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segformer_cracks_v2

This model is a fine-tuned version of nvidia/mit-b3 on the None dataset. It achieves the following results on the evaluation set:

• eval_loss: 0.0537
• eval_mean_iou: 0.7604
• eval_mean_accuracy: 0.8281
• eval_overall_accuracy: 0.9788
• eval_per_category_iou: [0.9782807410260149, 0.5424475354128461]
• eval_per_category_accuracy: [0.9911386477455301, 0.6649739140722758]
• eval_runtime: 1877.8784
• eval_samples_per_second: 1.459
• eval_steps_per_second: 0.365
• epoch: 1.0
• step: 1370

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: 8
• eval_batch_size: 4
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10

Framework versions

• Transformers 4.33.1
• Pytorch 2.0.1
• Datasets 2.14.5
• Tokenizers 0.13.3