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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: 0.1097
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- - Wer: 0.2742
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  ## Model description
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@@ -49,18 +47,28 @@ 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: 5
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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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- | 0.3035 | 0.9987 | 595 | 0.0981 | 0.2460 |
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- | 0.2664 | 1.9987 | 1190 | 0.0935 | 0.2819 |
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- | 0.2242 | 2.9987 | 1785 | 0.0878 | 0.2786 |
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- | 0.1442 | 3.9987 | 2380 | 0.0873 | 0.2561 |
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- | 0.1145 | 4.9987 | 2975 | 0.0848 | 0.2558 |
 
 
 
 
 
 
 
 
 
 
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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/Graduation_Project_distillation_Whisper_base2
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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: Graduation_Project_distillation_Whisper_base2
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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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+ # Graduation_Project_distillation_Whisper_base2
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+ This model is a fine-tuned version of [Baselhany/Graduation_Project_distillation_Whisper_base2](https://huggingface.co/Baselhany/Graduation_Project_distillation_Whisper_base2) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0746
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+ - Wer: 0.2358
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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: 15
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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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+ | 0.397 | 1.0 | 469 | 0.0686 | 0.2067 |
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+ | 0.3526 | 2.0 | 938 | 0.0674 | 0.2345 |
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+ | 0.3181 | 3.0 | 1407 | 0.0711 | 0.2225 |
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+ | 0.2689 | 4.0 | 1876 | 0.0724 | 0.2273 |
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+ | 0.2044 | 5.0 | 2345 | 0.0687 | 0.2366 |
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+ | 0.184 | 6.0 | 2814 | 0.0676 | 0.2165 |
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+ | 0.1404 | 7.0 | 3283 | 0.0673 | 0.2230 |
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+ | 0.1461 | 8.0 | 3752 | 0.0657 | 0.2049 |
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+ | 0.1269 | 9.0 | 4221 | 0.0662 | 0.2055 |
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+ | 0.1089 | 10.0 | 4690 | 0.0668 | 0.2070 |
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+ | 0.0835 | 11.0 | 5159 | 0.0639 | 0.2049 |
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+ | 0.0693 | 12.0 | 5628 | 0.0656 | 0.2152 |
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+ | 0.054 | 13.0 | 6097 | 0.0654 | 0.2160 |
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+ | 0.0419 | 14.0 | 6566 | 0.0662 | 0.2029 |
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+ | 0.0342 | 14.9685 | 7020 | 0.0668 | 0.2180 |
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  ### Framework versions
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