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vit-base-patch32-384-finetuned-eurosat – AI Model by keithanpai | AlphaNeural AI
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keithanpai
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vit-base-patch32-384-finetuned-eurosat
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transformers
pytorch
tensorboard
vit
image-classification
generated_from_trainer
imagefolder
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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vit-base-patch32-384-finetuned-eurosat
This model is a fine-tuned version of
google/vit-base-patch32-384
on the imagefolder dataset. It achieves the following results on the evaluation set:
Loss: 0.4381
Accuracy: 0.8423
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: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.607
0.99
70
0.5609
0.8014
0.5047
1.99
140
0.4634
0.8373
0.4089
2.99
210
0.4381
0.8423
Framework versions
Transformers 4.21.0
Pytorch 1.12.0+cu113
Datasets 2.4.0
Tokenizers 0.12.1
