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 on the GTZAN dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5086
  • Accuracy: 0.88

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: 2
  • eval_batch_size: 2
  • seed: 14
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 8
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.5982 1.0 112 0.5195 0.83
0.3962 2.0 225 0.5597 0.81
0.3143 3.0 337 0.7567 0.83
0.0548 4.0 450 0.5270 0.86
0.0119 5.0 562 0.5813 0.88
0.2503 6.0 675 0.7523 0.86
0.0008 7.0 787 0.6239 0.85
0.0003 8.0 900 0.4949 0.9
0.0001 9.0 1012 0.5706 0.88
0.0003 10.0 1125 0.4898 0.92
0.0001 11.0 1237 0.5281 0.89
0.0001 12.0 1350 0.5197 0.88
0.0002 13.0 1462 0.5036 0.9
0.0 14.0 1575 0.5362 0.9
0.0 15.0 1687 0.5065 0.89
0.0 16.0 1800 0.5011 0.9
0.0 17.0 1912 0.5025 0.88
0.0 18.0 2025 0.5027 0.88
0.0 19.0 2137 0.5074 0.88
0.0 19.91 2240 0.5086 0.88

Framework versions

  • Transformers 4.31.0.dev0
  • Pytorch 2.0.1+cu118
  • Datasets 2.13.1
  • Tokenizers 0.13.3
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Dataset used to train sumet/ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan

Evaluation results