Update README.md

README.md

@@ -3,7 +3,25 @@ tags:
 - generated_from_trainer
 model-index:
 - name: prosody_gttbsc_distilbert-uncased-energy
-  results: []
+  results: 
+    - task:
+        type: dialogue act classification
+      dataset:
+        name: asapp/slue-phase-2
+        type: hvb
+      metrics:
+        - name: F1 macro E2E
+          type: F1 macro
+          value: 65.75
+        - name: F1 macro GT
+          type: F1 macro
+          value: 71.95
+datasets:
+- asapp/slue-phase-2
+language:
+- en
+metrics:
+- f1-macro
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -11,21 +29,20 @@ should probably proofread and complete it, then remove this comment. -->
 
 # prosody_gttbsc_distilbert-uncased-energy
 
-This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
+Ground truth text with prosody encoding residual cross attention multi-label DAC
 
 ## Model description
 
-More information needed
-
-## Intended uses & limitations
-
-More information needed
+Prosody encoder: 2 layer transformer encoder with initial dense projection  
+Backbone: [DistilBert uncased](https://huggingface.co/distilbert/distilbert-base-uncased)  
+Pooling: Self attention  
+Multi-label classification head: 2 dense layers with two dropouts 0.3 and Tanh activation inbetween  
 
 ## Training and evaluation data
 
-More information needed
+Trained on ground truth.  
+Evaluated on ground truth (GT) and normalized [Whisper small](https://huggingface.co/openai/whisper-small) transcripts (E2E). 
 
-## Training procedure
 
 ### Training hyperparameters
 
@@ -41,10 +58,6 @@ The following hyperparameters were used during training:
 - num_epochs: 20
 - mixed_precision_training: Native AMP
 
-### Training results
-
-
-
 ### Framework versions
 
 - Transformers 4.41.2