Update README.md

README.md

@@ -69,33 +69,16 @@ SFT using HF Transformers
 
 <!-- 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).
-
 - **Hardware Type:** A10 GPU VMs [2x24GB A10]
 - **Hours used:** [3]
 - **Cloud Provider:** [Azure]
 - **Compute Region:** [North Europe (Dublin)]
 
+- Experiments were conducted using Azure in region northeurope, which has a carbon efficiency of 0.62 kgCO$_2$eq/kWh. A cumulative of 100 hours of computation was performed on hardware of type A10 (TDP of 350W).
 
-\usepackage{hyperref}
-
-\subsection{CO2 Emission Related to Experiments}
-
-Experiments were conducted using Azure in region northeurope, which has a carbon efficiency of 0.62 kgCO$_2$eq/kWh. A cumulative of 100 hours of computation was performed on hardware of type RTX 3090 (TDP of 350W).
-
-Total emissions are estimated to be 21.7 kgCO$_2$eq of which 100 percents were directly offset by the cloud provider.
+- Total emissions are estimated to be 21.7 kgCO$_2$eq of which 100 percents were directly offset by the cloud provider.
     
-%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}
-}
+- Estimations were conducted using the [https://mlco2.github.io/impact#compute][MachineLearning Impact calculator]
                         
 
 ## Technical Specifications [optional]