Update README.md

README.md

@@ -162,13 +162,34 @@ The model was evaluated using a separate test set, comprising 10% of the origina
 
 <!-- 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 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). -->
 
-- **Hardware Type:** NVIDIA GPUs
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
+
+\usepackage{hyperref}
+
+\subsection{CO2 Emission Related to Experiments}
+
+Experiments were conducted using a private infrastructure, which has a carbon efficiency of 0.432 kgCO$_2$eq/kWh. A cumulative of 10 hours of computation was performed on hardware of type GTX 1080 (TDP of 180W).
+
+Total emissions are estimated to be 0.78 kgCO$_2$eq of which 0 percents were directly offset.
+    
+%Uncomment if you bought additional offsets:
+%XX kg CO2eq were manually offset through \href{link}{Offset Provider}.
+
+Estimations were conducted using the \href{https://mlco2.github.io/impact#compute}{MachineLearning Impact calculator} presented in \cite{lacoste2019quantifying}.
+
+@article{lacoste2019quantifying,
+  title={Quantifying the Carbon Emissions of Machine Learning},
+  author={Lacoste, Alexandre and Luccioni, Alexandra and Schmidt, Victor and Dandres, Thomas},
+  journal={arXiv preprint arXiv:1910.09700},
+  year={2019}
+}
+                        
+
+- **Hardware Type:** NVIDIA GPUs (GTX 1080)
+- **Hours used:** 10
+- **Cloud Provider:** Private Infrastructure
+- **Carbon Emitted:** 0.78 kgCO
 
 ## Technical Specifications