deit_flyswot / README.md
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metadata
tags:
  - generated_from_trainer
datasets:
  - image_folder
metrics:
  - f1
model-index:
  - name: deit_flyswot
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: image_folder
          type: image_folder
          args: default
        metrics:
          - name: F1
            type: f1
            value: 0.990761405263678

deit_flyswot

This model was trained from scratch on the image_folder dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0755
  • F1: 0.9908

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: 32
  • eval_batch_size: 32
  • seed: 666
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 30
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss F1
No log 1.0 52 0.5710 0.8095
No log 2.0 104 0.2814 0.9380
No log 3.0 156 0.1719 0.9555
No log 4.0 208 0.1410 0.9692
No log 5.0 260 0.1457 0.9680
No log 6.0 312 0.1084 0.9747
No log 7.0 364 0.0892 0.9736
No log 8.0 416 0.0962 0.9831
No log 9.0 468 0.0819 0.9796
0.2034 10.0 520 0.0916 0.9778
0.2034 11.0 572 0.0793 0.9827
0.2034 12.0 624 0.0818 0.9894
0.2034 13.0 676 0.0852 0.9807
0.2034 14.0 728 0.0938 0.9778
0.2034 15.0 780 0.0814 0.9876
0.2034 16.0 832 0.0702 0.9892
0.2034 17.0 884 0.0801 0.9892
0.2034 18.0 936 0.0806 0.9892
0.2034 19.0 988 0.0769 0.9926
0.0115 20.0 1040 0.0800 0.9926
0.0115 21.0 1092 0.0794 0.9926
0.0115 22.0 1144 0.0762 0.9846
0.0115 23.0 1196 0.0789 0.9830
0.0115 24.0 1248 0.0794 0.9829
0.0115 25.0 1300 0.0770 0.9908
0.0115 26.0 1352 0.0791 0.9829
0.0115 27.0 1404 0.0813 0.9892
0.0115 28.0 1456 0.0816 0.9908
0.0058 29.0 1508 0.0774 0.9908
0.0058 30.0 1560 0.0755 0.9908

Framework versions

  • Transformers 4.17.0
  • Pytorch 1.10.0+cu111
  • Datasets 2.0.0
  • Tokenizers 0.11.6