FinBERT: A Pretrained Language Model for Financial Communications
Paper • 2006.08097 • Published
This repository is a fork of yiyanghkust/finbert-pretrain
All credits to @yiyanghkust.
I added the TensorFlow model and a proper tokenizer.json
FinBERT is a BERT model pre-trained on financial communication text. The purpose is to enhance financial NLP research and practice. It is trained on the following three financial communication corpus. The total corpora size is 4.9B tokens.
- Corporate Reports 10-K & 10-Q: 2.5B tokens
- Earnings Call Transcripts: 1.3B tokens
- Analyst Reports: 1.1B tokens
More details on FinBERT's pre-training process can be found at: https://arxiv.org/abs/2006.08097
FinBERT can be further fine-tuned on downstream tasks. Specifically, we have fine-tuned FinBERT on an analyst sentiment classification task, and the fine-tuned model is shared at https://huggingface.co/yiyanghkust/finbert-tone
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