IIC / bsc-bio-ehr-es-ctebmsp

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Total runs: 15
24-hour runs: 0
7-day runs: -4
30-day runs: 7
Model's Last Updated: January 17 2025
token-classification

Introduction of bsc-bio-ehr-es-ctebmsp

Model Details of bsc-bio-ehr-es-ctebmsp

bsc-bio-ehr-es-ctebmsp

This model is a finetuned version of bsc-bio-ehr-es for the CT-EBM-SP (Clinical Trials for Evidence-based Medicine in Spanish) dataset used in a benchmark in the paper TODO. The model has a F1 of 0.876

Please refer to the original publication for more information TODO LINK

Parameters used
parameter Value
batch size 16
learning rate 4e-05
classifier dropout 0.2
warmup ratio 0
warmup steps 0
weight decay 0
optimizer AdamW
epochs 10
early stopping patience 3
BibTeX entry and citation info
TODO

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15
Total runs
0
24-hour runs
-1
3-day runs
-4
7-day runs
7
30-day runs

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bsc-bio-ehr-es-ctebmsp huggingface.co is an AI model on huggingface.co that provides bsc-bio-ehr-es-ctebmsp's model effect (), which can be used instantly with this IIC bsc-bio-ehr-es-ctebmsp model. huggingface.co supports a free trial of the bsc-bio-ehr-es-ctebmsp model, and also provides paid use of the bsc-bio-ehr-es-ctebmsp. Support call bsc-bio-ehr-es-ctebmsp model through api, including Node.js, Python, http.

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bsc-bio-ehr-es-ctebmsp is an open source model from GitHub that offers a free installation service, and any user can find bsc-bio-ehr-es-ctebmsp on GitHub to install. At the same time, huggingface.co provides the effect of bsc-bio-ehr-es-ctebmsp install, users can directly use bsc-bio-ehr-es-ctebmsp installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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