--- license: apache-2.0 tags: - music - genre - classification datasets: - marsyas/gtzan metrics: - accuracy model-index: - name: distilhubert-finetuned-gtzan_accuracy_93 results: [] language: - en --- # distilhubert-finetuned-gtzan_accuracy_93 ### This model is a fine-tuned version of [yuval6967/distilhubert-finetuned-gtzan](https://huggingface.co/yuval6967/distilhubert-finetuned-gtzan) on the GTZAN dataset. It achieves the following results on the evaluation set: - Loss: 0.5121 - __Accuracy: 0.93__ ## Model description - Fine-tuned model to demonstrate > 87% accuracy for the [Huggingface Audio course](https://huggingface.co/learn/audio-course/chapter0/introduction) ## Intended uses & limitations - Model is built to identify the genre of music based on a ~30 sec clip ## Training and evaluation data More information needed ## Training procedure - test_size = 0.20 was used for the split ### 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.0316 | 1.0 | 100 | 0.4338 | 0.895 | | 0.0031 | 2.0 | 200 | 0.7039 | 0.86 | | 0.0069 | 3.0 | 300 | 0.4526 | 0.925 | | 0.1799 | 4.0 | 400 | 0.7071 | 0.88 | | 0.1783 | 5.0 | 500 | 0.5923 | 0.92 | | 0.0011 | 6.0 | 600 | 0.5498 | 0.92 | | 0.0005 | 7.0 | 700 | 0.4927 | 0.925 | | 0.0005 | 8.0 | 800 | 0.6172 | 0.915 | | 0.0004 | 9.0 | 900 | 0.4988 | 0.925 | | 0.0004 | 10.0 | 1000 | 0.5121 | 0.93 | ### Framework versions - Transformers 4.30.2 - Pytorch 2.0.1+cu118 - Datasets 2.13.1 - Tokenizers 0.13.3