metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: swinv2-large-patch4-window12to16-192to256-22kto1k-ft-finetuned-eurosat-50
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: imagefolder
          type: imagefolder
          config: Augmented
          split: train
          args: Augmented
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8795454545454545

swinv2-large-patch4-window12to16-192to256-22kto1k-ft-finetuned-eurosat-50

This model is a fine-tuned version of microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 0.3293
Accuracy: 0.8795

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: 1e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.5
num_epochs: 6

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.8498	1.0	55	1.7348	0.3273
1.1886	2.0	110	1.0198	0.6102
0.8636	3.0	165	0.6859	0.7398
0.576	4.0	220	0.4357	0.8477
0.5875	5.0	275	0.4188	0.8386
0.4677	6.0	330	0.3293	0.8795

Framework versions

Transformers 4.30.2
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3