Update README.md

README.md

@@ -29,7 +29,7 @@ model-index:
 
 # SciClimateBERT 🌎🔬
 
-**SciClimateBERT** is a domain-adapted version of **ClimateBERT**, further pretrained on peer-reviewed scientific papers focused on climate change. While ClimateBERT is tuned for general climate-related text, SciClimateBERT narrows the focus to high-quality academic content, improving performance in scientific NLP applications.
+**SciClimateBERT** is a domain-adapted version of [**ClimateBERT**](https://huggingface.co/climatebert/distilroberta-base-climate-f), further pretrained on peer-reviewed scientific papers focused on climate change. While ClimateBERT is tuned for general climate-related text, SciClimateBERT narrows the focus to high-quality academic content, improving performance in scientific NLP applications.
 
 ## 🔍 Overview
 
@@ -52,11 +52,22 @@ Evaluated on **ClimaBench**, a benchmark suite for climate-focused NLP tasks:
 
 While based on ClimateBERT, this model focuses on structured scientific input, making it ideal for downstream applications in climate science and research automation.
 
+Climate performance model card:
+|SciClimateBERT||
+|---------------------------------|-----------------------------|
+| 1. Model publicly available?    | Yes                         |
+| 2. Time to train final model    |300h                        | 
+| 3. Time for all experiments     | 1,226h $\sim$ 51 days       |
+| 4. Power of GPU and CPU         | 0.250 kW + 0.013 kW         |
+| 5. Location for computations    | Croatia                     |
+| 6. Energy mix at location       | 224.71 gCO$_2$eq/kWh        |
+| 7. CO$_2$eq for final model     | 18 kg CO$_2$  |
+| 8. CO$_2$eq for all experiments | 74 kg CO$_2$                |
+
 ## 🧪 Intended Uses
 
 **Use for:**
 - Scientific climate change text classification and extraction
-- NLP-powered climate science discovery tools
 - Knowledge base and graph construction in climate policy and research domains
 
 **Not suitable for:**