--- license: apache-2.0 base_model: facebook/wav2vec2-base tags: - generated_from_trainer datasets: - marsyas/gtzan metrics: - accuracy model-index: - name: wav2vec2-base-finetuned-gtzan results: - task: name: Audio Classification type: audio-classification dataset: name: GTZAN type: marsyas/gtzan config: all split: train args: all metrics: - name: Accuracy type: accuracy value: 0.83 --- # wav2vec2-base-finetuned-gtzan This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the GTZAN dataset. It achieves the following results on the evaluation set: - Loss: 0.6713 - Accuracy: 0.83 ## 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: 10 - eval_batch_size: 10 - seed: 42 - 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 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 1.9059 | 1.0 | 90 | 1.7870 | 0.48 | | 1.4224 | 2.0 | 180 | 1.3290 | 0.67 | | 1.2667 | 3.0 | 270 | 1.2726 | 0.57 | | 0.791 | 4.0 | 360 | 1.0556 | 0.7 | | 0.6727 | 5.0 | 450 | 0.7369 | 0.8 | | 0.4685 | 6.0 | 540 | 0.6371 | 0.86 | | 0.5113 | 7.0 | 630 | 0.8083 | 0.79 | | 0.2758 | 8.0 | 720 | 0.5974 | 0.87 | | 0.1834 | 9.0 | 810 | 0.5047 | 0.88 | | 0.1746 | 10.0 | 900 | 0.6713 | 0.83 | ### Framework versions - Transformers 4.42.4 - Pytorch 2.3.1+cu121 - Datasets 2.21.0 - Tokenizers 0.19.1