--- 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_mix-241029-v2 results: [] --- # whisper-large-v2-ft-cv16-1_mix-241029-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: 0.2544 ## 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 | |:-------------:|:-----:|:----:|:---------------:| | 2.0497 | 1.0 | 444 | 0.1964 | | 0.19 | 2.0 | 888 | 0.1885 | | 0.133 | 3.0 | 1332 | 0.1957 | | 0.0925 | 4.0 | 1776 | 0.2096 | | 0.0689 | 5.0 | 2220 | 0.2213 | | 0.0533 | 6.0 | 2664 | 0.2282 | | 0.0422 | 7.0 | 3108 | 0.2373 | | 0.0347 | 8.0 | 3552 | 0.2432 | | 0.0296 | 9.0 | 3996 | 0.2518 | | 0.0263 | 10.0 | 4440 | 0.2544 | ### Framework versions - PEFT 0.13.0 - Transformers 4.45.1 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.0