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SeizureClassifier_AST_B_43275870

This model is a fine-tuned version of MIT/ast-finetuned-audioset-10-10-0.4593 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0163
  • Accuracy: 0.9975

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: 3e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 15

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.2929 0.99 44 0.1468 0.9455
0.0774 1.99 88 0.1206 0.9629
0.0424 2.98 132 0.0863 0.9728
0.0359 4.0 177 0.0519 0.9802
0.0526 4.99 221 0.0088 0.9975
0.0028 5.99 265 0.0116 0.9926
0.0051 6.98 309 0.0214 0.9926
0.0004 8.0 354 0.0246 0.9975
0.0002 8.99 398 0.0233 0.9975
0.0 9.99 442 0.0205 0.9975
0.0 10.98 486 0.0183 0.9975
0.0 12.0 531 0.0171 0.9975
0.0 12.99 575 0.0166 0.9975
0.0 13.99 619 0.0164 0.9975
0.0 14.92 660 0.0163 0.9975

Framework versions

  • Transformers 4.32.1
  • Pytorch 2.1.2
  • Datasets 2.16.1
  • Tokenizers 0.13.3
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