Update README.md

README.md

@@ -9,29 +9,29 @@ tags:
 - SER
 - speech
 - emotion
-# model-index:
-# - name: Whisper-base for Speech Emotion Recognition in Russian
-#   results:
-#   - task:
-#       name: Audio Classification
-#       type: speech-emotion-recognition
-#     dataset:
-#       name: Sberdevices Dusha (crowd)
-#       type: SberDevices/Dusha
-#       args: ru
-#     metrics:
-#     - name: Test Weighted Accuracy
-#       type: acc
-#       value: 0.8364
-#     - name: Test F1 macro
-#       type: f1
-#       value: 0.8429
-#     - name: Test Recall macro
-#       type: recall
-#       value: 0.83
-#     - name: Test Precision macro
-#       type: precision
-#       value: 0.85
+model-index:
+- name: Whisper-base for Speech Emotion Recognition in Russian
+  results:
+  - task:
+      name: Audio Classification
+      type: speech-emotion-recognition
+    dataset:
+      name: Sberdevices Dusha (crowd)
+      type: SberDevices/Dusha
+      args: ru
+    metrics:
+    - name: Test Weighted Accuracy
+      type: acc
+      value: 0.8364
+    - name: Test F1 macro
+      type: f1
+      value: 0.8429
+    - name: Test Recall macro
+      type: recall
+      value: 0.83
+    - name: Test Precision macro
+      type: precision
+      value: 0.85
 metrics:
 - f1
 ---
@@ -40,7 +40,7 @@ Whisper-base encoder with classification head for speech emotion recognition.
 
 **Dusha dataset**: https://github.com/salute-developers/golos/tree/master/dusha
 
-**5 classes:**
+**Multiclass classification into 5 classes:**
 * angry 0
 * sad 1
 * neutral 2
@@ -49,7 +49,7 @@ Whisper-base encoder with classification head for speech emotion recognition.
 
 Model was fine-tuned on full Dusha-crowd with
 * augmentations Time Shift, Time Masking and Colored Noise;
-* Weighted batch sampler.
+* WeightedRandomSampler.
 
 ## Usage
 ```python