update model card README.md

README.md

@@ -1,10 +1,6 @@
 ---
-language:
-- tr
 license: apache-2.0
 tags:
-- automatic-speech-recognition
-- common_voice
 - generated_from_trainer
 datasets:
 - common_voice
@@ -17,15 +13,15 @@ model-index:
       name: Automatic Speech Recognition
       type: automatic-speech-recognition
     dataset:
-      name: COMMON_VOICE - TR
+      name: common_voice
       type: common_voice
       config: tr
       split: test
-      args: 'Config: tr, Training split: train+validation, Eval split: test'
+      args: tr
     metrics:
     - name: Wer
       type: wer
-      value: 0.33888264732917983
+      value: 0.3267286283321418
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -33,10 +29,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # wav2vec2-common_voice-tr-output
 
-This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the COMMON_VOICE - TR dataset.
+This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.3805
-- Wer: 0.3389
+- Loss: 0.3753
+- Wer: 0.3267
 
 ## Model description
 
@@ -64,29 +60,34 @@ 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: 500
-- num_epochs: 15.0
+- num_epochs: 20.0
 - mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Wer    |
 |:-------------:|:-----:|:----:|:---------------:|:------:|
-| No log        | 0.92  | 100  | 3.6032          | 1.0    |
-| No log        | 1.83  | 200  | 3.0158          | 0.9999 |
-| No log        | 2.75  | 300  | 0.9692          | 0.8029 |
-| No log        | 3.67  | 400  | 0.5820          | 0.6161 |
-| 3.1812        | 4.59  | 500  | 0.4891          | 0.5095 |
-| 3.1812        | 5.5   | 600  | 0.4719          | 0.4853 |
-| 3.1812        | 6.42  | 700  | 0.4360          | 0.4539 |
-| 3.1812        | 7.34  | 800  | 0.4098          | 0.4283 |
-| 3.1812        | 8.26  | 900  | 0.4020          | 0.3993 |
-| 0.2212        | 9.17  | 1000 | 0.4001          | 0.3806 |
-| 0.2212        | 10.09 | 1100 | 0.4000          | 0.3873 |
-| 0.2212        | 11.01 | 1200 | 0.4070          | 0.3751 |
-| 0.2212        | 11.93 | 1300 | 0.3874          | 0.3551 |
-| 0.2212        | 12.84 | 1400 | 0.3913          | 0.3561 |
-| 0.0998        | 13.76 | 1500 | 0.3882          | 0.3492 |
-| 0.0998        | 14.68 | 1600 | 0.3795          | 0.3403 |
+| No log        | 0.92  | 100  | 3.6020          | 1.0    |
+| No log        | 1.83  | 200  | 2.9971          | 0.9999 |
+| No log        | 2.75  | 300  | 0.9174          | 0.7772 |
+| No log        | 3.67  | 400  | 0.5668          | 0.6356 |
+| 3.1619        | 4.59  | 500  | 0.4949          | 0.5256 |
+| 3.1619        | 5.5   | 600  | 0.4516          | 0.4744 |
+| 3.1619        | 6.42  | 700  | 0.4291          | 0.4575 |
+| 3.1619        | 7.34  | 800  | 0.4330          | 0.4273 |
+| 3.1619        | 8.26  | 900  | 0.4016          | 0.4145 |
+| 0.2261        | 9.17  | 1000 | 0.4214          | 0.4005 |
+| 0.2261        | 10.09 | 1100 | 0.4093          | 0.3946 |
+| 0.2261        | 11.01 | 1200 | 0.4051          | 0.3917 |
+| 0.2261        | 11.93 | 1300 | 0.3908          | 0.3719 |
+| 0.2261        | 12.84 | 1400 | 0.3850          | 0.3603 |
+| 0.1119        | 13.76 | 1500 | 0.3967          | 0.3645 |
+| 0.1119        | 14.68 | 1600 | 0.3821          | 0.3526 |
+| 0.1119        | 15.6  | 1700 | 0.3919          | 0.3519 |
+| 0.1119        | 16.51 | 1800 | 0.3763          | 0.3366 |
+| 0.1119        | 17.43 | 1900 | 0.3682          | 0.3349 |
+| 0.074         | 18.35 | 2000 | 0.3753          | 0.3323 |
+| 0.074         | 19.27 | 2100 | 0.3753          | 0.3267 |
 
 
 ### Framework versions