update model card README.md

README.md

@@ -11,19 +11,20 @@ metrics:
 - wer
 model-index:
 - name: Whisper Small Hi - Swedish
-  results: 
+  results:
   - task:
       name: Automatic Speech Recognition
       type: automatic-speech-recognition
     dataset:
       name: Common Voice 11.0
       type: mozilla-foundation/common_voice_11_0
+      config: null
       split: None
-      args: 'config: sv-SE, split: test'
+      args: 'config: hi, split: test'
     metrics:
     - name: Wer
       type: wer
-      value: 51.31886746793579
+      value: 19.647226479524615
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -33,8 +34,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.0765
-- Wer: 51.3189
+- Loss: 0.3953
+- Wer: 19.6472
 
 ## Model description
 
@@ -53,25 +54,27 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 0.0005
+- learning_rate: 1e-05
 - train_batch_size: 16
 - eval_batch_size: 8
 - seed: 42
-- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_steps: 500
-- training_steps: 5000
-- mixed_precision_training: Native AMP
+- training_steps: 1
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Wer     |
 |:-------------:|:-----:|:----:|:---------------:|:-------:|
-| 1.5005        | 1.29  | 1000 | 1.7517          | 84.8861 |
-| 0.8752        | 2.59  | 2000 | 1.2958          | 68.8688 |
-| 0.4382        | 3.88  | 3000 | 1.1835          | 60.4152 |
-| 0.0694        | 5.17  | 4000 | 1.1659          | 55.8442 |
-| 0.0091        | 6.47  | 5000 | 1.0765          | 51.3189 |
+| 0.1331        | 1.29  | 1000 | 0.3014          | 22.3602 |
+| 0.0537        | 2.59  | 2000 | 0.2988          | 20.8572 |
+| 0.0217        | 3.88  | 3000 | 0.3093          | 20.5641 |
+| 0.004         | 5.17  | 4000 | 0.3551          | 20.0479 |
+| 0.0015        | 6.47  | 5000 | 0.3701          | 20.0022 |
+| 0.0015        | 7.76  | 6000 | 0.3769          | 19.7386 |
+| 0.0007        | 9.06  | 7000 | 0.3908          | 19.7010 |
+| 0.0006        | 10.35 | 8000 | 0.3953          | 19.6472 |
 
 
 ### Framework versions