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Pre-trained models and development set predictions

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@fschmid56 fschmid56 released this 23 Jun 08:59
· 6 commits to master since this release
v0.0.1
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Learn about vigilant mode.

PaSST models trained downstream on TAU Urban Acoustic Scenes 2022 Mobile, development dataset:

  • passt_253.pt : patchout_f=6, mixstyle_alpha=0.6, mixstyle_p=0.5; val. loss: 1.047
  • passt_254.pt : patchout_f=6, mixstyle_alpha=0.8, mixstyle_p=0.3; val. loss: 1.055
  • passt_255.pt : patchout_f=6, mixstyle_alpha=0.6, mixstyle_p=0.5; val. loss: 1.034
  • passt_256.pt : patchout_f=6, mixstyle_alpha=0.8, mixstyle_p=0.7; val. loss: 1.074

Predictions on reassembled 10-second files of a PaSST model:

  • preds_227.pt : patchout_f=8; val. loss: 0.655
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