joeddav/distilbert-base-uncased-go-emotions-student

🤗 Hugging Face sourcetext-classificationmit67M params268 MBsafetensors✓ 3 checksumsupdated today
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Run it next to your model folder. It makes the torrent, checks your files against Hugging Face, and submits it. You just start seeding and paste your key from your account. It only reads your files and never changes them. Read the script first if you like.

curl -fsSL https://pirateface.co/package.sh | bash -s -- --repo joeddav/distilbert-base-uncased-go-emotions-student ./model-folder
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distilbert-base-uncased-go-emotions-student

Model Description

This model is distilled from the zero-shot classification pipeline on the unlabeled GoEmotions dataset using this script. It was trained with mixed precision for 10 epochs and otherwise used the default script arguments.

Intended Usage

The model can be used like any other model trained on GoEmotions, 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, allowing a classifier to be trained with only unlabeled data. Note that although the GoEmotions dataset allow multiple labels per instance, the teacher used single-label classification to create psuedo-labels.