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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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- mdeberta-v3-base |
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license: mit |
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datasets: |
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- "IIC/livingner3" |
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metrics: |
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- f1 |
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model-index: |
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- name: IIC/mdeberta-v3-base-livingner3 |
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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: livingner3 |
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type: IIC/livingner3 |
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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: 0.153 |
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pipeline_tag: text-classification |
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--- |
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# mdeberta-v3-base-livingner3 |
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This model is a finetuned version of mdeberta-v3-base for the livingner3 dataset used in a benchmark in the paper TODO. The model has a F1 of 0.153 |
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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 | 64 | |
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| learning rate | 1e-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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