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update model card README.md
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README.md
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---
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language:
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- tr
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license: apache-2.0
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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 Medium Tr - Can K V2
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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: tr
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split: test
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args: 'config: tr, split: test'
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metrics:
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- name: Wer
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type: wer
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value: 67.02546197734821
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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 Medium Tr - Can K V2
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) 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: 0.1892
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- Wer: 67.0255
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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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- gradient_accumulation_steps: 4
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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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- lr_scheduler_warmup_steps: 500
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- training_steps: 8000
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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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| 0.146 | 0.34 | 1000 | 0.2164 | 105.0754 |
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| 0.1562 | 0.69 | 2000 | 0.2115 | 43.5238 |
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| 0.0803 | 1.03 | 3000 | 0.1979 | 42.8919 |
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| 0.0668 | 1.38 | 4000 | 0.1944 | 37.3397 |
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| 0.0693 | 1.72 | 5000 | 0.1869 | 36.3910 |
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| 0.0305 | 2.07 | 6000 | 0.1898 | 49.8254 |
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| 0.0272 | 2.41 | 7000 | 0.1908 | 60.8005 |
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| 0.0274 | 2.76 | 8000 | 0.1892 | 67.0255 |
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### Framework versions
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- Transformers 4.28.1
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- Pytorch 2.4.0+cu121
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- Datasets 2.20.0
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- Tokenizers 0.13.3
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