| | --- |
| | metrics: |
| | - accuracy |
| | pipeline_tag: audio-classification |
| | tags: |
| | - music |
| | --- |
| | This model is finetuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) for music genre classification. |
| | # This model was finetuned to distinguish between 18 music genres including: |
| | - Blues |
| | - Classical music |
| | - Country music |
| | - Drum & Bass |
| | - Dubstep |
| | - Folk |
| | - Future Bass |
| | - Hardstyle |
| | - House |
| | - Jazz |
| | - Latin music |
| | - Metal |
| | - Pop |
| | - R&B, Soul |
| | - Rap |
| | - Reagge |
| | - Rock |
| | - Trap |
| |
|
| | # Training hyperparameters |
| | The following hyperparameters were used during training: |
| | - metric_for_best_model = accuracy |
| | - learning_rate = 5e-5 |
| | - seed = 42 |
| | - per_device_train_batch_size = 4 |
| | - per_device_eval_batch_size = 4 |
| | - gradient_accumulation_steps = 1 |
| | - warmup_ratio = 0.1 |
| | - fp16 = True |
| | - adam_epsilon = 1e-08 |
| | - adam_beta1 = 0.9 |
| | - adam_beta2 = 0.999 |
