README.md

metadata

language: en
tags:
  - financial-text-analysis
  - forward-looking-statement
widget:
  - text: >-
      We expect the age of our fleet to enhance availability and reliability due
      to reduced downtime for repairs. 

Forward-looking statements (FLS) inform investors of managers’ beliefs and opinions about firm's future events or results. Identifying forward-looking statements from corporate reports can assist investors in financial analysis. FinBERT-FLS is a FinBERT model fine-tuned on 3,500 manually annotated sentences from Management Discussion and Analysis section of annual reports of Russell 3000 firms.

How to use

You can use this model with Transformers pipeline for sentiment analysis.

# tested in transformers==4.18.0 
from transformers import BertTokenizer, BertForSequenceClassification, pipeline

finbert = BertForSequenceClassification.from_pretrained('yiyanghkust/finbert-fls',num_labels=3)
tokenizer = BertTokenizer.from_pretrained('yiyanghkust/finbert-fls')
nlp = pipeline("text-classification", model=finbert, tokenizer=tokenizer)
results = nlp('We expect the age of our fleet to enhance availability and reliability due to reduced downtime for repairs.')
print(results)  # [{'label': 'Specific FLS', 'score': 0.77278733253479}]

Visit FinBERT.AI for more details on the recent development of FinBERT.