Update README.md

README.md

@@ -100,11 +100,25 @@ For more details and results, refer to the paper.
 
 <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
 
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+Carbon emissions were estimated by taking power curves from experiment tracking and using emissions data provided by the University of Colorado Research Computing Group.
 
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
+For hyperparameter tuning, the amount of time to train a single base model was extrapolated to 24 hours, which was the rough amount of time to hyperparameter tune each model. The table below provides a best-effort estimation of the amount of CO2 emitted per model, measured in kg.
+
+
+|      Model      | Base Model CO2 | Hyperparameter Tune CO2 | Tuned Model CO2 |
+|:---------------:|:--------------:|:-----------------------:|:---------------:|
+|     Full MLP    |     0.00314    |          0.137          |     0.00534     |
+| First-order MLP |     0.00319    |          0.139          |     0.004228    |
+|  Dendrogram MLP |    0.000802    |          0.0491         |     0.00423     |
+|  ConvNeXt-Tiny  |      0.782     |           3.69          |      0.153      |
+| EfficientNet-B0 |      0.256     |           2.67          |      0.0914     |
+| EfficientNet-B3 |      0.668     |           2.96          |      0.364      |
+| EfficientNet-B7 |      0.806     |           3.41          |      0.330      |
+|    ResNet-18    |      0.139     |           2.70          |      0.0325     |
+|    ResNet-50    |      0.349     |           3.19          |      0.0915     |
+|    ResNet-152   |      0.726     |           3.60          |      0.176      |
+
+From this, we provide a rough estimate that the entire training and hyperparameter tuning process emitted approximately 27.5 kg of CO2. This number is likely slightly higher, as this figure does not account for unsuccessful runs.
 
 ## Technical Specifications