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End of training

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  1. README.md +21 -2
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@@ -8,9 +8,22 @@ tags:
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  - generated_from_trainer
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  datasets:
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  - yonisaka/asr_medical_id
 
 
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  model-index:
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  - name: whisper-small-id-v2
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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
@@ -19,6 +32,9 @@ should probably proofread and complete it, then remove this comment. -->
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  # whisper-small-id-v2
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  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the ASR Medical Indonesian dataset.
 
 
 
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  ## Model description
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@@ -44,11 +60,14 @@ The following hyperparameters were used during training:
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  - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_steps: 500
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- - training_steps: 100
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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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  - yonisaka/asr_medical_id
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+ metrics:
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+ - wer
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  model-index:
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  - name: whisper-small-id-v2
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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: ASR Medical Indonesian
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+ type: yonisaka/asr_medical_id
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+ args: 'config: id, split: test'
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 0.0
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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-id-v2
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  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the ASR Medical Indonesian dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0001
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+ - Wer: 0.0
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  ## Model description
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  - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_steps: 500
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+ - training_steps: 1000
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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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+ | 0.0001 | 142.8571 | 1000 | 0.0001 | 0.0 |
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  ### Framework versions