87 lines
2.3 KiB
Markdown
87 lines
2.3 KiB
Markdown
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---
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language:
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- ar
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license: apache-2.0
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base_model: tarteel-ai/whisper-base-ar-quran
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tags:
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- generated_from_trainer
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datasets:
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- zolfa
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metrics:
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- wer
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model-index:
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- name: Zolfa-raghadomar
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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: Zolfa Dataset
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type: zolfa
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args: 'config: ar, split: test'
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metrics:
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- name: Wer
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type: wer
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value: 5.263157894736842
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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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# Zolfa-raghadomar
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This model is a fine-tuned version of [tarteel-ai/whisper-base-ar-quran](https://huggingface.co/tarteel-ai/whisper-base-ar-quran) on the Zolfa Dataset dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0157
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- Wer: 5.2632
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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: 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: 5
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- training_steps: 1000
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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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| 0.0155 | 2.8571 | 100 | 0.0156 | 5.2632 |
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| 0.0037 | 5.7143 | 200 | 0.0199 | 5.2632 |
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| 0.0011 | 8.5714 | 300 | 0.0175 | 5.2632 |
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| 0.0006 | 11.4286 | 400 | 0.0123 | 5.2632 |
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| 0.0003 | 14.2857 | 500 | 0.0187 | 5.2632 |
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| 0.0001 | 17.1429 | 600 | 0.0126 | 5.2632 |
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| 0.0001 | 20.0 | 700 | 0.0159 | 5.2632 |
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| 0.0002 | 22.8571 | 800 | 0.0137 | 5.2632 |
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| 0.0001 | 25.7143 | 900 | 0.0149 | 5.2632 |
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| 0.0001 | 28.5714 | 1000 | 0.0157 | 5.2632 |
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### Framework versions
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- Transformers 4.41.2
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- Pytorch 2.3.0+cu121
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- Datasets 2.19.2
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- Tokenizers 0.19.1
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