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ViT_face

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the face dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6941

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-05
  • train_batch_size: 128
  • eval_batch_size: 128
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 30

Training results

Training Loss Epoch Step Validation Loss
No log 1.0 10 1.0691
No log 2.0 20 1.0378
No log 3.0 30 0.9958
No log 4.0 40 0.9437
No log 5.0 50 0.8915
No log 6.0 60 0.8396
No log 7.0 70 0.7950
No log 8.0 80 0.7602
No log 9.0 90 0.7246
No log 10.0 100 0.7009
No log 11.0 110 0.6882
No log 12.0 120 0.6700
No log 13.0 130 0.6629
No log 14.0 140 0.6646
No log 15.0 150 0.6558
No log 16.0 160 0.6679
No log 17.0 170 0.6637
No log 18.0 180 0.6689
No log 19.0 190 0.6690
No log 20.0 200 0.6744
No log 21.0 210 0.6787
No log 22.0 220 0.6823
No log 23.0 230 0.6832
No log 24.0 240 0.6866
No log 25.0 250 0.6883
No log 26.0 260 0.6912
No log 27.0 270 0.6923
No log 28.0 280 0.6935
No log 29.0 290 0.6939
No log 30.0 300 0.6941

Framework versions

  • Transformers 4.42.4
  • Pytorch 2.4.0+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1
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