👨🏻⚕️ 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` • 92 items • Updated
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mdeberta-v3-base-livingner1
This model is a finetuned version of mdeberta-v3-base for the livingner1 dataset used in a benchmark in the paper TODO. The model has a F1 of 0.953
Please refer to the original publication for more information TODO LINK
Parameters used
| parameter | Value |
|---|---|
| batch size | 16 |
| learning rate | 4e-05 |
| classifier dropout | 0.1 |
| 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/mdeberta-v3-base-livingner1
Collection including IIC/mdeberta-v3-base-livingner1
Evaluation results
- f1 on livingner1test set self-reported0.953