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:

• eval_loss: 0.2695
• eval_accuracy: 0.9022
• eval_runtime: 195.5267
• eval_samples_per_second: 21.486
• eval_steps_per_second: 0.675
• epoch: 51.76
• step: 10196

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

Framework versions

• Transformers 4.20.1
• Pytorch 1.12.1+cu102
• Datasets 2.3.2
• Tokenizers 0.12.1