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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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- nadsoft |
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- generated_from_trainer |
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datasets: |
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- nadsoft/arabic-98 |
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metrics: |
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- wer |
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model-index: |
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- name: ./hamsa-v0.6Q |
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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: nadsoft/arabic-98 |
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type: nadsoft/arabic-98 |
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metrics: |
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- name: Wer |
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type: wer |
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value: 23.412419116812348 |
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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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# ./hamsa-v0.6Q |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the nadsoft/arabic-98 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2781 |
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- Wer: 23.4124 |
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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: 32 |
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- eval_batch_size: 16 |
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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: 300 |
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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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| 0.9225 | 0.33 | 100 | 0.8743 | 24.5136 | |
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| 0.2721 | 0.67 | 200 | 0.2782 | 24.1367 | |
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| 0.2474 | 1.0 | 300 | 0.2781 | 23.4124 | |
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### Framework versions |
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- Transformers 4.37.0.dev0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.2.dev0 |
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- Tokenizers 0.15.0 |
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