Ast Finetuned Gtzan

--- 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: ast-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: 0.91 --- <!-- 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. --> # ast-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: 0.4152 - Accuracy: 0.91 ## 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 - gradient_accumulation_steps: 4 - total_train_batch_size: 32 - 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 - lr_scheduler_warmup_steps: 0.1 - num_epochs: 10 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.7814 | 1.0 | 29 | 0.5261 | 0.85 | | 0.3218 | 2.0 | 58 | 0.6317 | 0.75 | | 0.1996 | 3.0 | 87 | 0.4910 | 0.85 | | 0.0459 | 4.0 | 116 | 0.4152 | 0.91 | | 0.0124 | 5.0 | 145 | 0.3330 | 0.9 | | 0.0032 | 6.0 | 174 | 0.3495 | 0.9 | | 0.0023 | 7.0 | 203 | 0.4007 | 0.9 | | 0.0174 | 8.0 | 232 | 0.3172 | 0.89 | | 0.0015 | 9.0 | 261 | 0.3410 | 0.9 | | 0.0016 | 10.0 | 290 | 0.3508 | 0.91 | ### Framework versions - Transformers 5.5.3 - Pytorch 2.11.0+cu130 - Datasets 3.6.0 - Tokenizers 0.22.2

Source context: 3 downloads · 0 likes · Pipeline audio-classification · Library transformers · Repo kenshi777/ast-finetuned-gtzan