Baselhany commited on
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Model save

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README.md CHANGED
@@ -1,27 +1,25 @@
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  ---
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  library_name: transformers
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- language:
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- - ar
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  license: apache-2.0
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- base_model: openai/whisper-base
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  tags:
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  - generated_from_trainer
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  metrics:
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  - wer
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  model-index:
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- - name: Whisper base AR - BA
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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 base AR - BA
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- This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the quran-ayat-speech-to-text dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0896
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- - Wer: 0.2038
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  ## Model description
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@@ -49,7 +47,7 @@ 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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- - num_epochs: 18
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  - mixed_precision_training: Native AMP
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  ### Training results
@@ -86,6 +84,9 @@ The following hyperparameters were used during training:
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  | 0.8382 | 16.5975 | 28000 | 0.0871 | 0.2003 |
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  | 0.8399 | 17.1903 | 29000 | 0.0872 | 0.1989 |
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  | 0.8303 | 17.7830 | 30000 | 0.0871 | 0.2022 |
 
 
 
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  ### Framework versions
 
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  ---
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  library_name: transformers
 
 
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  license: apache-2.0
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+ base_model: Baselhany/Distilation_Whisper_base_CKP_256
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  tags:
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  - generated_from_trainer
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  metrics:
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  - wer
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  model-index:
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+ - name: Distilation_Whisper_base_CKP_256
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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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+ # Distilation_Whisper_base_CKP_256
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+ This model is a fine-tuned version of [Baselhany/Distilation_Whisper_base_CKP_256](https://huggingface.co/Baselhany/Distilation_Whisper_base_CKP_256) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0895
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+ - Wer: 0.2050
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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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+ - num_epochs: 20
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  - mixed_precision_training: Native AMP
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  ### Training results
 
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  | 0.8382 | 16.5975 | 28000 | 0.0871 | 0.2003 |
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  | 0.8399 | 17.1903 | 29000 | 0.0872 | 0.1989 |
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  | 0.8303 | 17.7830 | 30000 | 0.0871 | 0.2022 |
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+ | 0.8621 | 18.3758 | 31000 | 0.0872 | 0.2022 |
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+ | 0.8784 | 18.9686 | 32000 | 0.0872 | 0.2066 |
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+ | 0.8448 | 19.5614 | 33000 | 0.0868 | 0.2076 |
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  ### Framework versions
runs/Jun10_17-47-09_710df61383f6/events.out.tfevents.1749590958.710df61383f6.19.1 ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:5e281c53a773ed377cd4cb3f642abdb35507267e67fe852b850aa96d299537d4
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+ size 412