--- 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__car200-e3n4-A50E100_owner12-copy2x-241217-v1 results: [] --- # whisper-large-v2-ft-cv16-1__car200-e3n4-A50E100_owner12-copy2x-241217-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: 0.1109 ## 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: 64 - eval_batch_size: 64 - 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 | |:-------------:|:-----:|:----:|:---------------:| | 3.7195 | 1.0 | 149 | 1.4206 | | 0.3691 | 2.0 | 298 | 0.1129 | | 0.1193 | 3.0 | 447 | 0.1035 | | 0.0939 | 4.0 | 596 | 0.0994 | | 0.0769 | 5.0 | 745 | 0.1003 | | 0.0634 | 6.0 | 894 | 0.1031 | | 0.053 | 7.0 | 1043 | 0.1054 | | 0.0455 | 8.0 | 1192 | 0.1077 | | 0.0402 | 9.0 | 1341 | 0.1098 | | 0.0365 | 10.0 | 1490 | 0.1109 | ### Framework versions - PEFT 0.13.0 - Transformers 4.45.1 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.0