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segformer-b1-GFB-exp – AI Model by luoyun75579 | AlphaNeural AI
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segformer-b1-GFB-exp
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transformers
safetensors
segformer
vision
image-segmentation
generated_from_trainer
nvidia/mit-b1
finetune
other
endpoints_compatible
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segformer-b1-GFB-exp
This model is a fine-tuned version of
nvidia/mit-b1
on the segments/GFB dataset. It achieves the following results on the evaluation set:
eval_loss: 0.3306
eval_mean_iou: 0.6108
eval_mean_accuracy: 0.7335
eval_overall_accuracy: 0.8871
eval_accuracy_unlabeled: 0.9407
eval_accuracy_GBM: 0.7830
eval_accuracy_Podo: 0.7113
eval_accuracy_Endo: 0.4989
eval_iou_unlabeled: 0.8871
eval_iou_GBM: 0.6348
eval_iou_Podo: 0.5239
eval_iou_Endo: 0.3975
eval_runtime: 16.627
eval_samples_per_second: 20.389
eval_steps_per_second: 1.323
epoch: 12.9412
step: 1100
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: 16
eval_batch_size: 16
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
lr_scheduler_warmup_steps: 250
num_epochs: 50
Framework versions
Transformers 4.57.1
Pytorch 2.9.1+cu130
Datasets 4.4.1
Tokenizers 0.22.1
