Update README.md

README.md

@@ -25,7 +25,12 @@ should probably proofread and complete it, then remove this comment. -->
 
 # er-model
 
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+
+## Model description
+
 This model is a fine-tuned version of [indolem/indobertweet-base-uncased](https://huggingface.co/indolem/indobertweet-base-uncased) on [The PRDECT-ID Dataset](https://www.kaggle.com/datasets/jocelyndumlao/prdect-id-indonesian-emotion-classification), it is a compilation of Indonesian product reviews that come with emotion and sentiment labels. These reviews were gathered from one of Indonesia's largest e-commerce platforms, Tokopedia..
+It has been trained to classify text into six different emotion categories: happy, sadness, anger, love, and fear.
 It achieves the following results on the evaluation set:
 - Loss: 0.6762
 - Accuracy: 0.6981
@@ -33,9 +38,6 @@ It achieves the following results on the evaluation set:
 - Recall: 0.6981
 - F1: 0.6963
 
-## Model description
-
-It has been trained to classify text into six different emotion categories: happy, sadness, anger, love, and fear.