This is the best russian opensource model for detecting all 27 types of emotions: Model F1 macro F1 macro weighted Precision macro Recall macro Size seara/rubert tiny2 ru go emotions 0.33 0.48 0.51 0.29 29.2M seara/rubert base cased ru go emotions 0.36 0.49 0.52 0.31 178M fyaronskiy/ruRoberta large ru go emotions default thresholds = 0.5 0.41 0.52 0.58 0.36 355M fyaronskiy/ruRoberta large ru go emotions best thresholds 0.48 0.58 0.46 0.55 355M fyaronskiy/deberta v1 base russian go emotions 0.48 0.57 0.46 0.54 125M Summary This is ruRoberta large model finetuned on ru go emotions dataset for multilabel classification. Model can be used to extract all emotions from text or detect certain emotions. Thresholds are selected on validation set by maximizing f1 macro over all labels. The quality of the model varies greatly across all classes (look at the table with metrics below). There are classes like amusement, gratitude, where the model shows high recognition quality, and classes that pose difficulties for the model grief, relief, that do have much fewer examples in the training data. Also ONNX version of model and INT8 quantized model is available. information about them is posted in…
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