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End of training

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  1. README.md +87 -0
  2. generation_config.json +265 -0
  3. model.safetensors +1 -1
README.md ADDED
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+ ---
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+ language:
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+ - ara
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+ license: apache-2.0
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+ base_model: openai/whisper-small
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+ tags:
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+ - hf-asr-leaderboard
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+ - generated_from_trainer
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+ datasets:
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+ - AsemBadr/GP
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: Whisper Small for Quran Recognition
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+ results:
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+ - task:
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+ name: Automatic Speech Recognition
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+ type: automatic-speech-recognition
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+ dataset:
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+ name: Quran_Reciters
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+ type: AsemBadr/GP
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+ config: default
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+ split: test
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+ args: 'config: default, split: train'
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 3.1287605294825513
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+ ---
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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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+
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+ # Whisper Small for Quran Recognition
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+
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+ This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Quran_Reciters dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0179
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+ - Wer: 3.1288
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 1e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 500
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+ - training_steps: 4000
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Wer |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 0.0073 | 1.62 | 500 | 0.0249 | 5.0026 |
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+ | 0.0014 | 3.24 | 1000 | 0.0214 | 4.1086 |
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+ | 0.0008 | 4.85 | 1500 | 0.0221 | 3.9883 |
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+ | 0.0 | 6.47 | 2000 | 0.0180 | 2.9740 |
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+ | 0.0 | 8.09 | 2500 | 0.0177 | 3.0944 |
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+ | 0.0 | 9.71 | 3000 | 0.0178 | 3.0944 |
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+ | 0.0 | 11.33 | 3500 | 0.0179 | 3.1288 |
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+ | 0.0 | 12.94 | 4000 | 0.0179 | 3.1288 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.40.0.dev0
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+ - Pytorch 2.1.2
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+ - Datasets 2.17.1
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+ - Tokenizers 0.15.1
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