End of training

README.md

@@ -12,8 +12,8 @@ model-index:
 - name: w2v-bert-2.0-Vietnamese-colab-CV17.0
   results:
   - task:
-      type: automatic-speech-recognition
       name: Automatic Speech Recognition
+      type: automatic-speech-recognition
     dataset:
       name: common_voice_17_0
       type: common_voice_17_0
@@ -21,9 +21,9 @@ model-index:
       split: test
       args: vi
     metrics:
-    - type: wer
-      value: 0.26461245235069886
-      name: Wer
+    - name: Wer
+      type: wer
+      value: 0.3026260059296908
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -33,8 +33,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the common_voice_17_0 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.7535
-- Wer: 0.2646
+- Loss: 0.7833
+- Wer: 0.3026
 
 ## Model description
 
@@ -53,7 +53,7 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 3e-05
+- learning_rate: 5e-05
 - train_batch_size: 16
 - eval_batch_size: 8
 - seed: 42
@@ -62,16 +62,17 @@ The following hyperparameters were used during training:
 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_steps: 500
-- num_epochs: 10
+- num_epochs: 15
 - mixed_precision_training: Native AMP
 
 ### Training results
 
-| Training Loss | Epoch  | Step | Validation Loss | Wer    |
-|:-------------:|:------:|:----:|:---------------:|:------:|
-| 3.2974        | 3.2609 | 300  | 0.6899          | 0.3559 |
-| 0.1432        | 6.5217 | 600  | 0.7335          | 0.2991 |
-| 0.0363        | 9.7826 | 900  | 0.7535          | 0.2646 |
+| Training Loss | Epoch   | Step | Validation Loss | Wer    |
+|:-------------:|:-------:|:----:|:---------------:|:------:|
+| 5.0336        | 3.2609  | 300  | 3.2141          | 1.0132 |
+| 2.5587        | 6.5217  | 600  | 1.3607          | 0.7407 |
+| 0.2529        | 9.7826  | 900  | 0.8210          | 0.3589 |
+| 0.0571        | 13.0435 | 1200 | 0.7833          | 0.3026 |
 
 
 ### Framework versions