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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-large |
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tags: |
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- generated_from_trainer |
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datasets: |
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- Mohsen21/WHISPERLARGEUAE |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Large fine tuned |
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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 Large fine tuned |
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This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the 1620 RAW dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1902 |
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- Wer: 12.3332 |
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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: 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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- training_steps: 750 |
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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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| 0.0375 | 2.4691 | 200 | 0.1497 | 13.3916 | |
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| 0.0174 | 4.9383 | 400 | 0.1739 | 12.7934 | |
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| 0.0114 | 7.4074 | 600 | 0.1902 | 12.3332 | |
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### Framework versions |
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- Transformers 4.48.1 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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