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metadata
license: bsd-3-clause
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: ast-finetuned-audioset-10-10-0.4593_ft_env_0-12
    results: []

ast-finetuned-audioset-10-10-0.4593_ft_env_0-12

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: 0.3804
  • Accuracy: 0.9643
  • Precision: 0.9702
  • Recall: 0.9643
  • F1: 0.9643

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: 1.5e-06
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 42
  • 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_steps: 56
  • num_epochs: 15

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1
2.0371 1.0 28 1.9267 0.1429 0.3214 0.1429 0.1482
1.7315 2.0 56 1.5823 0.3214 0.3667 0.3214 0.2973
1.3081 3.0 84 1.2250 0.75 0.8423 0.75 0.7499
0.9664 4.0 112 0.9526 0.8214 0.8616 0.8214 0.8078
0.6607 5.0 140 0.7525 0.8571 0.8795 0.8571 0.8520
0.5239 6.0 168 0.6080 0.8929 0.9152 0.8929 0.8866
0.453 7.0 196 0.5089 0.9286 0.9286 0.9286 0.9286
0.323 8.0 224 0.4353 0.9286 0.9286 0.9286 0.9286
0.296 9.0 252 0.3804 0.9643 0.9702 0.9643 0.9643
0.2167 10.0 280 0.3382 0.9643 0.9702 0.9643 0.9643
0.186 11.0 308 0.3157 0.9643 0.9702 0.9643 0.9643
0.1748 12.0 336 0.2931 0.9643 0.9702 0.9643 0.9643
0.1367 13.0 364 0.2781 0.9643 0.9702 0.9643 0.9643
0.1469 14.0 392 0.2705 0.9643 0.9702 0.9643 0.9643
0.1308 15.0 420 0.2679 0.9643 0.9702 0.9643 0.9643

Framework versions

  • Transformers 4.27.4
  • Pytorch 2.0.0
  • Datasets 2.10.1
  • Tokenizers 0.11.0