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README.md
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---
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license: cc-by-nc-4.0
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language:
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- es
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tags:
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- simplification
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- NER
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---
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This is a model for **complex word identification (CWI)** of Spanish medical texts, based on the
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[multilingual DeBERTa vs 3 (mDeBERTa)](https://huggingface.co/microsoft/mdeberta-v3-base).
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The model was fine-tuned on a corpus of 225 texts for patients (162575 tokens) to identify **complex words** (**CW**).
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**Results (test set)**
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| Class | Precision | Recall | F1 | Accuracy |
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|:-----:|:-------------:|:-------------:|:-------------:|:-------------:|
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| CW | 79.05 (±1.39) | 79.01 (±0.70) | 79.02 (±0.65) | 94.86 (±0.22) |
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*Results are the average of 3 experimental rounds.
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If you use this model or want to have more details about the experiments and the training details, take a look at our article:
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```
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@article{2025CWI,
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title={Complex Word Identification for Lexical Simplification in Spanish Texts for Patients},
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author={Ortega-Riba, Federico and Campillos-Llanos, Leonardo and Samy, Doaa},
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journal={Procesamiento del lenguaje natural},
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volume={74},
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year={2025}
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}
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```
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