segformerSAAD_26Aug_new1

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segformerSAAD_26Aug_new1

This model is a fine-tuned version of nvidia/mit-b0 on the saad7489/SixGUNNew dataset. It achieves the following results on the evaluation set:

• eval_loss: 0.2892
• eval_mean_iou: 0.7470
• eval_mean_accuracy: 0.8404
• eval_overall_accuracy: 0.9883
• eval_accuracy_BKG: 0.9937
• eval_accuracy_Knife: nan
• eval_accuracy_Gun: 0.6872
• eval_iou_BKG: 0.9882
• eval_iou_Knife: nan
• eval_iou_Gun: 0.5059
• eval_runtime: 3.6938
• eval_samples_per_second: 3.79
• eval_steps_per_second: 0.271
• epoch: 4.0
• step: 20

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: 5e-05
• train_batch_size: 30
• eval_batch_size: 30
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 50

Framework versions

• Transformers 4.42.4
• Pytorch 2.4.0+cu121
• Datasets 2.21.0
• Tokenizers 0.19.1