--- license: apache-2.0 tags: - audio-classification - generated_from_trainer datasets: - common_language metrics: - accuracy model-index: - name: whisper-base-ft-common-language-id results: [] --- # whisper-base-ft-common-language-id This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the common_language dataset. It achieves the following results on the evaluation set: - Loss: 1.0725 - Accuracy: 0.7525 ## 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: 1e-05 - train_batch_size: 32 - eval_batch_size: 16 - seed: 0 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 10.0 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 2.5291 | 1.0 | 694 | 2.4787 | 0.4806 | | 1.5801 | 2.0 | 1388 | 1.6258 | 0.6260 | | 1.0144 | 3.0 | 2082 | 1.2886 | 0.6816 | | 0.7442 | 4.0 | 2776 | 1.0783 | 0.7237 | | 0.4802 | 5.0 | 3470 | 1.0582 | 0.7266 | | 0.3378 | 6.0 | 4164 | 1.0173 | 0.7417 | | 0.1941 | 7.0 | 4858 | 1.0054 | 0.7446 | | 0.1424 | 8.0 | 5552 | 1.0213 | 0.7508 | | 0.1242 | 9.0 | 6246 | 1.0567 | 0.7495 | | 0.1527 | 10.0 | 6940 | 1.0725 | 0.7525 | ### Framework versions - Transformers 4.27.0.dev0 - Pytorch 1.13.1 - Datasets 2.9.0 - Tokenizers 0.13.2