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@@ -30,9 +30,9 @@ pipeline_tag: token-classification
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  # XLM_R_Galen-ehealth_kd
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- This model is a finetuned version of XLM_R_Galen for the eHealth-KD dataset used in a benchmark in the paper TODO. The model has a F1 of 0.83
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- Please refer to the original publication for more information TODO LINK
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  ## Parameters used
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@@ -51,7 +51,19 @@ Please refer to the original publication for more information TODO LINK
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  ## BibTeX entry and citation info
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- ```bibtex
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- TODO
 
 
 
 
 
 
 
 
 
 
 
 
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  ```
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  # XLM_R_Galen-ehealth_kd
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+ This model is a finetuned version of XLM_R_Galen for the eHealth-KD dataset used in a benchmark in the paper `A comparative analysis of Spanish Clinical encoder-based models on NER and classification tasks`. The model has a F1 of 0.83
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+ Please refer to the [original publication](https://doi.org/10.1093/jamia/ocae054) for more information.
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  ## Parameters used
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  ## BibTeX entry and citation info
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+ ```bibtext
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+ @article{10.1093/jamia/ocae054,
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+ author = {García Subies, Guillem and Barbero Jiménez, Álvaro and Martínez Fernández, Paloma},
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+ title = {A comparative analysis of Spanish Clinical encoder-based models on NER and classification tasks},
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+ journal = {Journal of the American Medical Informatics Association},
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+ volume = {31},
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+ number = {9},
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+ pages = {2137-2146},
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+ year = {2024},
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+ month = {03},
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+ issn = {1527-974X},
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+ doi = {10.1093/jamia/ocae054},
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+ url = {https://doi.org/10.1093/jamia/ocae054},
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+ }
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  ```
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