Gtzan Ast Classifier

--- library_name: transformers license: bsd-3-clause base_model: MIT/ast-finetuned-audioset-10-10-0.4593 tags: - generated_from_trainer datasets: - marsyas/gtzan metrics: - accuracy model-index: - name: MIT/ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan results: - task: name: Audio Classification type: audio-classification dataset: name: GTZAN type: marsyas/gtzan config: default split: train args: default metrics: - name: Accuracy type: accuracy value: 0.92 --- <!-- 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. --> # MIT/ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan This model is a fine-tuned version of [MIT/ast-finetuned-audioset-10-10-0.4593](https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593) on the GTZAN dataset. It achieves the following results on the evaluation set: - Loss: 0.2989 - Accuracy: 0.92 ## 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: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - num_epochs: 10 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.6403 | 1.0 | 113 | 0.4655 | 0.87 | | 0.2874 | 2.0 | 226 | 0.6336 | 0.82 | | 0.1274 | 3.0 | 339 | 0.4641 | 0.87 | | 0.0465 | 4.0 | 452 | 0.5623 | 0.83 | | 0.0285 | 5.0 | 565 | 0.3886 | 0.89 | | 0.0042 | 6.0 | 678 | 0.2969 | 0.92 | | 0.0006 | 7.0 | 791 | 0.3001 | 0.92 | | 0.0003 | 8.0 | 904 | 0.3014 | 0.92 | | 0.0003 | 9.0 | 1017 | 0.3009 | 0.92 | | 0.0022 | 10.0 | 1130 | 0.2989 | 0.92 | ### Framework versions - Transformers 4.57.3 - Pytorch 2.9.0+cu126 - Datasets 2.16.1 - Tokenizers 0.22.1

Source context: 5 downloads · 0 likes · Pipeline audio-classification · Library transformers · Repo explorer7/gtzan-ast-classifier