Update README.md

README.md

@@ -155,7 +155,7 @@ model-index:
     source:
       name: Kaggle Evaluation Notebook
       url: >-
-        https://www.kaggle.com/code/ravindranlogasanjeev/evaluation-logasanjeev-goemotions-bert/notebook
+        https://www.kaggle.com/code/ravindranlogasanjeev/evaluation-logasanjeev-emotion-analyzer-bert/notebook
 ---
 
 # Emotion Analyzer Bert
@@ -175,7 +175,7 @@ Fine-tuned [BERT-base-uncased](https://huggingface.co/bert-base-uncased) on [GoE
 
 ## Try It Out
 
-For accurate predictions with optimized thresholds, use the [Gradio demo](https://logasanjeev-emotion-analyzer-bert.hf.space). The demo now includes preprocessed text and the top 5 predicted emotions, in addition to thresholded predictions. Example predictions:
+For accurate predictions with optimized thresholds, use the [Gradio demo](https://logasanjeev-emotion-analyzer-bert-demo.hf.space). The demo now includes preprocessed text and the top 5 predicted emotions, in addition to thresholded predictions. Example predictions:
 
 - **Input**: "I’m thrilled to win this award! 😄"
   - **Output**: `excitement: 0.5836, joy: 0.5290`
@@ -193,7 +193,7 @@ For accurate predictions with optimized thresholds, use the [Gradio demo](https:
 - **Hamming Loss**: 0.0377
 - **Avg Positive Predictions**: 1.4789
 
-For a detailed evaluation, including class-wise accuracy, precision, recall, F1, MCC, support, and thresholds, along with visualizations, check out the [Kaggle notebook](https://www.kaggle.com/code/ravindranlogasanjeev/evaluation-logasanjeev-goemotions-bert/notebook).
+For a detailed evaluation, including class-wise accuracy, precision, recall, F1, MCC, support, and thresholds, along with visualizations, check out the [Kaggle notebook](https://www.kaggle.com/code/ravindranlogasanjeev/evaluation-logasanjeev-emotion-analyzer-bert/notebook).
 
 ### Class-Wise Performance