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End of training

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README.md CHANGED
@@ -7,9 +7,22 @@ tags:
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  - generated_from_trainer
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  datasets:
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  - velocity-whisper
 
 
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  model-index:
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  - name: whisper-small-finetuned-hinglish
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- results: []
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -18,6 +31,9 @@ should probably proofread and complete it, then remove this comment. -->
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  # whisper-small-finetuned-hinglish
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  This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the exclamation dataset.
 
 
 
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  ## Model description
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@@ -43,11 +59,21 @@ The following hyperparameters were used during training:
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_steps: 500
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- - num_epochs: 2
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  - mixed_precision_training: Native AMP
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  ### Training results
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  ### Framework versions
 
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  - generated_from_trainer
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  datasets:
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  - velocity-whisper
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+ metrics:
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+ - wer
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  model-index:
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  - name: whisper-small-finetuned-hinglish
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+ results:
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+ - task:
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+ name: Automatic Speech Recognition
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+ type: automatic-speech-recognition
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+ dataset:
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+ name: exclamation
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+ type: velocity-whisper
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+ args: 'config: hi, split: test'
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 17.393238434163703
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  # whisper-small-finetuned-hinglish
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  This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the exclamation dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2420
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+ - Wer: 17.3932
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  ## Model description
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_steps: 500
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+ - num_epochs: 30
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  - mixed_precision_training: Native AMP
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Wer |
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+ |:-------------:|:-------:|:----:|:---------------:|:-------:|
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+ | 0.0344 | 3.6765 | 1000 | 0.1656 | 18.9057 |
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+ | 0.0077 | 7.3529 | 2000 | 0.2077 | 19.5878 |
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+ | 0.0043 | 11.0294 | 3000 | 0.2179 | 17.6453 |
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+ | 0.0014 | 14.7059 | 4000 | 0.2176 | 16.8594 |
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+ | 0.0007 | 18.3824 | 5000 | 0.2293 | 16.6518 |
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+ | 0.0 | 22.0588 | 6000 | 0.2318 | 16.0587 |
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+ | 0.0 | 25.7353 | 7000 | 0.2384 | 17.4822 |
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+ | 0.0 | 29.4118 | 8000 | 0.2420 | 17.3932 |
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  ### Framework versions
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