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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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