update model card README.md

README.md

@@ -21,7 +21,7 @@ model-index:
     metrics:
     - name: Wer
       type: wer
-      value: 0.4557774607703281
+      value: 0.4536376604850214
 ---
 
 <!-- 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 [airesearch/wav2vec2-large-xlsr-53-th](https://huggingface.co/airesearch/wav2vec2-large-xlsr-53-th) on the common_voice dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.0926
-- Wer: 0.4558
+- Loss: 1.2174
+- Wer: 0.4536
 
 ## Model description
 
@@ -58,23 +58,28 @@ 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: 30
-- num_epochs: 35
+- num_epochs: 50
 - mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Wer    |
 |:-------------:|:-----:|:----:|:---------------:|:------:|
-| 5.4829        | 3.23  | 100  | 3.4277          | 1.0    |
-| 3.301         | 6.45  | 200  | 3.2260          | 1.0    |
-| 2.3           | 9.68  | 300  | 1.2590          | 0.5292 |
-| 1.1601        | 12.9  | 400  | 1.0578          | 0.5892 |
-| 0.9381        | 16.13 | 500  | 1.0390          | 0.4957 |
-| 0.8211        | 19.35 | 600  | 1.0411          | 0.4679 |
-| 0.7227        | 22.58 | 700  | 1.0614          | 0.4558 |
-| 0.6805        | 25.81 | 800  | 1.0750          | 0.4579 |
-| 0.6389        | 29.03 | 900  | 1.0678          | 0.4629 |
-| 0.6045        | 32.26 | 1000 | 1.0926          | 0.4558 |
+| 5.3619        | 3.23  | 100  | 3.2891          | 1.0    |
+| 3.299         | 6.45  | 200  | 3.1670          | 1.0    |
+| 2.1179        | 9.68  | 300  | 1.1747          | 0.5221 |
+| 1.1047        | 12.9  | 400  | 1.0323          | 0.5849 |
+| 0.8974        | 16.13 | 500  | 1.0128          | 0.5029 |
+| 0.769         | 19.35 | 600  | 1.0402          | 0.4957 |
+| 0.6659        | 22.58 | 700  | 1.0902          | 0.4729 |
+| 0.6114        | 25.81 | 800  | 1.1412          | 0.4629 |
+| 0.5511        | 29.03 | 900  | 1.1156          | 0.4643 |
+| 0.5137        | 32.26 | 1000 | 1.1556          | 0.4679 |
+| 0.5132        | 35.48 | 1100 | 1.1851          | 0.4515 |
+| 0.4583        | 38.71 | 1200 | 1.1971          | 0.4529 |
+| 0.4523        | 41.94 | 1300 | 1.2182          | 0.4579 |
+| 0.4329        | 45.16 | 1400 | 1.2178          | 0.4586 |
+| 0.4502        | 48.39 | 1500 | 1.2174          | 0.4536 |
 
 
 ### Framework versions