ViTuned_buildings / README.md
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metadata
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: ViTuned_buildings
    results: []

ViTuned_buildings

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

  • Loss: 0.0432
  • Accuracy: 0.9931

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: 0.0002
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 4
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.1985 0.33 100 1.1271 0.9726
0.4085 0.67 200 0.3959 0.9743
0.186 1.0 300 0.1963 0.9846
0.1066 1.34 400 0.2404 0.9417
0.1117 1.67 500 0.1423 0.9726
0.0923 2.01 600 0.1076 0.9794
0.0315 2.34 700 0.0656 0.9846
0.0263 2.68 800 0.0645 0.9880
0.0542 3.01 900 0.0458 0.9949
0.0203 3.34 1000 0.0444 0.9931
0.0189 3.68 1100 0.0432 0.9931

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.1.2
  • Datasets 2.1.0
  • Tokenizers 0.15.2