--- base_model: openai/whisper-large-v2 library_name: peft license: apache-2.0 tags: - generated_from_trainer model-index: - name: whisper-large-v2-ft-cv16-1__car50-all-format_copy2x_voiceless-241204-v1 results: [] --- # whisper-large-v2-ft-cv16-1__car50-all-format_copy2x_voiceless-241204-v1 This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.0868 ## 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-05 - train_batch_size: 128 - eval_batch_size: 128 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.2 - num_epochs: 10 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 4.7803 | 1.0 | 93 | 2.1664 | | 1.0542 | 2.0 | 186 | 0.1003 | | 0.1156 | 3.0 | 279 | 0.0844 | | 0.0917 | 4.0 | 372 | 0.0803 | | 0.0776 | 5.0 | 465 | 0.0811 | | 0.0668 | 6.0 | 558 | 0.0822 | | 0.0592 | 7.0 | 651 | 0.0834 | | 0.0529 | 8.0 | 744 | 0.0845 | | 0.0482 | 9.0 | 837 | 0.0858 | | 0.0451 | 10.0 | 930 | 0.0868 | ### Framework versions - PEFT 0.13.0 - Transformers 4.45.1 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.0