--- base_model: openai/whisper-large-v2 library_name: peft license: apache-2.0 tags: - generated_from_trainer model-index: - name: whisper-large-v2-ft-my_dataset_car100_owner12_snr0x8_mp3-241019-v2 results: [] --- # whisper-large-v2-ft-my_dataset_car100_owner12_snr0x8_mp3-241019-v2 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: 0.0141 ## 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 | |:-------------:|:-----:|:----:|:---------------:| | 7.7366 | 1.0 | 38 | 4.1452 | | 2.8856 | 2.0 | 76 | 1.8884 | | 0.7584 | 3.0 | 114 | 0.1070 | | 0.0722 | 4.0 | 152 | 0.0496 | | 0.0322 | 5.0 | 190 | 0.0292 | | 0.0162 | 6.0 | 228 | 0.0217 | | 0.0099 | 7.0 | 266 | 0.0178 | | 0.0063 | 8.0 | 304 | 0.0170 | | 0.0043 | 9.0 | 342 | 0.0146 | | 0.0031 | 10.0 | 380 | 0.0141 | ### Framework versions - PEFT 0.13.0 - Transformers 4.45.1 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.0