End of training

README.md

@@ -1,18 +1,18 @@
 ---
+license: apache-2.0
 base_model: facebook/wav2vec2-base
+tags:
+- generated_from_trainer
 datasets:
 - common_voice_13_0
-license: apache-2.0
 metrics:
 - wer
-tags:
-- generated_from_trainer
 model-index:
 - name: wav2vec2-large-xls-r-vi-colab
   results:
   - task:
-      type: automatic-speech-recognition
       name: Automatic Speech Recognition
+      type: automatic-speech-recognition
     dataset:
       name: common_voice_13_0
       type: common_voice_13_0
@@ -20,9 +20,9 @@ model-index:
       split: test[:50%]
       args: vi
     metrics:
-    - type: wer
-      value: 0.9155054191550542
-      name: Wer
+    - name: Wer
+      type: wer
+      value: 1.0
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,9 +32,9 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the common_voice_13_0 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 2.0995
-- Wer: 0.9155
-- Cer: 0.4345
+- Loss: 3.4884
+- Wer: 1.0
+- Cer: 1.0
 
 ## Model description
 
@@ -53,28 +53,33 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 3e-05
-- train_batch_size: 16
+- learning_rate: 1e-05
+- train_batch_size: 32
 - eval_batch_size: 8
 - seed: 42
 - gradient_accumulation_steps: 2
-- total_train_batch_size: 32
+- total_train_batch_size: 64
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- lr_scheduler_warmup_steps: 400
-- num_epochs: 30
+- lr_scheduler_warmup_steps: 0.1
+- num_epochs: 80
 - mixed_precision_training: Native AMP
 
 ### Training results
 
-| Training Loss | Epoch   | Step | Validation Loss | Wer    | Cer    |
-|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
-| 14.8797       | 4.4444  | 200  | 4.6129          | 1.0    | 1.0    |
-| 3.9436        | 8.8889  | 400  | 3.5521          | 1.0    | 1.0    |
-| 3.4845        | 13.3333 | 600  | 3.4997          | 1.0    | 1.0    |
-| 3.1358        | 17.7778 | 800  | 2.7899          | 1.0011 | 0.7023 |
-| 2.0727        | 22.2222 | 1000 | 2.2606          | 0.9600 | 0.4680 |
-| 1.5218        | 26.6667 | 1200 | 2.0995          | 0.9155 | 0.4345 |
+| Training Loss | Epoch   | Step | Validation Loss | Wer | Cer |
+|:-------------:|:-------:|:----:|:---------------:|:---:|:---:|
+| 9.4752        | 7.1111  | 160  | 4.4992          | 1.0 | 1.0 |
+| 4.2035        | 14.2222 | 320  | 3.9228          | 1.0 | 1.0 |
+| 3.7611        | 21.3333 | 480  | 3.6584          | 1.0 | 1.0 |
+| 3.5825        | 28.4444 | 640  | 3.5584          | 1.0 | 1.0 |
+| 3.5044        | 35.5556 | 800  | 3.5285          | 1.0 | 1.0 |
+| 3.4669        | 42.6667 | 960  | 3.5226          | 1.0 | 1.0 |
+| 3.4382        | 49.7778 | 1120 | 3.5093          | 1.0 | 1.0 |
+| 3.4183        | 56.8889 | 1280 | 3.4942          | 1.0 | 1.0 |
+| 3.4002        | 64.0    | 1440 | 3.4957          | 1.0 | 1.0 |
+| 3.3871        | 71.1111 | 1600 | 3.4896          | 1.0 | 1.0 |
+| 3.382         | 78.2222 | 1760 | 3.4884          | 1.0 | 1.0 |
 
 
 ### Framework versions