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metadata
license: other
base_model: nvidia/mit-b0
tags:
  - generated_from_trainer
model-index:
  - name: segformer-b0-scene-parse-150
    results: []

segformer-b0-scene-parse-150

This model is a fine-tuned version of nvidia/mit-b0 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: -34.0382
  • Mean Iou: 0.0
  • Mean Accuracy: nan
  • Overall Accuracy: nan
  • Per Category Iou: [0.0]
  • Per Category Accuracy: [nan]

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Mean Iou Mean Accuracy Overall Accuracy Per Category Iou Per Category Accuracy
-14.0066 0.95 20 -4.7161 0.0 nan nan [0.0] [nan]
-22.6107 1.9 40 -10.5378 0.0 nan nan [0.0] [nan]
-19.9201 2.86 60 -21.2021 0.0 nan nan [0.0] [nan]
-28.3712 3.81 80 -21.2437 0.0 nan nan [0.0] [nan]
-37.3469 4.76 100 -28.5338 0.0 nan nan [0.0] [nan]
-37.3102 5.71 120 -31.3866 0.0 nan nan [0.0] [nan]
-39.3847 6.67 140 -36.0143 0.0 nan nan [0.0] [nan]
-39.0931 7.62 160 -31.5379 0.0 nan nan [0.0] [nan]
-43.0727 8.57 180 -33.0026 0.0 nan nan [0.0] [nan]
-47.8338 9.52 200 -34.0382 0.0 nan nan [0.0] [nan]

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2