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deprem_satellite_semantic_xview2_large_2 – AI Model by SerdarHelli | AlphaNeural AI
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deprem_satellite_semantic_xview2_large_2
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segformer
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deprem_satellite_semantic_xview2_large_2
This model is a fine-tuned version of
nvidia/mit-b5
on an unknown dataset. It achieves the following results on the evaluation set:
eval_loss: 0.9892
eval_mean_iou: 0.3093
eval_mean_accuracy: 0.3576
eval_overall_accuracy: 0.9646
eval_accuracy_background: 0.9860
eval_accuracy_nodamage: 0.8022
eval_accuracy_minordamaged: 0.0
eval_accuracy_majordamaged: 0.0
eval_accuracy_destroyed: 0.0
eval_iou_background: 0.9677
eval_iou_nodamage: 0.5789
eval_iou_minordamaged: 0.0
eval_iou_majordamaged: 0.0
eval_iou_destroyed: 0.0
eval_runtime: 200.8095
eval_samples_per_second: 4.646
eval_steps_per_second: 4.646
epoch: 19.3
step: 27000
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: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 2
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 25
Framework versions
Transformers 4.27.0.dev0
Pytorch 1.13.1+cu116
Datasets 2.9.0
Tokenizers 0.13.2
