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violation-classification-bantai-vit-v100ep

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

  • Loss: 0.2557
  • Accuracy: 0.9157

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: 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: 100

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.2811 1.0 101 0.2855 0.9027
0.2382 2.0 202 0.2763 0.9085
0.2361 3.0 303 0.2605 0.9109
0.196 4.0 404 0.2652 0.9110
0.1395 5.0 505 0.2648 0.9134
0.155 6.0 606 0.2656 0.9152
0.1422 7.0 707 0.2607 0.9141
0.1511 8.0 808 0.2557 0.9157
0.1938 9.0 909 0.2679 0.9049
0.2094 10.0 1010 0.2392 0.9137
0.1835 11.0 1111 0.2400 0.9156

Framework versions

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