👨🏻⚕️ Spanish Clinical Encoders Analysis
Collection
Models and datasets used in the paper `A comparative analysis of Spanish Clinical encoder-based models on NER and classification tasks` • 91 items • Updated • 3
XLM_R_Galen-meddocan
This model is a finetuned version of XLM_R_Galen for the meddocan dataset used in a benchmark in the paper TODO. The model has a F1 of 0.947
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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Dataset used to train IIC/XLM_R_Galen-meddocan
Collection including IIC/XLM_R_Galen-meddocan
Evaluation results
- f1 on meddocantest set self-reported0.947