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

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

• Loss: 0.3648
• Accuracy: 0.9017

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: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	0.91	5	0.5982	0.7492
0.645	1.91	10	0.4862	0.7593
0.645	2.91	15	0.4191	0.7966
0.465	3.91	20	0.3803	0.8780
0.465	4.91	25	0.3648	0.9017

Framework versions

• Transformers 4.17.0
• Pytorch 1.11.0+cpu
• Datasets 2.2.0
• Tokenizers 0.12.1