update model card README.md

README.md

@@ -21,7 +21,7 @@ model-index:
     metrics:
     - name: Wer
       type: wer
-      value: 0.8409155834880732
+      value: 0.5262462505356378
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -31,8 +31,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the common_voice_8_0 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.2060
-- Wer: 0.8409
+- Loss: 0.9269
+- Wer: 0.5262
 
 ## Model description
 
@@ -58,27 +58,25 @@ The following hyperparameters were used during training:
 - optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 90
+- num_epochs: 80
 - mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Wer    |
 |:-------------:|:-----:|:----:|:---------------:|:------:|
-| 13.1755       | 6.25  | 50   | 4.7246          | 0.9927 |
-| 8.0106        | 12.5  | 100  | 3.8216          | 0.9996 |
-| 3.4536        | 18.75 | 150  | 3.0254          | 1.0    |
-| 3.1828        | 25.0  | 200  | 2.9839          | 1.0    |
-| 3.1087        | 31.25 | 250  | 2.9887          | 1.0    |
-| 3.0176        | 37.5  | 300  | 2.8903          | 1.0    |
-| 2.912         | 43.75 | 350  | 2.6903          | 1.0    |
-| 2.7648        | 50.0  | 400  | 2.1968          | 1.0016 |
-| 2.1665        | 56.25 | 450  | 1.6039          | 0.9838 |
-| 1.8149        | 62.5  | 500  | 1.3367          | 0.9484 |
-| 1.6385        | 68.75 | 550  | 1.2353          | 0.9340 |
-| 1.314         | 75.0  | 600  | 1.2081          | 0.8834 |
-| 1.0963        | 81.25 | 650  | 1.2016          | 0.8416 |
-| 1.2322        | 87.5  | 700  | 1.2060          | 0.8409 |
+| 9.2929        | 6.25  | 50   | 3.0514          | 1.0    |
+| 3.315         | 12.5  | 100  | 3.2255          | 1.0    |
+| 3.1506        | 18.75 | 150  | 2.9924          | 1.0    |
+| 2.9773        | 25.0  | 200  | 2.2199          | 1.0    |
+| 2.1616        | 31.25 | 250  | 1.1423          | 0.8603 |
+| 1.6887        | 37.5  | 300  | 0.9730          | 0.7020 |
+| 1.1178        | 43.75 | 350  | 0.8971          | 0.6323 |
+| 0.9512        | 50.0  | 400  | 0.9040          | 0.5960 |
+| 0.7696        | 56.25 | 450  | 0.9232          | 0.5713 |
+| 0.7348        | 62.5  | 500  | 0.9203          | 0.5412 |
+| 0.9312        | 68.75 | 550  | 0.9673          | 0.5376 |
+| 0.6519        | 75.0  | 600  | 0.9269          | 0.5262 |
 
 
 ### Framework versions