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videomae-base-finetuned-good-gestureUnitV12

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:

  • Accuracy: 0.8966
  • Loss: 0.2937
  • Accuracy Gunit: 0.8333
  • Accuracy Nothing: 0.9556

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: 1e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • 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: 160

Training results

Training Loss Epoch Step Accuracy Validation Loss Accuracy Gunit Accuracy Nothing
0.8549 0.1062 17 0.5714 0.6774 0.68 0.4839
0.6437 1.1062 34 0.4643 0.7254 1.0 0.0323
0.6226 2.1063 51 0.6071 0.6527 0.96 0.3226
0.5883 3.1063 68 0.5714 0.6389 1.0 0.2258
0.5136 4.1063 85 0.6964 0.5330 0.84 0.5806
0.4284 5.1063 102 0.8214 0.4506 0.84 0.8065
0.3474 6.1063 119 0.8214 0.3974 0.76 0.8710
0.2859 7.1063 136 0.8214 0.3822 0.64 0.9677
0.3059 8.1062 153 0.8393 0.3763 0.68 0.9677
0.2582 9.0437 160 0.8393 0.3738 0.68 0.9677

Framework versions

  • Transformers 4.41.1
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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Finetuned from