--- library_name: peft language: - it license: cc-by-nc-4.0 base_model: nyrahealth/CrisperWhisper tags: - generated_from_trainer datasets: - b-brave-clean metrics: - wer model-index: - name: Whisper-Crisper results: - task: type: automatic-speech-recognition name: Automatic Speech Recognition dataset: name: b-brave-clean type: b-brave-clean config: default split: test args: default metrics: - type: wer value: 155.63816604708796 name: Wer --- # Whisper-Crisper This model is a fine-tuned version of [nyrahealth/CrisperWhisper](https://huggingface.co/nyrahealth/CrisperWhisper) on the b-brave-clean dataset. It achieves the following results on the evaluation set: - Loss: 0.2971 - Wer: 155.6382 - Cer: 74.4218 - Lr: 0.0000 ## 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: 0.0003 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 8 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.5 - num_epochs: 8 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | Cer | Lr | |:-------------:|:------:|:----:|:---------------:|:---------:|:--------:|:------:| | 1.0227 | 1.0 | 335 | 0.8979 | 601.9827 | 363.8095 | 0.0001 | | 0.5552 | 2.0 | 670 | 0.5294 | 1520.4461 | 678.7302 | 0.0002 | | 0.4207 | 3.0 | 1005 | 0.4611 | 403.5936 | 219.1610 | 0.0002 | | 0.2025 | 4.0 | 1340 | 0.3812 | 346.8401 | 162.0408 | 0.0003 | | 0.1216 | 5.0 | 1675 | 0.3001 | 400.3717 | 203.6054 | 0.0002 | | 0.0478 | 6.0 | 2010 | 0.2932 | 198.6369 | 94.8299 | 0.0001 | | 0.0313 | 7.0 | 2345 | 0.3033 | 241.0161 | 115.3288 | 0.0001 | | 0.012 | 7.9776 | 2672 | 0.2971 | 155.6382 | 74.4218 | 0.0000 | ### Framework versions - PEFT 0.14.0 - Transformers 4.48.3 - Pytorch 2.2.0 - Datasets 3.2.0 - Tokenizers 0.21.0