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videomae-base-finetuned-ucf101-subset

This model is a fine-tuned version of MCG-NJU/videomae-base on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3585
  • Accuracy: 0.9226

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: 5e-05
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • training_steps: 3750

Training results

Training Loss Epoch Step Validation Loss Accuracy
2.0046 0.04 150 2.0806 0.3143
1.9549 1.04 300 1.4746 0.5429
0.6873 2.04 450 0.9489 0.6714
1.6042 3.04 600 0.6865 0.7571
0.2082 4.04 750 0.4017 0.8857
0.2805 5.04 900 0.9705 0.7714
0.0062 6.04 1050 0.4833 0.8571
0.2727 7.04 1200 0.8048 0.8714
0.1055 8.04 1350 0.0264 0.9857
0.234 9.04 1500 0.1460 0.9714
0.0015 10.04 1650 0.3039 0.9429
0.0012 11.04 1800 0.2351 0.9571
0.0009 12.04 1950 0.3080 0.9286
0.0009 13.04 2100 0.3477 0.9429
0.036 14.04 2250 0.2366 0.9571
0.0008 15.04 2400 0.4506 0.9
0.0037 16.04 2550 0.2327 0.9571
0.0007 17.04 2700 0.3480 0.9286
0.0007 18.04 2850 0.1762 0.9714
0.0006 19.04 3000 0.0991 0.9714
0.0006 20.04 3150 0.1551 0.9714
0.0006 21.04 3300 0.3023 0.9429
0.0006 22.04 3450 0.1543 0.9571
0.0006 23.04 3600 0.1025 0.9571
0.0006 24.04 3750 0.0876 0.9571

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.0.1+cu117
  • Datasets 2.14.4
  • Tokenizers 0.13.3
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