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metadata
license: apache-2.0
base_model: microsoft/swinv2-tiny-patch4-window8-256
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: swinv2-tiny-patch4-window8-256-finetuned-eurosat
    results: []

swinv2-tiny-patch4-window8-256-finetuned-eurosat

This model is a fine-tuned version of microsoft/swinv2-tiny-patch4-window8-256 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6760
  • Accuracy: 0.8170

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: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.2519 0.9955 167 0.7302 0.8017
0.2407 1.9970 335 0.7095 0.7836
0.3423 2.9985 503 0.7016 0.7884
0.4687 4.0 671 0.6480 0.7969
0.4789 4.9955 838 0.5132 0.8160
0.4417 5.9970 1006 0.5321 0.8065
0.435 6.9985 1174 0.5770 0.8093
0.4106 8.0 1342 0.5650 0.8189
0.4216 8.9955 1509 0.5535 0.8132
0.3786 9.9970 1677 0.5745 0.8179
0.3536 10.9985 1845 0.6322 0.8046
0.4842 12.0 2013 0.7200 0.8103
0.3095 12.9955 2180 0.6996 0.8112
0.2603 13.9970 2348 0.7004 0.8065
0.2838 14.9985 2516 0.6331 0.8227
0.3449 16.0 2684 0.6788 0.8122
0.253 16.9955 2851 0.6940 0.8103
0.2647 17.9970 3019 0.6770 0.8132
0.2991 18.9985 3187 0.6647 0.8189
0.26 19.9106 3340 0.6760 0.8170

Framework versions

  • Transformers 4.40.2
  • Pytorch 2.2.2
  • Datasets 2.19.1
  • Tokenizers 0.19.1