Update README.md

README.md

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-# Classification of patent abstracts - "green plastics" or "no green plastics"
+# Classification of patent abstracts - "Green Plastics" or "No Green Plastics"
 
-This model classifies patents into "green plastics" or "no green plastics" by their abstracts.
+This model (distilbert-base-uncased-finetuned-greenplastics-3) classifies patents into "green plastics" or "no green plastics" by their abstracts.
 
-# distilbert-base-uncased-finetuned-greenplastics-3
-
-This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the [green plastics dataset](https://huggingface.co/datasets/cwinkler/patents_green_plastics). The green patent dataset was split into 70 % training data and 30 % test data (using ".train_test_split(test_size=0.3)").
+The model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the [green plastics dataset](https://huggingface.co/datasets/cwinkler/patents_green_plastics). The green patent dataset was split into 70 % training data and 30 % test data (using ".train_test_split(test_size=0.3)").
 The model achieves the following results on the evaluation set:
 
 - Accuracy: 0.8574
 - F1: 0.8573
 
+## EPO - CodeFest on Green Plastics
+
+The model has been developed for submission to the [CodeFest on Green Plastics](https://www.epo.org/news-events/in-focus/codefest.html) by the European Patent Office (EPO).
+
+The task:
+
+**_"To develop creative and reliable artificial intelligence (AI) models for automating the identification of patents related to green plastics."_**
 
 ## Training procedure