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update model card README.md

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@@ -5,9 +5,24 @@ tags:
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  - generated_from_trainer
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  datasets:
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  - PolyAI/minds14
 
 
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  model-index:
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  - name: whisper-tiny-enUS
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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
@@ -17,14 +32,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the PolyAI/minds14 dataset.
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  It achieves the following results on the evaluation set:
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- - eval_loss: 0.6151
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- - eval_wer_ortho: 24.3412
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- - eval_wer: 0.2421
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- - eval_runtime: 9.0197
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- - eval_samples_per_second: 12.417
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- - eval_steps_per_second: 0.776
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- - epoch: 35.71
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- - step: 500
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  ## Model description
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@@ -52,7 +62,14 @@ 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: 100
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- - training_steps: 5000
 
 
 
 
 
 
 
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  ### Framework versions
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  - generated_from_trainer
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  datasets:
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  - PolyAI/minds14
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+ metrics:
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+ - wer
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  model-index:
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  - name: whisper-tiny-enUS
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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: PolyAI/minds14
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+ type: PolyAI/minds14
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+ config: en-US
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+ split: train
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+ args: en-US
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 0.23076923076923078
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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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  This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the PolyAI/minds14 dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6018
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+ - Wer Ortho: 0.2351
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+ - Wer: 0.2308
 
 
 
 
 
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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: 100
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+ - training_steps: 500
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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 Ortho | Wer |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
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+ | 0.0003 | 35.71 | 500 | 0.6018 | 0.2351 | 0.2308 |
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+
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  ### Framework versions
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