Model card.

README.md

@@ -0,0 +1,57 @@
+---
+language: es
+license: cc-by-4.0
+tags:
+- spanish
+- roberta
+- bertin
+pipeline_tag: text-classification
+widget:
+- 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.
+---
+
+# Readability ES Sentences for two classes
+
+Model based on the Roberta architecture finetuned on [BERTIN](https://huggingface.co/bertin-project/bertin-roberta-base-spanish) for readability assessment of Spanish texts.
+
+## Description and performance
+
+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:
+- Simple.
+- Complex.
+
+It achieves a F1 macro average score of 0.8891, measured on the validation set.
+
+## Model variants
+
+- [`readability-es-sentences`](https://huggingface.co/hackathon-pln-es/readability-es-sentences). Two classes, sentence-based dataset.
+- `readability-es-paragraphs` (this model). Two classes, paragraph-based dataset.
+- [`readability-es-3class-sentences`](https://huggingface.co/hackathon-pln-es/readability-es-3class-sentences). Three classes, sentence-based dataset.
+- [`readability-es-3class-paragraphs`](https://huggingface.co/hackathon-pln-es/readability-es-3class-paragraphs). Three classes, paragraph-based dataset.
+
+## Datasets
+
+- [`readability-es-sentences`](https://huggingface.co/datasets/hackathon-pln-es/readability-es-sentences), composed of:
+  * coh-metrix-esp corpus.
+  * Various text resources scraped from websites.
+- Other non-public datasets: newsela-es, simplext.
+
+## Training details
+
+Please, refer to [this training run](https://wandb.ai/readability-es/readability-es/runs/3rgvwps0/overview?workspace=user-pcuenq) for full details on hyperparameters and training regime.
+
+## Biases and Limitations
+
+- Due to the scarcity of data and the lack of a reliable gold test set, performance metrics are reported on the validation set.
+- 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.
+- Some of the datasets used cannot be publicly disseminated, making it more difficult to assess the existence of biases or mistakes.
+- Language might be biased towards the Spanish dialect spoken in Spain. Other regional variants might be sub-represented.
+- 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).
+
+## Authors
+
+- [Laura Vásquez-Rodríguez](https://lmvasque.github.io/)
+- [Pedro Cuenca](https://twitter.com/pcuenq)
+- [Sergio Morales](https://www.fireblend.com/)
+- [Fernando Alva-Manchego](https://feralvam.github.io/)
+