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metadata
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: deit-tiny-patch16-224-RESISC45_01
    results: []

deit-tiny-patch16-224-RESISC45_01

This model is a fine-tuned version of facebook/deit-tiny-patch16-224 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3266
  • Accuracy: 0.912
  • Precision: 0.9184
  • Recall: 0.912
  • F1: 0.9127

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: 0.0001
  • train_batch_size: 512
  • eval_batch_size: 512
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1
2.1588 1.0 37 1.4843 0.716 0.7429 0.716 0.7079
1.1043 2.0 74 0.8240 0.825 0.8391 0.825 0.8245
0.801 3.0 111 0.5870 0.866 0.8733 0.866 0.8660
0.6546 4.0 148 0.4760 0.885 0.8916 0.885 0.8852
0.5632 5.0 185 0.4202 0.896 0.9038 0.896 0.8963
0.5004 6.0 222 0.3792 0.895 0.9046 0.895 0.8953
0.4392 7.0 259 0.3483 0.906 0.9126 0.906 0.9067
0.4358 8.0 296 0.3436 0.907 0.9150 0.907 0.9084
0.4208 9.0 333 0.3298 0.908 0.9135 0.908 0.9086
0.4148 10.0 370 0.3266 0.912 0.9184 0.912 0.9127

Framework versions

  • Transformers 4.44.0
  • Pytorch 2.4.0
  • Datasets 2.21.0
  • Tokenizers 0.19.1