End of training

README.md

@@ -7,22 +7,9 @@ tags:
 - generated_from_trainer
 datasets:
 - velocity-whisper
-metrics:
-- wer
 model-index:
 - name: whisper-small-finetuned-hinglish
-  results:
-  - task:
-      name: Automatic Speech Recognition
-      type: automatic-speech-recognition
-    dataset:
-      name: exclamation
-      type: velocity-whisper
-      args: 'config: hi, split: test'
-    metrics:
-    - name: Wer
-      type: wer
-      value: 17.393238434163703
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -31,9 +18,6 @@ should probably proofread and complete it, then remove this comment. -->
 # whisper-small-finetuned-hinglish
 
 This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the exclamation dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.2420
-- Wer: 17.3932
 
 ## Model description
 
@@ -59,26 +43,16 @@ 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: 30
+- num_epochs: 10
 - mixed_precision_training: Native AMP
 
 ### Training results
 
-| Training Loss | Epoch   | Step | Validation Loss | Wer     |
-|:-------------:|:-------:|:----:|:---------------:|:-------:|
-| 0.0344        | 3.6765  | 1000 | 0.1656          | 18.9057 |
-| 0.0077        | 7.3529  | 2000 | 0.2077          | 19.5878 |
-| 0.0043        | 11.0294 | 3000 | 0.2179          | 17.6453 |
-| 0.0014        | 14.7059 | 4000 | 0.2176          | 16.8594 |
-| 0.0007        | 18.3824 | 5000 | 0.2293          | 16.6518 |
-| 0.0           | 22.0588 | 6000 | 0.2318          | 16.0587 |
-| 0.0           | 25.7353 | 7000 | 0.2384          | 17.4822 |
-| 0.0           | 29.4118 | 8000 | 0.2420          | 17.3932 |
 
 
 ### Framework versions
 
 - Transformers 4.41.2
 - Pytorch 2.3.0+cu121
-- Datasets 2.19.1
+- Datasets 2.19.2
 - Tokenizers 0.19.1

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