update model card README.md

README.md

@@ -1,8 +1,6 @@
 ---
 license: apache-2.0
 tags:
-- automatic-speech-recognition
-- google/fleurs
 - generated_from_trainer
 datasets:
 - fleurs
@@ -15,15 +13,15 @@ model-index:
       name: Automatic Speech Recognition
       type: automatic-speech-recognition
     dataset:
-      name: GOOGLE/FLEURS - PS_AF
+      name: fleurs
       type: fleurs
       config: ps_af
       split: test
-      args: 'Config: ps_af, Training split: train+validation, Eval split: test'
+      args: ps_af
     metrics:
     - name: Wer
       type: wer
-      value: 0.9322987721691678
+      value: 0.9294849931787176
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -31,11 +29,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 # facebook/wav2vec2-xls-r-1b
 
-This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the GOOGLE/FLEURS - PS_AF dataset.
+This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the fleurs dataset.
 It achieves the following results on the evaluation set:
-- Loss: 4.9040
-- Wer: 0.9323
-- Cer: 0.9546
+- Loss: 4.1921
+- Wer: 0.9295
+- Cer: 0.9608
 
 ## Model description
 
@@ -63,7 +61,7 @@ The following hyperparameters were used during training:
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_steps: 1000
-- training_steps: 500
+- training_steps: 1000
 - mixed_precision_training: Native AMP
 
 ### Training results
@@ -72,9 +70,10 @@ The following hyperparameters were used during training:
 |:-------------:|:-----:|:----:|:------:|:---------------:|:------:|
 | 19.9558       | 1.27  | 100  | 3.2660 | 20.9197         | 1.0    |
 | 19.7186       | 2.53  | 200  | 1.1692 | 19.2447         | 1.0    |
-| 15.203        | 3.8   | 300  | 15.0053| 0.9998          | 0.9687 |
-| 6.4303        | 5.06  | 400  | 6.5437 | 0.9632          | 0.9911 |
-| 4.5712        | 6.33  | 500  | 4.9040 | 0.9323          | 0.9546 |
+| 15.203        | 3.8   | 300  | 0.9687 | 15.0053         | 0.9998 |
+| 6.4303        | 5.06  | 400  | 0.9911 | 6.5437          | 0.9632 |
+| 4.5712        | 6.33  | 500  | 0.9546 | 4.9040          | 0.9323 |
+| 3.3986        | 12.66 | 1000 | 4.1921 | 0.9295          | 0.9608 |
 
 
 ### Framework versions