--- language: - yue license: apache-2.0 tags: - hf-asr-leaderboard - generated_from_trainer datasets: - mozilla-foundation/common_voice_11 metrics: - wer model-index: - name: Whisper Base Yue results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 11.0 yue type: mozilla-foundation/common_voice_11 config: unclear split: None args: 'config: yue, split: train' metrics: - name: Wer type: wer value: 69.58637469586375 --- # Whisper Base Yue This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Common Voice 11.0 yue dataset. It achieves the following results on the evaluation set: - Loss: 0.3671 - Wer: 69.5864 ## 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: 2e-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: 200 - training_steps: 1000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.0998 | 2.78 | 500 | 0.3500 | 71.4517 | | 0.0085 | 5.56 | 1000 | 0.3671 | 69.5864 | ### Framework versions - Transformers 4.26.0.dev0 - Pytorch 1.13.0+cu116 - Datasets 2.7.1 - Tokenizers 0.13.2