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mobilevit-trained-task3

This model is a fine-tuned version of apple/mobilevitv2-1.0-imagenet1k-256 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1371
  • Accuracy: 0.9670

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: 0.001
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • 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: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.6753 0.99 126 0.8382 0.7376
0.6882 2.0 253 0.6129 0.7874
0.4068 3.0 380 0.3532 0.8876
0.3587 4.0 507 0.4896 0.8622
0.3013 4.99 633 0.2656 0.9078
0.2777 6.0 760 0.1679 0.9472
0.2093 7.0 887 0.2264 0.9302
0.1866 8.0 1014 0.2245 0.9263
0.1896 8.99 1140 0.2252 0.9333
0.1059 10.0 1267 0.1544 0.9528
0.1072 11.0 1394 0.2232 0.9391
0.1121 12.0 1521 0.1723 0.9467
0.103 12.99 1647 0.1750 0.9530
0.071 14.0 1774 0.1713 0.9541
0.0276 15.0 1901 0.1384 0.9631
0.0279 16.0 2028 0.1575 0.9607
0.0396 16.99 2154 0.1579 0.9604
0.0129 18.0 2281 0.1389 0.9674
0.0031 19.0 2408 0.1315 0.9689
0.0074 19.88 2520 0.1371 0.9670

Framework versions

  • Transformers 4.37.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.17.1
  • Tokenizers 0.15.2
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