GbgMehdi commited on
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End of training

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README.md CHANGED
@@ -9,19 +9,19 @@ tags:
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  metrics:
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  - wer
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  model-index:
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- - name: Whisper Tiny English - G.Mehdi
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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
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  should probably proofread and complete it, then remove this comment. -->
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- # Whisper Tiny English - G.Mehdi
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  This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the commands_dataset dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0019
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- - Wer: 2.8333
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  ## Model description
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@@ -46,16 +46,18 @@ The following hyperparameters were used during training:
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  - seed: 42
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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: 10
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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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  | Training Loss | Epoch | Step | Validation Loss | Wer |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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- | 0.0075 | 1.0 | 75 | 0.0026 | 3.0833 |
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- | 0.0027 | 1.33 | 100 | 0.0019 | 2.8333 |
 
 
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  ### Framework versions
 
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  metrics:
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  - wer
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  model-index:
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+ - name: Whisper Tiny English 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
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  should probably proofread and complete it, then remove this comment. -->
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+ # Whisper Tiny English v2
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  This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the commands_dataset dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0003
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+ - Wer: 3.3333
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  ## Model description
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  - seed: 42
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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: 30
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+ - training_steps: 300
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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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+ | 0.0098 | 1.0 | 75 | 0.0038 | 3.3333 |
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+ | 0.0035 | 2.0 | 150 | 0.0006 | 3.75 |
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+ | 0.0031 | 3.0 | 225 | 0.0004 | 3.1667 |
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+ | 0.0012 | 4.0 | 300 | 0.0003 | 3.3333 |
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  ### Framework versions
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