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distilbert-base-uncased-agnews-student

Text Classification Transformers PyTorch TensorFlow
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distilbert-base-uncased-agnews-student / README.md
Joe Davison
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metadata
language: en
tags:
  - text-classification
  - pytorch
  - tensorflow
datasets:
  - ag_news
license: mit
widget:
  - text: Armed conflict has been a near-constant policial and economic burden.
  - text: Tom Brady won his seventh Super Bowl last night.
  - text: Dow falls more than 100 points after disappointing jobs data
  - text: A new moon has been discovered in Jupter's orbit.

distilbert-base-uncased-agnews-student

Model Description

This model is distilled from the zero-shot classification pipeline on the unlabeled AG's News dataset using this script. It is the result of the demo notebook here, where more details about the model can be found.

Intended Usage

The model can be used like any other model trained on AG's News, but will likely not perform as well as a model trained with full supervision. It is primarily intended as a demo of how an expensive NLI-based zero-shot model can be distilled to a more efficient student.