Overview Model trained from roberta base on the go emotions dataset for multi label classification. ONNX version also available A version of this model in ONNX format (including an INT8 quantized ONNX version) is now available at https://huggingface.co/SamLowe/roberta base go emotions onnx. These are faster for inference, esp for smaller batch sizes, massively reduce the size of the dependencies required for inference, make inference of the model more multi platform, and in the case of the quantized version reduce the model file/download size by 75% whilst retaining almost all the accuracy if you only need inference. Dataset used for the model go emotions is based on Reddit data and has 28 labels. It is a multi label dataset where one or multiple labels may apply for any given input text, hence this model is a multi label classification model with 28 'probability' float outputs for any given input text. Typically a threshold of 0.5 is applied to the probabilities for the prediction for each label. How the model was created The model was trained using AutoModelForSequenceClassification.from pretrained with problem type="multi label classification" for 3 epochs with a learning rate o…
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