code135/scene_segmentation

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code135/scene_segmentation

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

• —Train Loss: nan
• —Validation Loss: nan
• —Validation Mean Iou: 0.0183
• —Validation Mean Accuracy: 0.1667
• —Validation Overall Accuracy: 0.1607
• —Validation Accuracy Ciel: 1.0
• —Validation Accuracy Vegetation: 0.0
• —Validation Accuracy Batiment peu vitre (<50%): 0.0
• —Validation Accuracy Batiment tres vitre (>50%): 0.0
• —Validation Accuracy Couvert: 0.0
• —Validation Accuracy Autre: 0.0
• —Validation Iou Ciel: 0.1098
• —Validation Iou Vegetation: 0.0
• —Validation Iou Batiment peu vitre (<50%): 0.0
• —Validation Iou Batiment tres vitre (>50%): 0.0
• —Validation Iou Couvert: 0.0
• —Validation Iou Autre: 0.0
• —Epoch: 2

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:

• —optimizer: {'name': 'AdamWeightDecay', 'learningrate': {'module': 'keras.optimizers.schedules', 'classname': 'PolynomialDecay', 'config': {'initiallearningrate': 6e-05, 'decaysteps': 120, 'endlearningrate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registeredname': None}, 'decay': 0.0, 'beta1': 0.9, 'beta2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weightdecayrate': 0.01}
• —training_precision: float32

Training results

Framework versions

• —Transformers 4.46.2
• —TensorFlow 2.17.1
• —Datasets 3.1.0
• —Tokenizers 0.20.3