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update model card README.md
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README.md
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---
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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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- common_voice_11_0
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metrics:
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- wer
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model-index:
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- name: openai/whisper-medium
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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_11_0
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type: common_voice_11_0
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config: ru
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split: test
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args: ru
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metrics:
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- name: Wer
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type: wer
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value: 7.562437929892964
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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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# openai/whisper-medium
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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_11_0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2253
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- Wer: 7.5624
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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: 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: 10000
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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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| 0.1578 | 0.1 | 1000 | 0.1662 | 8.8290 |
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| 0.045 | 1.08 | 2000 | 0.1748 | 8.9148 |
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| 0.0176 | 2.06 | 3000 | 0.1889 | 8.7848 |
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| 0.0104 | 3.04 | 4000 | 0.1922 | 8.4354 |
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| 0.0051 | 4.02 | 5000 | 0.2034 | 8.1865 |
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| 0.0047 | 4.12 | 6000 | 0.2012 | 8.0455 |
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| 0.0018 | 5.1 | 7000 | 0.2117 | 7.6237 |
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| 0.0004 | 6.08 | 8000 | 0.2177 | 7.6078 |
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| 0.0003 | 7.06 | 9000 | 0.2244 | 7.6262 |
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| 0.0002 | 8.04 | 10000 | 0.2253 | 7.5624 |
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### Framework versions
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- Transformers 4.28.0.dev0
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- Pytorch 2.0.0+cu117
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- Datasets 2.11.1.dev0
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- Tokenizers 0.13.2
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