--- license: apache-2.0 base_model: facebook/wav2vec2-base tags: - audio-classification - generated_from_trainer datasets: - superb metrics: - accuracy model-index: - name: wav2vec2-base-ft-keyword-spotting results: - task: name: Audio Classification type: audio-classification dataset: name: superb type: superb config: ks split: validation args: ks metrics: - name: Accuracy type: accuracy value: 0.9829361576934392 --- # wav2vec2-base-ft-keyword-spotting This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the superb dataset. It achieves the following results on the evaluation set: - Loss: 0.0804 - Accuracy: 0.9829 ## 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: 3e-05 - train_batch_size: 32 - eval_batch_size: 32 - seed: 0 - gradient_accumulation_steps: 4 - total_train_batch_size: 128 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 5.0 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.5081 | 1.0 | 399 | 0.3587 | 0.9698 | | 0.2772 | 2.0 | 798 | 0.1273 | 0.9763 | | 0.1748 | 3.0 | 1197 | 0.0957 | 0.9796 | | 0.1407 | 4.0 | 1597 | 0.0804 | 0.9829 | | 0.1233 | 5.0 | 1995 | 0.0774 | 0.9825 | ### Framework versions - Transformers 4.34.0.dev0 - Pytorch 2.0.1+cu118 - Datasets 2.14.5 - Tokenizers 0.14.0