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Label Scheme

Component Labels
textcat_multilabel negative, neutral, positive

Accuracy

Type Score
CATS_SCORE 100.00
CATS_MACRO_P 98.32
CATS_MACRO_R 99.06
CATS_MACRO_F 98.68
CATS_MACRO_AUC 100.00

Performance

METHOD SCORE MARCO_P MARCO_R MARCO_F1
RAW 0.999969 0.983160 0.990559 0.986817
Remove Emoji 0.999981 0.991312 0.998311 0.994768
Emoji to Description 0.999898 0.989309 0.981696 0.985458
Remove Punctuation 0.999239 0.991312 0.998311 0.994768
CATEGORY PRECISION RECALL F1
negative 0.996534 0.996534 0.996534
neutral 0.954545 0.976744 0.965517
positive 0.998400 0.998400 0.998400
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Dataset used to train scfengv/TVL_Sentiment_Classifier