Update app.py

app.py

@@ -4,11 +4,10 @@ from transformers import Wav2Vec2ForSequenceClassification, Wav2Vec2Processor
 import librosa
 
 # Placeholder model (Replace later with your trained model)
-MODEL_NAME = "audeering/wav2vec2-large-robust-12-ft-emotion-msp-dim"
+MODEL_NAME = "ameliabb0913/emotion-classifier"
 processor = Wav2Vec2Processor.from_pretrained(MODEL_NAME)
-model = Wav2Vec2ForSequenceClassification.from_pretrained(
-    MODEL_NAME, ignore_mismatched_sizes=True
-)
+model = Wav2Vec2ForSequenceClassification.from_pretrained(MODEL_NAME)
+model.eval()
 
 # Emotion labels (based on the dataset used to train the model)
 id2label = {
@@ -16,11 +15,12 @@ id2label = {
     1: "Happy",
     2: "Sad",
     3: "Angry",
-    4: "Surprised",
+    4: "Fearful",
     5: "Disgusted",
-    6: "Fearful"
+    6: "Surprised"
 }
 
+
 # Function to classify emotions from audio
 def classify_emotion(audio_file):
     # Load and process audio