--- language: - ru license: apache-2.0 base_model: openai/whisper-small tags: - generated_from_trainer datasets: - mozilla-foundation/common_voice_16_0 metrics: - wer model-index: - name: Whisper Base Ru results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 16.0 type: mozilla-foundation/common_voice_16_0 config: ru split: None args: 'config: ru, split: test' metrics: - name: Wer type: wer value: 131.35769718547476 --- # Whisper Base Ru This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 16.0 dataset. It achieves the following results on the evaluation set: - Loss: 0.2080 - Wer: 131.3577 ## 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: 16 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - training_steps: 4000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.2013 | 0.61 | 1000 | 0.2301 | 130.4397 | | 0.0753 | 1.21 | 2000 | 0.2159 | 131.7603 | | 0.0902 | 1.82 | 3000 | 0.2046 | 129.7846 | | 0.0394 | 2.43 | 4000 | 0.2080 | 131.3577 | ### Framework versions - Transformers 4.37.2 - Pytorch 2.2.2 - Datasets 2.18.0 - Tokenizers 0.15.1