--- license: apache-2.0 library_name: peft tags: - generated_from_trainer base_model: openai/whisper-large-v2 model-index: - name: int8-whisper-large-v2-asr-gn-15-all-a100 results: [] --- # int8-whisper-large-v2-asr-gn-15-all-a100 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: 0.1441 ## 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: 64 - eval_batch_size: 8 - 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 | |:-------------:|:-----:|:----:|:---------------:| | 0.5271 | 1.0 | 292 | 0.3598 | | 0.3254 | 2.0 | 584 | 0.2609 | | 0.2019 | 3.0 | 876 | 0.2030 | | 0.1125 | 4.0 | 1168 | 0.1562 | | 0.0543 | 5.0 | 1460 | 0.1441 | ### Framework versions - PEFT 0.7.1 - Transformers 4.36.2 - Pytorch 2.1.0+cu118 - Datasets 2.16.1 - Tokenizers 0.15.0