Distilbert Base Uncased Go Emotions Onnx

🚀 distilbert-base-uncased-go-emotions-student

The joeddav/distilbert-base-uncased-go-emotions-student model converted to ONNX and quantized using optimum, offering an efficient alternative for emotion classification.

🚀 Quick Start

The joeddav/distilbert-base-uncased-go-emotions-student has been converted to ONNX and quantized using optimum.

📚 Documentation

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.

📄 License

This project is licensed under the MIT license.