Update README.md

README.md

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 ## SetFit with TurkuNLP/bert-base-finnish-cased-v1
 
-This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification of actions in asynchronous conversation. This particular model detects if a comment includes a question or not. The configuration of the model is that the model is based on only one annotator's annotations (annotator A3). Metric evaluations are based on conservative ground truth (see paper). This SetFit model uses TurkuNLP/bert-base-finnish-cased-v1 as the Sentence Transformer embedding model. A LogisticRegression instance is used for classification.
+This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification of actions in asynchronous conversation. This particular model detects if a comment includes a question or not. The configuration of the model is that the model is based on only one annotator's annotations (annotator A3). Metric evaluations are based on conservative ground truth (see paper). This SetFit model uses TurkuNLP/bert-base-finnish-cased-v1 as the Sentence Transformer embedding model (using word embeddings). A LogisticRegression instance is used for classification.
 The model has been trained using an efficient few-shot learning technique that involves:
 
 1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning.