11,805 non-survey papers from the ACL Anthology and the arXiv cs.CL category. Prior to fine-tuning, the model is initialized with weights from Prior to fine-tuning, the model is initialized with weights from [malteos/scincl](https://huggingface.co/malteos/scincl).
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  * **F1:** 84.35
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  * **Precision:** 82.38
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  * **Recall:** 86.53
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- * **Accuracy:** 98.04
 
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  license: mit
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+ language:
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+ - en
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+ metrics:
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+ - f1
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+ - accuracy
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+ - precision
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+ - recall
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+ library_name: transformers
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+ pipeline_tag: text-classification
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  ---
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  This is a fine-tuned BERT-based language model to classify NLP-related research papers as "survey" or "non-survey" papers. The model is fine-tuned on a dataset of 787 survey and 11,805 non-survey papers from the ACL Anthology and the arXiv cs.CL category. Prior to fine-tuning, the model is initialized with weights from Prior to fine-tuning, the model is initialized with weights from [malteos/scincl](https://huggingface.co/malteos/scincl).
 
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  * **F1:** 84.35
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  * **Precision:** 82.38
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  * **Recall:** 86.53
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+ * **Accuracy:** 98.04