update model card README.md

README.md

@@ -5,7 +5,7 @@ license: apache-2.0
 tags:
 - generated_from_trainer
 datasets:
-- common_voice
+- mozilla-foundation/common_voice_11_0
 metrics:
 - wer
 model-index:
@@ -15,15 +15,15 @@ model-index:
       name: Automatic Speech Recognition
       type: automatic-speech-recognition
     dataset:
-      name: Common Voice
-      type: common_voice
+      name: mozilla-foundation/common_voice_11_0
+      type: mozilla-foundation/common_voice_11_0
       config: nl
       split: test
       args: 'config: nl, split: test'
     metrics:
     - name: Wer
       type: wer
-      value: 81.03500884883744
+      value: 307.7064764692038
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -31,10 +31,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # Whisper small nl last, Berb2000-GPU
 
-This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice dataset.
+This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2568
-- Wer: 81.0350
+- Loss: 0.1789
+- Wer: 307.7065
 
 ## Model description
 
@@ -60,14 +60,17 @@ 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
-- training_steps: 1000
+- training_steps: 4000
 - mixed_precision_training: Native AMP
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Wer     |
-|:-------------:|:-----:|:----:|:---------------:|:-------:|
-| 0.079         | 1.11  | 1000 | 0.2568          | 81.0350 |
+| Training Loss | Epoch | Step | Validation Loss | Wer      |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.151         | 0.39  | 1000 | 0.2196          | 89.8038  |
+| 0.1237        | 0.78  | 2000 | 0.1978          | 46.0495  |
+| 0.044         | 1.17  | 3000 | 0.1840          | 114.0796 |
+| 0.0385        | 1.56  | 4000 | 0.1789          | 307.7065 |
 
 
 ### Framework versions