AIが動く。未来が更新される。FinancialBERT-Sentiment-Analysis
The model was fine-tuned for Sentiment Analysis task on _Financial PhraseBank_ dataset. Experiments show that this model outperforms the general BERT and other financial domain-specific models. More details on `FinancialBERT`'s pre-training process can be found at: https://www.researchgate.net/publication/358284785_FinancialBERT_-_A_Pretrained_Language_Model_for_Financial_Text_Mining FinancialBERT model was fine-tuned on Financial PhraseBank, a dataset consisting of 4840 Financial News categorised by sentiment (negative, neutral, positive).
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The model was fine-tuned for Sentiment Analysis task on _Financial PhraseBank_ dataset. Experiments show that this model outperforms the general BERT and other financial domain-specific models. More details on `FinancialBERT`'s pre-training process can be found at: https://www.researchgate.net/publication/358284785_FinancialBERT_-_A_Pretrained_Language_Model_for_Financial_Text_Mining FinancialBERT model was fine-tuned on Financial PhraseBank, a dataset consisting of 4840 Financial News categorised by sentiment (negative, neutral, positive).