Baselhany commited on
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README.md CHANGED
@@ -1,26 +1,24 @@
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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: 0.0925
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  - Wer: 0.1967
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Wer |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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- | 2.373 | 1.0 | 625 | 0.0946 | 0.1911 |
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- | 1.8885 | 2.0 | 1250 | 0.0937 | 0.1913 |
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- | 1.5793 | 3.0 | 1875 | 0.0939 | 0.1948 |
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- | 1.4038 | 4.0 | 2500 | 0.0925 | 0.1898 |
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- | 1.1949 | 5.0 | 3125 | 0.0903 | 0.1919 |
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- | 1.0817 | 6.0 | 3750 | 0.0892 | 0.1911 |
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- | 1.0321 | 7.0 | 4375 | 0.0896 | 0.1877 |
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- | 0.9399 | 8.0 | 5000 | 0.0887 | 0.1982 |
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- | 0.8522 | 9.0 | 5625 | 0.0883 | 0.1938 |
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- | 0.8565 | 10.0 | 6250 | 0.0880 | 0.1944 |
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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_bigger_samples
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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_bigger_samples
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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_bigger_samples
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+ This model is a fine-tuned version of [Baselhany/Distilation_Whisper_base_bigger_samples](https://huggingface.co/Baselhany/Distilation_Whisper_base_bigger_samples) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0907
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  - Wer: 0.1967
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  ## Model description
 
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  | Training Loss | Epoch | Step | Validation Loss | Wer |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 2.1766 | 1.0 | 625 | 0.0940 | 0.2060 |
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+ | 1.8382 | 2.0 | 1250 | 0.0916 | 0.1966 |
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+ | 1.4337 | 3.0 | 1875 | 0.0906 | 0.1905 |
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+ | 1.2601 | 4.0 | 2500 | 0.0898 | 0.1904 |
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+ | 1.1154 | 5.0 | 3125 | 0.0884 | 0.1886 |
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+ | 1.0993 | 6.0 | 3750 | 0.0875 | 0.1902 |
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+ | 0.9665 | 7.0 | 4375 | 0.0866 | 0.1936 |
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+ | 0.9165 | 8.0 | 5000 | 0.0866 | 0.1929 |
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+ | 0.8476 | 9.0 | 5625 | 0.0865 | 0.1926 |
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+ | 0.7916 | 10.0 | 6250 | 0.0865 | 0.1927 |
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  ### Framework versions
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