Average Model Cost: $0.0000
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Models by this creator
FinancialBERT is a BERT model that has been pre-trained on a large dataset of financial texts. Its purpose is to improve NLP research and practice in the financial domain by providing a pre-trained model that can be used without the need for significant computational resources. The model has been fine-tuned for sentiment analysis using the Financial PhraseBank dataset and has been shown to outperform general BERT models and other financial domain-specific models. The model can be used for sentiment analysis tasks on financial text data using Transformers pipeline.
FinancialBERT is a BERT model pre-trained on a large corpora of financial texts. The purpose is to enhance financial NLP research and practice in financial domain, hoping that financial practitioners and researchers can benefit from it without the necessity of the significant computational resources required to train the model. The model was trained on a large corpus of financial texts: More details on FinancialBERT can be found at: https://www.researchgate.net/publication/358284785_FinancialBERT_-_A_Pretrained_Language_Model_for_Financial_Text_Mining