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--- |
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library_name: transformers |
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language: |
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- ru |
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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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- hf-asr-leaderboard |
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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 ru - slowlydoor |
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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: ru |
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split: None |
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args: 'config: ru, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 16.67692593581956 |
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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 ru - slowlydoor |
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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: 0.1989 |
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- Wer: 16.6769 |
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- Cer: 4.3640 |
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- Ser: 59.1591 |
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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: 8 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.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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- num_epochs: 1 |
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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 | Cer | Ser | |
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|:-------------:|:------:|:----:|:---------------:|:-------:|:------:|:-------:| |
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| 0.2176 | 0.1516 | 500 | 0.2575 | 21.0009 | 5.4512 | 69.0581 | |
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| 0.2146 | 0.3032 | 1000 | 0.2395 | 19.7826 | 5.2221 | 66.5785 | |
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| 0.1817 | 0.4548 | 1500 | 0.2264 | 18.5724 | 4.7800 | 64.4320 | |
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| 0.1862 | 0.6064 | 2000 | 0.2140 | 18.2088 | 4.7904 | 62.3542 | |
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| 0.1618 | 0.7580 | 2500 | 0.2049 | 17.0765 | 4.3953 | 60.4234 | |
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| 0.1597 | 0.9096 | 3000 | 0.1989 | 16.6769 | 4.3640 | 59.1591 | |
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### Framework versions |
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- Transformers 4.52.3 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.6.0 |
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- Tokenizers 0.21.1 |
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