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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 - YA |
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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 - YA |
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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: 0.0033 |
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- Wer: 0.0497 |
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- Cer: 0.0200 |
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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: 2 |
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- total_train_batch_size: 16 |
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- optimizer: Use 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: 25 |
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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 | Cer | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:| |
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| 0.0024 | 1.0 | 320 | 0.0034 | 0.0440 | 0.0180 | |
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| 0.0014 | 2.0 | 640 | 0.0049 | 0.0653 | 0.0257 | |
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| 0.0013 | 3.0 | 960 | 0.0057 | 0.0766 | 0.0283 | |
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| 0.0007 | 4.0 | 1280 | 0.0057 | 0.0681 | 0.0290 | |
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| 0.0004 | 5.0 | 1600 | 0.0057 | 0.0617 | 0.0253 | |
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| 0.0002 | 6.0 | 1920 | 0.0060 | 0.0662 | 0.0244 | |
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| 0.0002 | 7.0 | 2240 | 0.0068 | 0.0624 | 0.0237 | |
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| 0.0003 | 8.0 | 2560 | 0.0061 | 0.0652 | 0.0259 | |
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| 0.0003 | 9.0 | 2880 | 0.0067 | 0.0648 | 0.0252 | |
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| 0.0004 | 10.0 | 3200 | 0.0062 | 0.0670 | 0.0259 | |
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| 0.0002 | 11.0 | 3520 | 0.0061 | 0.0610 | 0.0230 | |
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| 0.0001 | 12.0 | 3840 | 0.0064 | 0.0581 | 0.0217 | |
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| 0.0001 | 13.0 | 4160 | 0.0061 | 0.0576 | 0.0217 | |
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| 0.0 | 14.0 | 4480 | 0.0062 | 0.0594 | 0.0235 | |
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| 0.0 | 15.0 | 4800 | 0.0066 | 0.0630 | 0.0251 | |
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| 0.0 | 16.0 | 5120 | 0.0069 | 0.0581 | 0.0240 | |
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| 0.0 | 17.0 | 5440 | 0.0070 | 0.0579 | 0.0228 | |
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| 0.0 | 18.0 | 5760 | 0.0071 | 0.0586 | 0.0232 | |
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| 0.0 | 19.0 | 6080 | 0.0072 | 0.0590 | 0.0239 | |
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| 0.0 | 20.0 | 6400 | 0.0072 | 0.0576 | 0.0234 | |
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| 0.0 | 21.0 | 6720 | 0.0073 | 0.0574 | 0.0239 | |
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| 0.0 | 22.0 | 7040 | 0.0073 | 0.0577 | 0.0240 | |
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| 0.0 | 23.0 | 7360 | 0.0074 | 0.0577 | 0.0240 | |
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| 0.0 | 24.0 | 7680 | 0.0076 | 0.0613 | 0.0246 | |
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| 0.0 | 25.0 | 8000 | 0.0074 | 0.0581 | 0.0244 | |
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### Framework versions |
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- Transformers 4.46.3 |
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- Pytorch 2.4.0 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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