language	tags	datasets	license	pipeline_tag	widget
es	zero-shot-classification nli pytorch	xnli	mit	zero-shot-classification	text candidate_labels El autor se perfila, a los 50 años de su muerte, como uno de los grandes de su siglo cultura, sociedad, economia, salud, deportes

bert-base-spanish-wwm-cased-xnli

UPDATE, 15.10.2021: Check out our new zero-shot classifiers, much more lightweight and even outperforming this one: zero-shot SELECTRA small and zero-shot SELECTRA medium.

Model description

This model is a fine-tuned version of the spanish BERT model with the Spanish portion of the XNLI dataset. You can have a look at the training script for details of the training.

How to use

You can use this model with Hugging Face's zero-shot-classification pipeline:

from transformers import pipeline
classifier = pipeline("zero-shot-classification", 
                       model="Recognai/bert-base-spanish-wwm-cased-xnli")

classifier(
    "El autor se perfila, a los 50 años de su muerte, como uno de los grandes de su siglo",
    candidate_labels=["cultura", "sociedad", "economia", "salud", "deportes"],
    hypothesis_template="Este ejemplo es {}."
)
"""output
{'sequence': 'El autor se perfila, a los 50 años de su muerte, como uno de los grandes de su siglo',
 'labels': ['cultura', 'sociedad', 'economia', 'salud', 'deportes'],
 'scores': [0.38897448778152466,
  0.22997373342514038,
  0.1658431738615036,
  0.1205764189362526,
  0.09463217109441757]}
"""

Eval results

Accuracy for the test set:

	XNLI-es
bert-base-spanish-wwm-cased-xnli	79.9%