This model is created from the finetuning of the pre-model for Spanish BETO, using PyTorch framework, and trained with a set of theses of the National Autonomous University of Mexico (UNAM). The model classifies a text into for five (Psicología, Derecho, Química Farmacéutico Biológica, Actuaría, Economía) possible careers at the UNAM.

1000 documents (Thesis introduction, Author´s first name, Author´s last name, Thesis title, Year, Career)

For further details on how to use unam_tesis_BETO_finnetuning you can visit the Hugging Face Transformers library, starting with the Quickstart section. The UNAM tesis model can be accessed simply as 'hackathon-pln-e/unam_tesis_BETO_finnetuning' by using the Transformers library. An example of how to download and use the model can be found next.

To cite this resource in a publication please use the following:

[UNAM's Tesis with BETO finetuning classify] (https://huggingface.co/hackathon-pln-es/unam_tesis_BETO_finnetuning)

To cite this resource in a publication please use the following:

@inproceedings{SpanishNLPHackaton2022,
  title={UNAM's Theses with BETO fine-tuning classify},
  author={López López, Isaac Isaías; Clavel Quintero, Yisel; López Ramos, Dionis & López López, Ximena Yeraldin},
  booktitle={Somos NLP Hackaton 2022},
  year={2022}
}