--- base_model: openai/whisper-large-v2 datasets: - common_voice_16_1 library_name: peft license: apache-2.0 tags: - generated_from_trainer model-index: - name: whisper-large-v2-ft-common_voice_16_1-241026-v1 results: [] --- # whisper-large-v2-ft-common_voice_16_1-241026-v1 This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the common_voice_16_1 dataset. It achieves the following results on the evaluation set: - Loss: 3.0642 ## 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 | |:-------------:|:-----:|:----:|:---------------:| | 6.5065 | 1.0 | 1 | 5.8581 | | 6.9782 | 2.0 | 2 | 5.3557 | | 5.8666 | 3.0 | 3 | 4.5343 | | 4.6367 | 4.0 | 4 | 3.9887 | | 4.0018 | 5.0 | 5 | 3.6462 | | 3.6299 | 6.0 | 6 | 3.4259 | | 3.5384 | 7.0 | 7 | 3.2591 | | 3.4859 | 8.0 | 8 | 3.1552 | | 3.3513 | 9.0 | 9 | 3.0924 | | 3.3222 | 10.0 | 10 | 3.0642 | ### Framework versions - PEFT 0.13.0 - Transformers 4.45.1 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.0