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---
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language:
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- fa
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license: apache-2.0
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base_model: openai/whisper-small
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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-17-0
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metrics:
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- wer
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model-index:
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- name: Whisper Small Persian - Persian ASR
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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-17-0
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type: mozilla-foundation-common-voice-17-0
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config: default
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split: test[:20%]
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args: 'config: Persian, split: train[:20%]+validation[:20%]'
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metrics:
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- name: Wer
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type: wer
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value: 43.69646680942184
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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 Persian - Persian ASR
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the common-voice-17-0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6543
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- Wer: 43.6965
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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: 4
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- eval_batch_size: 4
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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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- num_epochs: 5
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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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| 0.3355 | 1.0 | 1973 | 0.5819 | 50.9101 |
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| 0.176 | 2.0 | 3946 | 0.5479 | 49.8796 |
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| 0.0767 | 3.0 | 5919 | 0.5610 | 45.3292 |
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| 0.0262 | 4.0 | 7892 | 0.6115 | 44.0645 |
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| 0.0116 | 5.0 | 9865 | 0.6543 | 43.6965 |
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### Framework versions
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- Transformers 4.44.0
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- Pytorch 2.4.0+cu121
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- Datasets 2.21.0
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- Tokenizers 0.19.1
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