Update README.md

README.md

@@ -13,9 +13,9 @@ model-index:
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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-# working
+# Herbal Multilabel Classification
 
-This model is a fine-tuned version of [medicalai/ClinicalBERT](https://huggingface.co/medicalai/ClinicalBERT) on an unknown dataset.
+This model is a fine-tuned version of [medicalai/ClinicalBERT](https://huggingface.co/medicalai/ClinicalBERT) on a custom dataset.
 It achieves the following results on the evaluation set:
 - Loss: 0.0108
 - F1: 0.9834
@@ -24,11 +24,20 @@ It achieves the following results on the evaluation set:
 
 ## Model description
 
-More information needed
+It is a multilabel classification model that deals with 10 herbal plants 
+(Jackfruit, Sambong, Lemon, Jasmine, Mango, Mint, Ampalaya, Malunggay, Guava, Lagundi)
+which are abundant in the Philippines.
+The model classifies a herbal(s) that is/are applicable based on the input symptom
+of the user.
 
 ## Intended uses & limitations
 
-More information needed
+The model is created for the purpose of completing a University course.
+It will be integrated to a React Native mobile application for the
+project.
+The model performs well when the input of the user contains a symptom that has been trained
+to the model from the dataset. However, other words/inputs that do not present a significance to
+the purpose of the model would generate an underwhelming and inaccurate result.
 
 ## Training and evaluation data