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+ ---
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+ language: es
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+ tags:
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+ - biomedical
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+ - clinical
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+ - spanish
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+ - XLM_R_Galen
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+ license: mit
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+ datasets:
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+ - "chizhikchi/CARES"
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+ metrics:
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+ - f1
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+
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+ model-index:
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+ - name: IIC/XLM_R_Galen-caresC
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+ results:
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+ - task:
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+ type: multi-label-classification
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+ dataset:
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+ name: Cares Chapters
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+ type: chizhikchi/CARES
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+ split: test
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+ metrics:
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+ - name: f1
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+ type: f1
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+ value: 0.823
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+ pipeline_tag: text-classification
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+
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+ ---
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+
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+ # XLM_R_Galen-caresC
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+
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+ This model is a finetuned version of XLM_R_Galen for the Cares Chapters dataset used in a benchmark in the paper TODO. The model has a F1 of 0.823
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+
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+ Please refer to the original publication for more information TODO LINK
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+
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+ ## Parameters used
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+
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+ | parameter | Value |
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+ |-------------------------|:-----:|
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+ | batch size | 16 |
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+ | learning rate | 4e-05 |
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+ | classifier dropout | 0 |
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+ | warmup ratio | 0 |
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+ | warmup steps | 0 |
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+ | weight decay | 0 |
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+ | optimizer | AdamW |
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+ | epochs | 10 |
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+ | early stopping patience | 3 |
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+
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+
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+ ## BibTeX entry and citation info
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+
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+ ```bibtex
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+ TODO
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+ ```
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+