--- library_name: transformers license: apache-2.0 base_model: ntu-spml/distilhubert tags: - generated_from_trainer metrics: - accuracy model-index: - name: distilhubert-finetuned-gtzan results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # distilhubert-finetuned-gtzan This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.1809 - Accuracy: 0.8231 ## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 10 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 1.0783 | 1.0 | 874 | 1.1569 | 0.6234 | | 0.4485 | 2.0 | 1748 | 0.8199 | 0.7499 | | 0.3201 | 3.0 | 2622 | 0.7982 | 0.7705 | | 0.3439 | 4.0 | 3496 | 0.8584 | 0.8025 | | 0.2061 | 5.0 | 4370 | 0.9085 | 0.8065 | | 0.0801 | 6.0 | 5244 | 0.9950 | 0.8134 | | 0.0178 | 7.0 | 6118 | 1.0729 | 0.8168 | | 0.0002 | 8.0 | 6992 | 1.1714 | 0.8180 | | 0.0001 | 9.0 | 7866 | 1.1886 | 0.8226 | | 0.0001 | 10.0 | 8740 | 1.1809 | 0.8231 | ### Framework versions - Transformers 4.46.2 - Pytorch 2.5.1+cu121 - Datasets 3.1.0 - Tokenizers 0.20.3