End of training

README.md

@@ -5,7 +5,7 @@ tags:
 - whisper-event
 - generated_from_trainer
 datasets:
-- common_voice_15_0
+- common_voice_17_0
 metrics:
 - wer
 model-index:
@@ -15,15 +15,15 @@ model-index:
       name: Automatic Speech Recognition
       type: automatic-speech-recognition
     dataset:
-      name: common_voice_15_0
-      type: common_voice_15_0
+      name: common_voice_17_0
+      type: common_voice_17_0
       config: da
       split: test
       args: da
     metrics:
     - name: Wer
       type: wer
-      value: 28.276087362329662
+      value: 28.635316438541807
 ---
 
 <!-- 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 da-nst
 
-This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the common_voice_15_0 dataset.
+This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the common_voice_17_0 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.7829
-- Wer: 28.2761
+- Loss: 0.8780
+- Wer: 28.6353
 
 ## Model description
 
@@ -62,18 +62,24 @@ 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: 5000
+- training_steps: 11000
 - mixed_precision_training: Native AMP
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Wer     |
-|:-------------:|:-----:|:----:|:---------------:|:-------:|
-| 0.0046        | 4.03  | 1000 | 0.7389          | 31.9209 |
-| 0.003         | 9.02  | 2000 | 0.7225          | 29.6108 |
-| 0.0001        | 14.01 | 3000 | 0.7554          | 28.3788 |
-| 0.0           | 18.04 | 4000 | 0.7761          | 28.3508 |
-| 0.0           | 23.03 | 5000 | 0.7829          | 28.2761 |
+| Training Loss | Epoch | Step  | Validation Loss | Wer     |
+|:-------------:|:-----:|:-----:|:---------------:|:-------:|
+| 0.0096        | 4.01  | 1000  | 0.7403          | 31.2960 |
+| 0.0046        | 9.0   | 2000  | 0.7646          | 29.8505 |
+| 0.0016        | 13.02 | 3000  | 0.7695          | 30.8398 |
+| 0.0009        | 18.01 | 4000  | 0.7821          | 31.2102 |
+| 0.0006        | 22.02 | 5000  | 0.8035          | 31.6303 |
+| 0.0011        | 27.01 | 6000  | 0.8169          | 29.6336 |
+| 0.0001        | 32.0  | 7000  | 0.8244          | 29.6246 |
+| 0.0           | 36.01 | 8000  | 0.8461          | 28.8205 |
+| 0.0           | 41.01 | 9000  | 0.8633          | 28.7754 |
+| 0.0           | 45.02 | 10000 | 0.8738          | 28.6986 |
+| 0.0           | 50.01 | 11000 | 0.8780          | 28.6353 |
 
 
 ### Framework versions