--- language: - ko license: apache-2.0 library_name: peft tags: - generated_from_trainer base_model: openai/whisper-large-v2 datasets: - customd_ataset model-index: - name: Whisper large-v2 Korean - ML_project_custom_data_5epoch_with500 results: [] --- # Whisper large-v2 Korean - ML_project_custom_data_5epoch_with500 This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the customd_ataset dataset. It achieves the following results on the evaluation set: - Loss: 0.7892 - Cer: 80.2045 ## 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: 0.001 - train_batch_size: 4 - eval_batch_size: 2 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 50 - num_epochs: 5 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Cer | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.114 | 1.0 | 113 | 0.8207 | 86.1943 | | 0.1328 | 2.0 | 226 | 0.8307 | 96.2016 | | 0.0678 | 3.0 | 339 | 0.8054 | 96.7860 | | 0.0246 | 4.0 | 452 | 0.7812 | 78.8897 | | 0.0155 | 5.0 | 565 | 0.7892 | 80.2045 | ### Framework versions - PEFT 0.11.2.dev0 - Transformers 4.41.2 - Pytorch 2.3.0+cu121 - Datasets 2.19.2 - Tokenizers 0.19.1