Edit model card

swin-tiny-patch4-window7-224-finetuned-eurosat

This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6838
  • Accuracy: 0.7968

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: 15

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.5891 0.9966 218 1.3833 0.5723
1.2997 1.9977 437 1.0831 0.6700
1.1166 2.9989 656 0.9937 0.6958
1.0464 4.0 875 0.9180 0.7231
0.982 4.9966 1093 0.8399 0.7432
0.9472 5.9977 1312 0.8127 0.7536
0.8751 6.9989 1531 0.7852 0.7639
0.9107 8.0 1750 0.7644 0.7713
0.8464 8.9966 1968 0.7322 0.7830
0.8398 9.9977 2187 0.7243 0.7798
0.7534 10.9989 2406 0.7088 0.7845
0.7051 12.0 2625 0.6982 0.7935
0.7359 12.9966 2843 0.6985 0.7916
0.7641 13.9977 3062 0.6838 0.7968
0.7372 14.9486 3270 0.6781 0.7968

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.1+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1
Downloads last month
38
Safetensors
Model size
27.6M params
Tensor type
I64
·
F32
·
Inference API
Drag image file here or click to browse from your device
This model can be loaded on Inference API (serverless).

Finetuned from

Evaluation results