Update README.md

README.md

@@ -6,11 +6,27 @@ tags:
 - automatic-speech-recognition
 - mozilla-foundation/common_voice_8_0
 - generated_from_trainer
+- ug
+- robust-speech-event
 datasets:
-- common_voice
+- - mozilla-foundation/common_voice_8_0
 model-index:
-- name: xls-r-uyghur-cv8
-  results: []
+- name: XLS-R-300M Uyghur CV8
+  results:
+  - task: 
+      name: Automatic Speech Recognition 
+      type: automatic-speech-recognition
+    dataset:
+      name: Common Voice 8
+      type: mozilla-foundation/common_voice_8_0
+      args: ug
+    metrics:
+       - name: Test WER
+         type: wer
+         value: 30.50
+       - name: Test CER
+         type: cer
+         value: 5.80
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -25,18 +41,26 @@ It achieves the following results on the evaluation set:
 
 ## Model description
 
-More information needed
+For a description of the model architecture, see [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m)
+
+The model vocabulary consists of the alphabetic characters of the [Perso-Arabic script for the Uyghur language](https://omniglot.com/writing/uyghur.htm), with punctuation removed.
 
 ## Intended uses & limitations
 
-More information needed
+This model is expected to be of some utility for low-fidelity use cases such as:
+- Draft video captions
+- Indexing of recorded broadcasts
+
+The model is not reliable enough to use as a substitute for live captions for accessibility purposes, and it should not be used in a manner that would infringe the privacy of any of the contributors to the Common Voice dataset nor any other speakers.
 
 ## Training and evaluation data
 
-More information needed
+The combination of `train` and `dev` of common voice official splits were used as training data. The official `test` split was used as validation data as well as for final evaluation.
 
 ## Training procedure
 
+The featurization layers of the XLS-R model are frozen while tuning a final CTC/LM layer on the Uyghur CV8 example sentences. A ramped learning rate is used with an initial warmup phase of 2000 steps, a max of 0.0001, and cooling back towards 0 for the remainder of the 9400 steps (100 epochs).
+
 ### Training hyperparameters
 
 The following hyperparameters were used during training: