readme: ---
  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.  
  
  **Input**: A financial text.
  
  **Output**: Specific-FLS , Non-specific FLS, or Not-FLS.
  
  # How to use 
  You can use this model with Transformers pipeline for forward-looking statement classification.
  ```python
  # 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](https://finbert.ai/) for more details on the recent development of FinBERT.