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Baselhany
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Distilation_Whisper_base_CKP_256

Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Arabic
whisper
Generated from Trainer
Model card Files
xet
Metrics Community
Baselhany commited on
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  1. README.md +34 -28
  2. model.safetensors +1 -1
  3. runs/Jun12_07-29-00_8015bbd76758/events.out.tfevents.1749745040.8015bbd76758.19.1 +3 -0
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: 0.0857
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- - Wer: 0.1990
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  ## Model description
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@@ -49,30 +47,38 @@ 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: 10
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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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- | 2.0599 | 0.5858 | 1000 | 0.0910 | 0.2075 |
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- | 1.6156 | 1.1716 | 2000 | 0.0921 | 0.1917 |
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- | 1.5706 | 1.7575 | 3000 | 0.0891 | 0.1953 |
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- | 1.3401 | 2.3433 | 4000 | 0.0880 | 0.1882 |
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- | 1.2238 | 2.9291 | 5000 | 0.0865 | 0.1886 |
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- | 1.0654 | 3.5149 | 6000 | 0.0860 | 0.1922 |
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- | 1.0904 | 4.1008 | 7000 | 0.0859 | 0.2000 |
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- | 1.2607 | 4.6866 | 8000 | 0.0872 | 0.1882 |
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- | 1.147 | 5.2724 | 9000 | 0.0870 | 0.1944 |
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- | 1.1237 | 5.8582 | 10000 | 0.0856 | 0.1905 |
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- | 1.0093 | 6.4441 | 11000 | 0.0849 | 0.2001 |
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- | 0.9993 | 7.0299 | 12000 | 0.0839 | 0.1888 |
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- | 0.8718 | 7.6157 | 13000 | 0.0844 | 0.1894 |
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- | 0.8877 | 8.2015 | 14000 | 0.0838 | 0.1908 |
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- | 0.8187 | 8.7873 | 15000 | 0.0843 | 0.1957 |
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- | 0.8235 | 9.3732 | 16000 | 0.0838 | 0.1975 |
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- | 0.7972 | 9.9590 | 17000 | 0.0835 | 0.1911 |
 
 
 
 
 
 
 
 
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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: 0.0853
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+ - Wer: 0.1969
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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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+ | 2.0599 | 0.5858 | 1000 | 0.0910 | 0.2075 |
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+ | 1.6156 | 1.1716 | 2000 | 0.0921 | 0.1917 |
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+ | 1.5706 | 1.7575 | 3000 | 0.0891 | 0.1953 |
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+ | 1.3401 | 2.3433 | 4000 | 0.0880 | 0.1882 |
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+ | 1.2238 | 2.9291 | 5000 | 0.0865 | 0.1886 |
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+ | 1.0654 | 3.5149 | 6000 | 0.0860 | 0.1922 |
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+ | 1.0904 | 4.1008 | 7000 | 0.0859 | 0.2000 |
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+ | 1.2607 | 4.6866 | 8000 | 0.0872 | 0.1882 |
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+ | 1.147 | 5.2724 | 9000 | 0.0870 | 0.1944 |
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+ | 1.1237 | 5.8582 | 10000 | 0.0856 | 0.1905 |
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+ | 1.0093 | 6.4441 | 11000 | 0.0849 | 0.2001 |
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+ | 0.9993 | 7.0299 | 12000 | 0.0839 | 0.1888 |
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+ | 0.8718 | 7.6157 | 13000 | 0.0844 | 0.1894 |
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+ | 0.8877 | 8.2015 | 14000 | 0.0838 | 0.1908 |
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+ | 0.8187 | 8.7873 | 15000 | 0.0843 | 0.1957 |
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+ | 0.8235 | 9.3732 | 16000 | 0.0838 | 0.1975 |
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+ | 0.7972 | 9.9590 | 17000 | 0.0835 | 0.1911 |
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+ | 0.8203 | 10.5448 | 18000 | 0.0844 | 0.1866 |
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+ | 0.8593 | 11.1306 | 19000 | 0.0843 | 0.1916 |
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+ | 0.8279 | 11.7165 | 20000 | 0.0840 | 0.1905 |
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+ | 0.806 | 12.3023 | 21000 | 0.0827 | 0.1897 |
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+ | 0.8343 | 12.8881 | 22000 | 0.0832 | 0.1891 |
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+ | 0.7252 | 13.4739 | 23000 | 0.0830 | 0.1845 |
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+ | 0.7685 | 14.0598 | 24000 | 0.0830 | 0.1919 |
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+ | 0.7085 | 14.6456 | 25000 | 0.0829 | 0.1975 |
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  ### Framework versions
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