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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: openai/whisper-medium |
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tags: |
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- generated_from_trainer |
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datasets: |
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- arabic_speech_corpus |
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model-index: |
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- name: Whisper Medium Arabic |
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results: [] |
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metrics: |
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- wer |
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library_name: transformers |
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pipeline_tag: automatic-speech-recognition |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/abdelrahmanabosteet/Graduation_project/runs/uszjncge) |
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# Whisper Medium Arabic |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Arabic Speech Corpus dataset. |
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It achieves the following results on the evaluation set: |
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- eval_loss: 0.0794 |
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- eval_wer: 5.4226 |
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- eval_runtime: 200.1714 |
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- eval_samples_per_second: 0.5 |
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- eval_steps_per_second: 0.5 |
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- epoch: 5.7143 |
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- step: 250 |
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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: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 16 |
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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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- training_steps: 400 |
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### Framework versions |
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- Transformers 4.41.0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
