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--- |
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base_model: openai/whisper-small |
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datasets: |
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- fleurs |
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language: |
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- ru |
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license: apache-2.0 |
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metrics: |
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- wer |
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tags: |
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- hf-asr-leaderboard |
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- generated_from_trainer |
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model-index: |
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- name: Whisper Small ru - Chee Li |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: Google Fleurs |
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type: fleurs |
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config: ru_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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- type: wer |
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value: 50.354088722608225 |
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name: Wer |
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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 - Chee Li |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co./openai/whisper-small) on the Google Fleurs dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2500 |
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- Wer: 50.3541 |
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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: 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: 4000 |
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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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| 0.0049 | 5.4645 | 1000 | 0.2170 | 29.2090 | |
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| 0.0013 | 10.9290 | 2000 | 0.2340 | 43.3993 | |
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| 0.0006 | 16.3934 | 3000 | 0.2457 | 49.9800 | |
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| 0.0004 | 21.8579 | 4000 | 0.2500 | 50.3541 | |
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### Framework versions |
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- Transformers 4.44.0 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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