| --- |
| library_name: transformers |
| language: |
| - ru |
| license: apache-2.0 |
| base_model: openai/whisper-small |
| tags: |
| - hf-asr-leaderboard |
| - generated_from_trainer |
| datasets: |
| - mozilla-foundation/common_voice_17_0 |
| metrics: |
| - wer |
| model-index: |
| - name: Whisper Small ru - slowlydoor |
| results: |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: Common Voice 17.0 |
| type: mozilla-foundation/common_voice_17_0 |
| config: ru |
| split: None |
| args: 'config: ru, split: test' |
| metrics: |
| - name: Wer |
| type: wer |
| value: 16.67692593581956 |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # Whisper Small ru - slowlydoor |
|
|
| This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 17.0 dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.1989 |
| - Wer: 16.6769 |
| - Cer: 4.3640 |
| - Ser: 59.1591 |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 1e-05 |
| - train_batch_size: 8 |
| - eval_batch_size: 4 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 1 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Wer | Cer | Ser | |
| |:-------------:|:------:|:----:|:---------------:|:-------:|:------:|:-------:| |
| | 0.2176 | 0.1516 | 500 | 0.2575 | 21.0009 | 5.4512 | 69.0581 | |
| | 0.2146 | 0.3032 | 1000 | 0.2395 | 19.7826 | 5.2221 | 66.5785 | |
| | 0.1817 | 0.4548 | 1500 | 0.2264 | 18.5724 | 4.7800 | 64.4320 | |
| | 0.1862 | 0.6064 | 2000 | 0.2140 | 18.2088 | 4.7904 | 62.3542 | |
| | 0.1618 | 0.7580 | 2500 | 0.2049 | 17.0765 | 4.3953 | 60.4234 | |
| | 0.1597 | 0.9096 | 3000 | 0.1989 | 16.6769 | 4.3640 | 59.1591 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.52.3 |
| - Pytorch 2.6.0+cu124 |
| - Datasets 3.6.0 |
| - Tokenizers 0.21.1 |
|
|
