Update README.md

README.md

@@ -22,6 +22,19 @@ model-index:
     - name: Wer
       type: wer
       value: 0.07238251678331667
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: common_voice_8_0
+      type: common_voice_8_0
+      config: fy-NL
+      split: test
+      args: fy-NL
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.07103627691862986
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -34,20 +47,30 @@ It achieves the following results on the evaluation set:
 - Loss: 0.0707
 - Wer: 0.0724
 
+And on the test set:
+
+- Wer: 0.0710
+
 ## Model description
 
-More information needed
+This model has been developed for my Master's thesis in "Voice Technology" at Rijksuniversiteit Groningen - Campus Fryslân. It corresponds to experiment 6 where 
+I use as training set all validated data (~ 50 hours) except the test and evaluation sets (~ 4.5 hours each). 
+The number of training hours adds up to 41 hours of Frisian speech. This varies from experiment 2 because I fine-tune on the 300M/0.3B parameters version of XLS-R.
 
 ## Intended uses & limitations
 
-More information needed
+The intended use is for recognizing Frisian speech.
+
+Limitations include no LM rescoring and using version 8.0 of Common Voice instead of 13.0.
 
 ## Training and evaluation data
 
-More information needed
+The evaluation split used is the one available in the Common Voice 8.0 Frisian subset. The train split corresponds to all of the validated data except for the recordings found in the evaluation and test splits.
 
 ## Training procedure
 
+The script used for training this model can be found in this GitHub repository: [link](https://github.com/greenw0lf/MSc-VT-Thesis/).
+
 ### Training hyperparameters
 
 The following hyperparameters were used during training: