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--- |
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language: es |
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license: cc-by-4.0 |
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tags: |
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- spanish |
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- roberta |
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- bertin |
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pipeline_tag: text-classification |
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widget: |
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- text: La cueva de Zaratustra en el Pretil de los Consejos. Rimeros de libros hacen escombro y cubren las paredes. Empapelan los cuatro vidrios de una puerta cuatro cromos espeluznantes de un novelón por entregas. En la cueva hacen tertulia el gato, el can, el loro y el librero. Zaratustra, abichado y giboso -la cara de tocino rancio y la bufanda de verde serpiente- promueve con su caracterización de fantoche, una aguda y dolorosa disonancia muy emotiva y muy moderna. Encogido en el roto pelote de su silla enana, con los pies entrapados y cepones en la tarima del brasero, guarda la tienda. Un ratón saca el hocico intrigante por un agujero. |
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--- |
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# Readability ES Paragraphs for two classes |
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Model based on the Roberta architecture finetuned on [BERTIN](https://huggingface.co/bertin-project/bertin-roberta-base-spanish) for readability assessment of Spanish texts. |
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## Description and performance |
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This version of the model was trained on a mix of datasets, using paragraph-level granularity when possible. The model performs binary classification among the following classes: |
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- Simple. |
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- Complex. |
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It achieves a F1 macro average score of 0.8891, measured on the validation set. |
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## Model variants |
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- [`readability-es-sentences`](https://huggingface.co/hackathon-pln-es/readability-es-sentences). Two classes, sentence-based dataset. |
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- `readability-es-paragraphs` (this model). Two classes, paragraph-based dataset. |
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- [`readability-es-3class-sentences`](https://huggingface.co/hackathon-pln-es/readability-es-3class-sentences). Three classes, sentence-based dataset. |
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- [`readability-es-3class-paragraphs`](https://huggingface.co/hackathon-pln-es/readability-es-3class-paragraphs). Three classes, paragraph-based dataset. |
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## Datasets |
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- [`readability-es-hackathon-pln-public`](https://huggingface.co/datasets/hackathon-pln-es/readability-es-hackathon-pln-public), composed of: |
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* coh-metrix-esp corpus. |
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* Various text resources scraped from websites. |
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- Other non-public datasets: newsela-es, simplext. |
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## Training details |
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Please, refer to [this training run](https://wandb.ai/readability-es/readability-es/runs/2z8080pi/overview) for full details on hyperparameters and training regime. |
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## Biases and Limitations |
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- Due to the scarcity of data and the lack of a reliable gold test set, performance metrics are reported on the validation set. |
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- One of the datasets involved is the Spanish version of newsela, which is frequently used as a reference. However, it was created by translating previous datasets, and therefore it may contain somewhat unnatural phrases. |
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- Some of the datasets used cannot be publicly disseminated, making it more difficult to assess the existence of biases or mistakes. |
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- Language might be biased towards the Spanish dialect spoken in Spain. Other regional variants might be sub-represented. |
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- No effort has been performed to alleviate the shortcomings and biases described in the [original implementation of BERTIN](https://huggingface.co/bertin-project/bertin-roberta-base-spanish#bias-examples-spanish). |
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## Authors |
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- [Laura Vásquez-Rodríguez](https://lmvasque.github.io/) |
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- [Pedro Cuenca](https://twitter.com/pcuenq) |
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- [Sergio Morales](https://www.fireblend.com/) |
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- [Fernando Alva-Manchego](https://feralvam.github.io/) |
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