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This is a BERT Base model for emotion analysis in Japanese additionally fine-tuned for emotion detection and classification.

The model was based on tohoku-nlp/bert-base-japanese, and later finetuned on a dataset containing 10 labels of emotional blog posts.

The dataset was composed of about 1,000 sentences, with about 100 sentences each for each emotion category.

emotion_mapping = { 0: 'amaze', 1: 'anger', 2: 'dislike', 3: 'excite', 4: 'fear', 5: 'joy', 6: 'like', 7: 'relief', 8: 'sad', 9: 'shame' }

emotion_mapping = { 0: '้ฉšใ', 1: 'ๆ€’ใ‚Š', 2: 'ใ„ใ‚„', 3: 'ๆ˜‚ใ‚Š', 4: 'ๆ€–ใŒใ‚Š', 5: 'ๅ–œใณ', 6: 'ๅฅฝใ', 7: 'ๅฎ‰ใ‚‰ใŽ', 8: 'ๆ‚ฒใ—ใฟ', 9: 'ๆฅใšใ‹ใ—ใ„' }

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