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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - image_folder
metrics:
  - accuracy
model-index:
  - name: violation-classification-bantai-vit-v100ep
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: image_folder
          type: image_folder
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9157343919162757

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