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README.md

@@ -1,9 +1,7 @@
 ---
-license: cc0-1.0
-tags:
-- generated_from_trainer
 datasets:
 - coscan-speech2
+license: cc0-1.0
 metrics:
 - accuracy
 - f1
@@ -11,7 +9,28 @@ metrics:
 - recall
 model-index:
 - name: wav2vec2-large-voxrex-swedish-coscan-no-region
-  results: []
+  results:
+  - dataset:
+      name: Coscan Speech
+      type: NbAiLab/coscan-speech2
+    metrics:
+    - name: Test Accuracy on Coscan Speech
+      type: accuracy
+      value: 0.6155107552811807
+    - name: Validation Accuracy on Coscan Speech
+      type: accuracy
+      value: 0.8773432861141742
+    - name: Test F1 (micro) on Coscan Speech
+      type: f1
+      value: 0.6155107552811807
+    - name: Validation F1 (micro) on Coscan Speech
+      type: f1
+      value: 0.8773432861141742
+    task:
+      name: Audio Classification
+      type: audio-classification
+tags:
+- generated_from_trainer
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -64,9 +83,33 @@ The following hyperparameters were used during training:
 | 0.0001        | 5.0   | 32340 | 1.1031          | 0.8700   | 0.8700 | 0.8700    | 0.8700 |
 
 
+### Classification report on Coscan Speech (test set)
+
+```
+                         precision    recall  f1-score   support
+
+Bergen og Ytre Vestland       0.65      0.97      0.78      1809
+     Hedmark og Oppland       0.12      0.06      0.08      2302
+               Nordland       0.97      0.47      0.63      2195
+           Oslo-området       0.78      0.42      0.55      6957
+               Sunnmøre       0.94      0.71      0.81      2636
+         Sør-Vestlandet       0.96      0.46      0.62      2860
+              Sørlandet       0.62      0.81      0.70      2490
+                  Troms       0.67      1.00      0.80      2867
+              Trøndelag       0.52      0.94      0.67      2666
+         Voss og omland       0.70      0.71      0.71      2641
+         Ytre Oslofjord       0.20      0.49      0.29      1678
+
+               accuracy                           0.62     31101
+              macro avg       0.65      0.64      0.60     31101
+           weighted avg       0.68      0.62      0.61     31101
+
+```
+
+
 ### Framework versions
 
 - Transformers 4.22.0.dev0
 - Pytorch 1.10.1+cu102
 - Datasets 2.4.1.dev0
-- Tokenizers 0.12.1
+- Tokenizers 0.12.1