--- base_model: m3hrdadfi/wav2vec2-base-100k-gtzan-music-genres tags: - generated_from_trainer datasets: - marsyas/gtzan metrics: - accuracy model-index: - name: wav2vec2-base-100k-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: 0.96 --- # wav2vec2-base-100k-finetuned-gtzan This model is a fine-tuned version of [m3hrdadfi/wav2vec2-base-100k-gtzan-music-genres](https://huggingface.co/m3hrdadfi/wav2vec2-base-100k-gtzan-music-genres) on the GTZAN dataset. It achieves the following results on the evaluation set: - Loss: 0.8208 - Accuracy: 0.96 ## 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: 5 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 1.9319 | 1.0 | 113 | 1.8502 | 0.78 | | 1.5211 | 2.0 | 226 | 1.4238 | 0.86 | | 1.1818 | 3.0 | 339 | 1.1062 | 0.92 | | 0.8895 | 4.0 | 452 | 0.8764 | 0.95 | | 0.8228 | 5.0 | 565 | 0.8208 | 0.96 | ### Framework versions - Transformers 4.44.0 - Pytorch 2.4.0 - Datasets 2.21.0 - Tokenizers 0.19.1