--- language: - zh license: apache-2.0 library_name: peft tags: - hf-asr-leaderboard - generated_from_trainer datasets: - mozilla-foundation/common_voice_16_0 base_model: openai/whisper-large-v3 model-index: - name: Whisper Large v3 zh-TW - Chinese results: [] --- # Whisper Large v3 zh-TW - Chinese This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the Common Voice 16.0 dataset. It achieves the following results on the evaluation set: - Loss: 0.1537 ## 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: 0.001 - train_batch_size: 8 - 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: 50 - num_epochs: 3 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 0.198 | 1.0 | 1507 | 0.1869 | | 0.0817 | 2.0 | 3014 | 0.1605 | | 0.021 | 3.0 | 4521 | 0.1537 | ### Framework versions - PEFT 0.7.1 - Transformers 4.36.2 - Pytorch 2.1.0.post301 - Datasets 2.16.1 - Tokenizers 0.15.0