beit-base-patch16-224-pt22k-finetuned-eurosat

This model is a fine-tuned version of microsoft/beit-base-patch16-224-pt22k on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9338
  • Accuracy: 0.6667

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: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 3 1.3657 0.3095
No log 2.0 6 1.1966 0.4286
No log 3.0 9 1.1076 0.4524
1.2696 4.0 12 1.0717 0.5714
1.2696 5.0 15 0.9948 0.5238
1.2696 6.0 18 1.0701 0.5
1.0945 7.0 21 0.9920 0.5
1.0945 8.0 24 0.9338 0.6667
1.0945 9.0 27 0.9605 0.5714
0.9538 10.0 30 0.9285 0.6190
0.9538 11.0 33 0.9113 0.5714
0.9538 12.0 36 0.8414 0.6190
0.9538 13.0 39 0.9422 0.5476
0.8646 14.0 42 0.8165 0.6429
0.8646 15.0 45 0.9582 0.5238
0.8646 16.0 48 0.8548 0.6190
0.8082 17.0 51 0.8568 0.6190
0.8082 18.0 54 0.8792 0.5476
0.8082 19.0 57 0.8819 0.5476
0.7731 20.0 60 0.8454 0.5714

Framework versions

  • Transformers 4.30.0
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.13.3
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