mdeberta-v3-base-livingner3

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

Please refer to the original publication for more information TODO LINK

Parameters used

parameter	Value
batch size	64
learning rate	1e-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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Safetensors

Model size

279M params

Tensor type

I64

F32

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Text Classification

This model is not currently available via any of the supported third-party Inference Providers, and the model is not deployed on the HF Inference API.

Dataset used to train IIC/mdeberta-v3-base-livingner3

Collection including IIC/mdeberta-v3-base-livingner3

👨🏻‍⚕️ 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 Jan 23, 2024 • 1

Evaluation results

f1 on livingner3
test set self-reported

0.153

View on Papers With Code