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bigearthnet-vit – AI Model by Ganymede981 | AlphaNeural AI
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Ganymede981
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bigearthnet-vit
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peft
safetensors
adapter
lora
transformers
google/vit-base-patch16-224
apache-2.0
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bigearthnet-vit
This model is a fine-tuned version of
google/vit-base-patch16-224
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.0968
F1 Micro: 0.6503
F1 Macro: 0.2662
Map: 0.3291
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: 0.0001
train_batch_size: 512
eval_batch_size: 512
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine_with_restarts
lr_scheduler_warmup_steps: 500
num_epochs: 2
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
F1 Macro
F1 Micro
Validation Loss
Map
0.1646
0.9488
500
0.2670
0.6567
0.0970
0.3339
0.1245
1.8975
1000
0.0971
0.6492
0.2668
0.3284
0.1245
2.0
1054
0.0968
0.6503
0.2662
0.3291
Framework versions
PEFT 0.19.1
Transformers 5.8.1
Pytorch 2.10.0+cu128
Datasets 4.8.5
Tokenizers 0.22.2
