Update README.md

README.md

@@ -22,7 +22,7 @@ metrics:
 - exact_match
 library_name: transformers
 pipeline_tag: question-answering
-co2_eq_emissions: 90
+co2_eq_emissions: 100
 ---
 
 # QAmembert
@@ -160,10 +160,10 @@ result
 *Carbon emissions were 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). The hardware, runtime, cloud provider, and compute region were utilized to estimate the carbon impact.*
 
 - **Hardware Type:** A100 PCIe 40/80GB
-- **Hours used:** 4.96
+- **Hours used:** 5h and 36 min
 - **Cloud Provider:** Private Infrastructure
 - **Carbon Efficiency (kg/kWh):** 0.076kg (estimated from [electricitymaps](https://app.electricitymaps.com/zone/FR) ; we take the average carbon intensity in France for the month of March 2023, as we are unable to use the data for the day of training, which are not available.)
-- **Carbon Emitted** *(Power consumption x Time x Carbon produced based on location of power grid)*: 0.09 kg eq. CO2
+- **Carbon Emitted** *(Power consumption x Time x Carbon produced based on location of power grid)*: 0.1 kg eq. CO2
 
 
 ## Citations