--- license: apache-2.0 base_model: YCHuang2112/distilhubert-finetuned-gtzan tags: - generated_from_trainer datasets: - marsyas/gtzan metrics: - accuracy model-index: - name: distilhubert-finetuned-gtzan-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: 0.88 --- # distilhubert-finetuned-gtzan-finetuned-gtzan This model is a fine-tuned version of [YCHuang2112/distilhubert-finetuned-gtzan](https://huggingface.co/YCHuang2112/distilhubert-finetuned-gtzan) on the GTZAN dataset. It achieves the following results on the evaluation set: - Loss: 0.9510 - Accuracy: 0.88 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.1926 | 1.0 | 113 | 1.0906 | 0.8 | | 0.0102 | 2.0 | 226 | 1.0165 | 0.81 | | 0.0035 | 3.0 | 339 | 1.0433 | 0.85 | | 0.0013 | 4.0 | 452 | 1.0259 | 0.87 | | 0.0011 | 5.0 | 565 | 0.9510 | 0.88 | ### Framework versions - Transformers 4.41.2 - Pytorch 2.1.2 - Datasets 2.19.2 - Tokenizers 0.19.1