readme: ---
  widget:
  - text: "The reduction of carbon emissions is improving for the last 2 years."
    example_title: "Example 1"
    candidate_labels: "Related to Environmental Claims, Not related to Environmental Claims"
  - text: "The weather is very sunny today."
    example_title: "Example 2"
    
    
  language: en
  datasets:
  - climatebert/environmental_claims
  tags:
  - Text Classification
  - environmental-claims
  - bert-base-uncased
  model-index:
  - name: Vinoth24/environmental_claims
    results:
    - task:
        type: text-classification
        name: Text Classification
      dataset:
        name: environmental-claims
        type: environmental-claims
        config: environmental-claims
        split: validation & test
      metrics:
      - name: Loss
        type: loss
        value: 0.488700
  ---
  
  
  # Model Card for environmental-claims
  ### Model Description
  The environmental-claims model is fine-tuned using the EnvironmentalClaims dataset on Bert base-uncased model. This model is fine-tuned with the help of Happy Transformers on the Bert base-uncased model. The EnvironmentalClaims dataset is annotated by finance and sustainable finance students and authors of Zurich University. This model is expected to predict whether the input sequence is related to real-time environmental claims or not. 
  
  
  # Usage
  ### loading the model :
  ```python
  from happytransformer import HappyTextClassification
  happy_class = HappyTextClassification(model_type="BERT", model_name="Vinoth24/environmental_claims")
  ```
  ### prediction :
  ```python
  result = happy_class.classify_text('The reduction of carbon emissions is improving for the last 2 years.')
  print(result) -- TextClassificationResult(label='LABEL_1', score=0.9948860359191895)
  print(result.label) -- LABEL_1
  print(result.score) -- 0.994
  ```
  
  ### Result Interpretation:
  LABEL_1 - Related to Environmental Claims <br />
  LABEL_0 - Not Related to Environmental Claims
  
  Feel free to train the model more with your custom Environmental claims data. Any queries will be answered. <br />Thank you! :)
  
  Created by Kasi Vinoth S from India