--- library_name: transformers 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: 0.86 --- # 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: 0.5653 - Accuracy: 0.86 ## 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: 8 - eval_batch_size: 8 - 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 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 1.9774 | 1.0 | 113 | 1.9927 | 0.28 | | 1.5184 | 2.0 | 226 | 1.4378 | 0.5 | | 1.3158 | 3.0 | 339 | 1.1390 | 0.72 | | 0.8236 | 4.0 | 452 | 1.0595 | 0.69 | | 0.7644 | 5.0 | 565 | 1.0361 | 0.7 | | 0.5783 | 6.0 | 678 | 0.6584 | 0.82 | | 0.4597 | 7.0 | 791 | 0.5901 | 0.87 | | 0.2232 | 8.0 | 904 | 0.5699 | 0.87 | | 0.1191 | 9.0 | 1017 | 0.5567 | 0.88 | | 0.0797 | 10.0 | 1130 | 0.5653 | 0.86 | ### Framework versions - Transformers 4.45.2 - Pytorch 2.4.0 - Datasets 3.0.1 - Tokenizers 0.20.1