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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-roberta-large |
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license: mit |
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datasets: |
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- "ehealth_kd" |
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metrics: |
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- f1 |
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model-index: |
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- name: IIC/xlm-roberta-large-ehealth_kd |
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results: |
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- task: |
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type: token-classification |
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dataset: |
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name: eHealth-KD |
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type: ehealth_kd |
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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: 0.871 |
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pipeline_tag: token-classification |
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--- |
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# xlm-roberta-large-ehealth_kd |
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This model is a finetuned version of xlm-roberta-large for the eHealth-KD dataset used in a benchmark in the paper TODO. The model has a F1 of 0.871 |
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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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| parameter | Value | |
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|-------------------------|:-----:| |
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| batch size | 16 | |
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| learning rate | 2e-05 | |
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| classifier dropout | 0.2 | |
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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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## BibTeX entry and citation info |
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```bibtex |
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TODO |
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``` |
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