Update README.md

README.md

@@ -17,14 +17,13 @@ inference: true
 
 This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [intfloat/multilingual-e5-large](https://huggingface.co/intfloat/multilingual-e5-large) as the Sentence Transformer embedding model. A [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance is used for classification.
 
-The model has been trained using an efficient few-shot learning technique that involves:
+The model has been trained on paragraphs from German company websites using an efficient few-shot learning technique that involves:
 
 1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning.
 2. Training a classification head with features from the fine-tuned Sentence Transformer.
 
 The model is designed to predict the AI capabilities of German companies based on their website texts. It is intended to be used in conjunction with the Twin_Transition_Mapper_Green model to identify companies contributing to the twin transition in Germany. For detailed information on the fine-tuning process and the results of these models, please refer to: [LINK TO WORKING PAPER]
 
-## Model Details
 
 ### Model Description
 - **Model Type:** SetFit