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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_aug_0-2
    results: []

ast-finetuned-audioset-10-10-0.4593_ft_env_aug_0-2

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: 0.6899
  • Accuracy: 0.9643
  • Precision: 0.9694
  • Recall: 0.9643
  • F1: 0.9631

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-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_ratio: 0.1
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1
2.0165 1.0 28 1.6252 0.4643 0.5373 0.4643 0.4711
1.3702 2.0 56 1.0553 0.8571 0.8929 0.8571 0.8536
0.8861 3.0 84 0.6899 0.9643 0.9694 0.9643 0.9631
0.5655 4.0 112 0.4766 0.9643 0.9694 0.9643 0.9631
0.4232 5.0 140 0.3403 0.9643 0.9694 0.9643 0.9631
0.3148 6.0 168 0.2679 0.9643 0.9694 0.9643 0.9631
0.2335 7.0 196 0.2239 0.9643 0.9694 0.9643 0.9631
0.176 8.0 224 0.1979 0.9643 0.9694 0.9643 0.9631
0.1624 9.0 252 0.1824 0.9643 0.9694 0.9643 0.9631
0.1466 10.0 280 0.1781 0.9643 0.9694 0.9643 0.9631

Framework versions

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