segformer_outputs_withweight

This model is a fine-tuned version of nvidia/mit-b0 on the AIeng1danah/cwld-segformer dataset. It achieves the following results on the evaluation set:

• Loss: 0.1424
• Mean Iou: 0.8050
• Mean Accuracy: 0.8811
• Overall Accuracy: 0.9416
• Accuracy Background: 0.9685
• Accuracy Waste: 0.7936
• Iou Background: 0.9334
• Iou Waste: 0.6767

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: 0.001
• train_batch_size: 16
• eval_batch_size: 16
• seed: 1337
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: polynomial
• num_epochs: 200.0

Training results

Framework versions

• Transformers 4.53.0.dev0
• Pytorch 2.3.0+cu118
• Datasets 3.6.0
• Tokenizers 0.21.1