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End of training

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  1. README.md +27 -2
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@@ -9,9 +9,22 @@ tags:
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  - generated_from_trainer
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  datasets:
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  - Chinese_english
 
 
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  model-index:
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  - name: Whisper tiny Chinese
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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
@@ -20,6 +33,9 @@ should probably proofread and complete it, then remove this comment. -->
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  # Whisper tiny Chinese
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  This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Chinese English dataset.
 
 
 
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  ## Model description
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@@ -45,7 +61,16 @@ The following hyperparameters were used during training:
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  - optimizer: Use OptimizerNames.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: 1400
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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  - generated_from_trainer
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  datasets:
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  - Chinese_english
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+ metrics:
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+ - wer
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  model-index:
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  - name: Whisper tiny Chinese
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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: Chinese English
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+ type: Chinese_english
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+ args: 'config: default, split: test'
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 15.933280381254963
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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 tiny Chinese
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  This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Chinese English dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3506
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+ - Wer: 15.9333
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  ## Model description
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  - optimizer: Use OptimizerNames.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: 600
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Wer |
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+ |:-------------:|:------:|:----:|:---------------:|:-------:|
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+ | 0.3967 | 0.6667 | 200 | 0.4181 | 20.5401 |
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+ | 0.2614 | 1.3333 | 400 | 0.3771 | 18.1255 |
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+ | 0.222 | 2.0 | 600 | 0.3506 | 15.9333 |
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+
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  ### Framework versions
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