readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - imagefolder
  metrics:
  - accuracy
  model-index:
  - name: swin-tiny-patch4-window7-224-seg-swin-amal-finetuned-eurosat
    results:
    - task:
        name: Image Classification
        type: image-classification
      dataset:
        name: imagefolder
        type: imagefolder
        args: default
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.4527928818586258
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # swin-tiny-patch4-window7-224-seg-swin-amal-finetuned-eurosat
  
  This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
  It achieves the following results on the evaluation set:
  - Loss: 5.6236
  - Accuracy: 0.4528
  
  ## 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: 200
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
  | 2.1452        | 1.0   | 268   | 2.2034          | 0.2247   |
  | 0.9905        | 2.0   | 536   | 0.9729          | 0.7126   |
  | 0.5262        | 3.0   | 804   | 0.5282          | 0.8314   |
  | 0.36          | 4.0   | 1072  | 0.5618          | 0.8337   |
  | 0.305         | 5.0   | 1340  | 0.9210          | 0.6535   |
  | 0.2669        | 6.0   | 1608  | 1.1776          | 0.6317   |
  | 0.2663        | 7.0   | 1876  | 1.2129          | 0.6290   |
  | 0.2207        | 8.0   | 2144  | 2.2039          | 0.4068   |
  | 0.2178        | 9.0   | 2412  | 1.9747          | 0.4740   |
  | 0.1822        | 10.0  | 2680  | 1.4390          | 0.5526   |
  | 0.1691        | 11.0  | 2948  | 2.1020          | 0.3814   |
  | 0.1731        | 12.0  | 3216  | 2.0999          | 0.4251   |
  | 0.1705        | 13.0  | 3484  | 2.4643          | 0.3700   |
  | 0.1286        | 14.0  | 3752  | 2.7902          | 0.4345   |
  | 0.1511        | 15.0  | 4020  | 2.5151          | 0.4165   |
  | 0.1403        | 16.0  | 4288  | 4.4323          | 0.3099   |
  | 0.1562        | 17.0  | 4556  | 2.0293          | 0.5096   |
  | 0.1233        | 18.0  | 4824  | 2.5863          | 0.4236   |
  | 0.1293        | 19.0  | 5092  | 2.6533          | 0.4506   |
  | 0.1268        | 20.0  | 5360  | 2.1429          | 0.4998   |
  | 0.1464        | 21.0  | 5628  | 2.3014          | 0.5470   |
  | 0.1507        | 22.0  | 5896  | 2.3857          | 0.4911   |
  | 0.1285        | 23.0  | 6164  | 1.4228          | 0.6406   |
  | 0.1364        | 24.0  | 6432  | 3.6147          | 0.4842   |
  | 0.1209        | 25.0  | 6700  | 2.4210          | 0.4896   |
  | 0.1321        | 26.0  | 6968  | 2.7809          | 0.5344   |
  | 0.0944        | 27.0  | 7236  | 3.5598          | 0.4226   |
  | 0.1013        | 28.0  | 7504  | 4.0793          | 0.3905   |
  | 0.1243        | 29.0  | 7772  | 4.5733          | 0.3443   |
  | 0.0962        | 30.0  | 8040  | 2.9494          | 0.4199   |
  | 0.0974        | 31.0  | 8308  | 3.1012          | 0.4496   |
  | 0.113         | 32.0  | 8576  | 3.9522          | 0.3764   |
  | 0.1067        | 33.0  | 8844  | 1.9792          | 0.6053   |
  | 0.095         | 34.0  | 9112  | 2.8795          | 0.5302   |
  | 0.1015        | 35.0  | 9380  | 5.9943          | 0.2941   |
  | 0.0912        | 36.0  | 9648  | 2.9536          | 0.5242   |
  | 0.1193        | 37.0  | 9916  | 3.5187          | 0.4226   |
  | 0.0906        | 38.0  | 10184 | 3.0049          | 0.5114   |
  | 0.1109        | 39.0  | 10452 | 2.6823          | 0.5675   |
  | 0.0903        | 40.0  | 10720 | 4.7151          | 0.3109   |
  | 0.0846        | 41.0  | 10988 | 3.1118          | 0.3880   |
  | 0.0986        | 42.0  | 11256 | 3.9827          | 0.4792   |
  | 0.1244        | 43.0  | 11524 | 4.7544          | 0.2860   |
  | 0.1039        | 44.0  | 11792 | 4.4297          | 0.3178   |
  | 0.077         | 45.0  | 12060 | 5.8973          | 0.3524   |
  | 0.0718        | 46.0  | 12328 | 6.0338          | 0.3033   |
  | 0.0838        | 47.0  | 12596 | 6.3524          | 0.3507   |
  | 0.0935        | 48.0  | 12864 | 3.8675          | 0.4194   |
  | 0.0922        | 49.0  | 13132 | 4.7731          | 0.3129   |
  | 0.0903        | 50.0  | 13400 | 3.5435          | 0.4115   |
  | 0.0927        | 51.0  | 13668 | 4.7606          | 0.4234   |
  | 0.0757        | 52.0  | 13936 | 3.4110          | 0.4436   |
  | 0.0738        | 53.0  | 14204 | 6.3143          | 0.3648   |
  | 0.0