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README.md
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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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- "chizhikchi/CARES"
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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-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: 0.756
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pipeline_tag: text-classification
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---
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# mdeberta-v3-base-caresC
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This model is a finetuned version of mdeberta-v3-base for the Cares Chapters dataset used in a benchmark in the paper TODO. The model has a F1 of 0.756
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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 | 3e-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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