--- 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__my_dataset_car50_owner12_notmix_copy8x_mp3-241114-v1 results: [] --- # whisper-large-v2-ft-cv16-1__my_dataset_car50_owner12_notmix_copy8x_mp3-241114-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: 0.1018 ## 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 | |:-------------:|:-----:|:----:|:---------------:| | 4.3903 | 1.0 | 75 | 2.2025 | | 1.1765 | 2.0 | 150 | 0.1276 | | 0.1351 | 3.0 | 225 | 0.1008 | | 0.1071 | 4.0 | 300 | 0.0972 | | 0.0925 | 5.0 | 375 | 0.0966 | | 0.0813 | 6.0 | 450 | 0.0974 | | 0.0722 | 7.0 | 525 | 0.0997 | | 0.066 | 8.0 | 600 | 0.0998 | | 0.0608 | 9.0 | 675 | 0.1019 | | 0.0583 | 10.0 | 750 | 0.1018 | ### Framework versions - PEFT 0.13.0 - Transformers 4.45.1 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.0