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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: 0.0928 |
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- Wer: 0.2043 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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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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| 1.2944 | 1.0 | 313 | 0.0886 | 0.1967 | |
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| 1.2819 | 2.0 | 626 | 0.0902 | 0.1923 | |
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| 1.2752 | 3.0 | 939 | 0.0902 | 0.1986 | |
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| 1.1425 | 4.0 | 1252 | 0.0915 | 0.1989 | |
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| 1.0812 | 5.0 | 1565 | 0.0900 | 0.1914 | |
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| 0.9708 | 6.0 | 1878 | 0.0900 | 0.1916 | |
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| 0.9029 | 7.0 | 2191 | 0.0891 | 0.1985 | |
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| 0.8248 | 8.0 | 2504 | 0.0896 | 0.1916 | |
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| 0.7778 | 9.0 | 2817 | 0.0897 | 0.1941 | |
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| 0.7485 | 10.0 | 3130 | 0.0890 | 0.1944 | |
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| 0.7219 | 11.0 | 3443 | 0.0883 | 0.1961 | |
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| 0.6584 | 12.0 | 3756 | 0.0889 | 0.1948 | |
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| 0.6516 | 13.0 | 4069 | 0.0883 | 0.1951 | |
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| 0.6233 | 14.0 | 4382 | 0.0882 | 0.1942 | |
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| 0.6017 | 14.9536 | 4680 | 0.0883 | 0.1957 | |
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### Framework versions |
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- Transformers 4.51.1 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.5.0 |
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- Tokenizers 0.21.0 |
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