Update README.md

README.md

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 The environmental-claims model is fine-tuned on the [EnvironmentalClaims](https://huggingface.co/datasets/climatebert/environmental_claims) dataset by using the [climatebert/distilroberta-base-climate-f](https://huggingface.co/climatebert/distilroberta-base-climate-f) model as pre-trained language model. The underlying methodology can be found in our [research paper](https://arxiv.org/abs/2209.00507).
 
+## Climate Performance Card
+
+| environmental-claims                                                     |                |
+|--------------------------------------------------------------------------|----------------|
+| 1. Is the resulting model publicly available?                            | Yes            |
+| 2. How much time does the training of the final model take?              | < 5 min        |
+| 3. How much time did all experiments take (incl. hyperparameter search)? | 60 hours       |
+| 4. What was the power of GPU and CPU?                                    | 0.3 kW         |
+| 5. At which geo location were the computations performed?                | Switzerland    |
+| 6. What was the energy mix at the geo location?                          | 89 gCO2eq/kWh  |
+| 7. How much CO2eq was emitted to train the final model?                  | 2.2 g          |
+| 8. How much CO2eq was emitted for all experiments?                       | 1.6 kg         |
+| 9. What is the average CO2eq emission for the inference of one sample?   | 0.0067 mg      |
+| 10. Which positive environmental impact can be expected from this work?  | This work can help detect and evaluate environmental claims and thus have a positive impact on the environment in the future. |
+| 11. Comments                                                             | - |
+
 ### Citation Information
 
 ```bibtex