Update README.md

README.md

@@ -1,7 +1,14 @@
+---
+license: mit
+base_model:
+- aadel4/Wav2vec_Classroom
+- facebook/wav2vec2-large-robust
+pipeline_tag: automatic-speech-recognition
+---
 ## Model Card: Wav2vec_Classroom_FT
 
 ### Model Overview
-**Model Name:**Wav2vec_Classroom_FT  
+**Model Name:** Wav2vec_Classroom_FT  
 **Version:** 1.0  
 **Developed By:** Ahmed Adel Attia (University of Maryland and Stanford University)  
 **Date:** 2025  
@@ -11,6 +18,8 @@ NCTE-Baseline-ASR is an automatic speech recognition (ASR) model trained for cla
 
 This model is adapted from **[Wav2vec-Classroom](https://huggingface.co/aadel4/Wav2vec_Classroom)**, which was trained using continued pretraining (CPT) on large-scale unlabeled classroom speech data. The adaptation involves direct fine-tuning on a limited transcribed dataset.
 
+This model was originally trained using the fairseq library then ported into Huggingface.
+
 **Use Case:**  
 - Speech-to-text transcription for classroom environments.  
 - ASR applications requiring high precision with limited data.  
@@ -43,5 +52,4 @@ This model is adapted from **[Wav2vec-Classroom](https://huggingface.co/aadel4/W
 ### Usage Request
 If you use the NCTE-Baseline-ASR model in your research, please acknowledge this work and refer to the original paper submitted to Interspeech 2025.
 
-For inquiries or collaborations, please contact the authors of the original paper.
-
+For inquiries or collaborations, please contact the authors of the original paper.