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--- |
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library_name: transformers |
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language: |
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- ur |
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license: apache-2.0 |
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base_model: GogetaBlueMUI/whisper-small-ur |
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tags: |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/common_voice_13_0 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Small Urdu V2 - Muhammad Abdullah |
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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: Common Voice 13.0 |
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type: mozilla-foundation/common_voice_13_0 |
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config: ur |
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split: test |
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args: 'config: ur, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 35.42311262376238 |
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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 Small Urdu V2 - Muhammad Abdullah |
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This model is a fine-tuned version of [GogetaBlueMUI/whisper-small-ur](https://huggingface.co/GogetaBlueMUI/whisper-small-ur) on the Common Voice 13.0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7436 |
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- Wer: 35.4231 |
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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 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: 1500 |
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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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| 0.068 | 1.9305 | 500 | 0.6670 | 37.1751 | |
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| 0.0182 | 3.8610 | 1000 | 0.7094 | 35.9684 | |
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| 0.0032 | 5.7915 | 1500 | 0.7436 | 35.4231 | |
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### Framework versions |
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- Transformers 4.47.0 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.21.0 |
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