update model card README.md

README.md

@@ -4,9 +4,24 @@ tags:
 - generated_from_trainer
 datasets:
 - common_voice_11_0
+metrics:
+- wer
 model-index:
 - name: openai/whisper-medium
-  results: []
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: common_voice_11_0
+      type: common_voice_11_0
+      config: vi
+      split: test
+      args: vi
+    metrics:
+    - name: Wer
+      type: wer
+      value: 20.04825619653433
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -15,6 +30,9 @@ should probably proofread and complete it, then remove this comment. -->
 # openai/whisper-medium
 
 This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the common_voice_11_0 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5422
+- Wer: 20.0483
 
 ## Model description
 
@@ -34,17 +52,20 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 1e-05
-- train_batch_size: 32
-- eval_batch_size: 64
+- train_batch_size: 16
+- eval_batch_size: 16
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_steps: 100
-- training_steps: 1
+- training_steps: 1000
 - mixed_precision_training: Native AMP
 
 ### Training results
 
+| Training Loss | Epoch | Step | Validation Loss | Wer     |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|
+| 0.0241        | 4.01  | 1000 | 0.5422          | 20.0483 |
 
 
 ### Framework versions