--- language: - zh license: apache-2.0 tags: - whisper - generated_from_trainer datasets: - '-' model-index: - name: whisper-base-zh-20230718-1 - au2a results: [] --- # whisper-base-zh-20230718-1 - au2a This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the some hakka audio dataset. It achieves the following results on the evaluation set: - Loss: 0.4142 - Cer: 84.7926 ## 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: 5e-06 - train_batch_size: 64 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 128 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - training_steps: 10000 ### Training results | Training Loss | Epoch | Step | Validation Loss | Cer | |:-------------:|:-----:|:-----:|:---------------:|:--------:| | 0.0499 | 2.59 | 1000 | 0.3377 | 153.9019 | | 0.0035 | 5.17 | 2000 | 0.3506 | 138.4528 | | 0.0015 | 7.76 | 3000 | 0.3651 | 128.2541 | | 0.001 | 10.35 | 4000 | 0.3754 | 105.1522 | | 0.0005 | 12.94 | 5000 | 0.3841 | 90.0846 | | 0.0004 | 15.52 | 6000 | 0.3925 | 92.5134 | | 0.0002 | 18.11 | 7000 | 0.4011 | 86.3035 | | 0.0002 | 20.7 | 8000 | 0.4070 | 80.0219 | | 0.0001 | 23.29 | 9000 | 0.4118 | 82.5451 | | 0.0001 | 25.87 | 10000 | 0.4142 | 84.7926 | ### Framework versions - Transformers 4.30.2 - Pytorch 2.0.1+cu117 - Datasets 2.13.1 - Tokenizers 0.13.3