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The roberta-large-ca-paraphrase is a Paraphrase Detection model for the Catalan language fine-tuned from the roberta-large-ca-v2 model, a RoBERTa base model pre-trained on a medium-size corpus collected from publicly available corpora and crawlers.
roberta-large-ca-paraphrase model can be used to detect if two sentences are in a paraphrase relation. The model is limited by its training dataset and may not generalize well for all use cases.
Here is how to use this model:
from transformers import pipeline
from pprint import pprint
nlp = pipeline("text-classification", model="projecte-aina/roberta-large-ca-paraphrase")
example = "Tinc un amic a Manresa. </s></s> A Manresa hi viu un amic meu."
paraphrase = nlp(example)
At the time of submission, no measures have been taken to estimate the bias embedded in the model. However, we are well aware that our models may be biased since the corpora have been collected using crawling techniques on multiple web sources. We intend to conduct research in these areas in the future, and if completed, this model card will be updated.
We used the Paraphase Detection dataset in Catalan Parafraseja for training and evaluation.
The model was trained with a batch size of 16 and a learning rate of 5e-5 for 5 epochs. We then selected the best checkpoint using the downstream task metric in the corresponding development set and then evaluated it on the test set.
This model was finetuned maximizing the combined_score.
We evaluated the roberta-large-ca-paraphrase on the Parafraseja test set against standard multilingual and monolingual baselines:
Text Mining Unit (TeMU) at the Barcelona Supercomputing Center (email@example.com)
For further information, send an email to firstname.lastname@example.org
Copyright (c) 2022 Text Mining Unit at Barcelona Supercomputing Center
This work was funded by the Departament de la Vicepresidència i de Polítiques Digitals i Territori de la Generalitat de Catalunya within the framework of Projecte AINA.
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The models published in this repository are intended for a generalist purpose and are available to third parties. These models may have bias and/or any other undesirable distortions.
When third parties, deploy or provide systems and/or services to other parties using any of these models (or using systems based on these models) or become users of the models, they should note that it is their responsibility to mitigate the risks arising from their use and, in any event, to comply with applicable regulations, including regulations regarding the use of Artificial Intelligence.
In no event shall the owner and creator of the models (BSC – Barcelona Supercomputing Center) be liable for any results arising from the use made by third parties of these models.
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