Edit model card

vit-base-patch16-224-in21k-finetuned-eurosat

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0581
  • Accuracy: 0.9904

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: 1
  • eval_batch_size: 1
  • seed: 42
  • distributed_type: IPU
  • gradient_accumulation_steps: 32
  • total_train_batch_size: 32
  • total_eval_batch_size: 4
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 3
  • training precision: Mixed Precision

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.0804 1.0 759 0.1383 0.9741
0.0385 2.0 1518 0.0756 0.9859
0.1211 3.0 2277 0.0581 0.9904

Framework versions

  • Transformers 4.20.1
  • Pytorch 1.10.0+cpu
  • Datasets 2.7.1
  • Tokenizers 0.12.1
Downloads last month
4
Inference API
Unable to determine this model’s pipeline type. Check the docs .