distil-ast-audioset / README.md
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metadata
license: bsd-3-clause
tags:
  - generated_from_trainer
metrics:
  - f1
  - accuracy
model-index:
  - name: distil-ast-audioset-2
    results: []

distil-ast-audioset-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: 0.3063
  • F1: 0.4876
  • Roc Auc: 0.7140
  • Accuracy: 0.0714
  • Map: 0.4743

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: 32
  • eval_batch_size: 32
  • seed: 0
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 10.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss F1 Roc Auc Accuracy Map
1.5521 1.0 153 0.7759 0.3929 0.6789 0.0209 0.3394
0.7088 2.0 306 0.5183 0.4480 0.7162 0.0349 0.4047
0.484 3.0 459 0.4342 0.4673 0.7241 0.0447 0.4348
0.369 4.0 612 0.3847 0.4777 0.7332 0.0504 0.4463
0.2943 5.0 765 0.3587 0.4838 0.7284 0.0572 0.4556
0.2446 6.0 918 0.3415 0.4875 0.7296 0.0608 0.4628
0.2099 7.0 1071 0.3273 0.4896 0.7246 0.0648 0.4682
0.186 8.0 1224 0.3140 0.4888 0.7171 0.0689 0.4711
0.1693 9.0 1377 0.3101 0.4887 0.7157 0.0703 0.4741
0.1582 10.0 1530 0.3063 0.4876 0.7140 0.0714 0.4743

Framework versions

  • Transformers 4.27.0.dev0
  • Pytorch 1.13.1+cu117
  • Datasets 2.10.0
  • Tokenizers 0.13.2