segformer-b01-finetuned-wrinkle

This model is a fine-tuned version of nvidia/mit-b1 on the face-wrinkles dataset. It achieves the following results on the evaluation set:

• eval_loss: 0.0002
• eval_mean_iou: 0.0
• eval_mean_accuracy: nan
• eval_overall_accuracy: nan
• eval_accuracy_unlabeled: nan
• eval_accuracy_wrinkle: nan
• eval_iou_unlabeled: 0.0
• eval_iou_wrinkle: 0.0
• eval_runtime: 13.0305
• eval_samples_per_second: 10.053
• eval_steps_per_second: 5.065
• epoch: 2.3978
• step: 880

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: 6e-05
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 5

Framework versions

• Transformers 4.46.2
• Pytorch 2.5.1+cu121
• Datasets 3.1.0
• Tokenizers 0.20.3