vit-base-patch16-224-finetuned-eurosat – AI Model by brainer | AlphaNeural AI

You can deploy this model and start earning money today!

brainer/
vit-base-patch16-224-finetuned-eurosat

like

0

image-classification

generated_from_trainer

google/vit-base-patch16-224

autotrain_compatible

endpoints_compatible

Views

No views yet

vit-base-patch16-224-finetuned-eurosat

This model is a fine-tuned version of google/vit-base-patch16-224 on the None dataset. It achieves the following results on the evaluation set:

Loss: inf
Accuracy: 0.0224

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: 4e-05
train_batch_size: 96
eval_batch_size: 96
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 384
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
18403482038360886413349920928956416.0000	1.0	258	inf	0.0224
18462639726606223815285376672595968.0000	2.0	517	inf	0.0224
18309578839444917002657010957680640.0000	3.0	775	inf	0.0224
18496480055520128970480019132383232.0000	4.0	1034	inf	0.0224
18428848915293890075301730177777664.0000	4.99	1290	inf	0.0224

Framework versions

Transformers 4.36.0
Pytorch 2.0.0
Datasets 2.16.1
Tokenizers 0.15.0