segformer-finetuned-paddyV1

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bhaskarSingha/segformer-finetuned-paddyV1

This model is a fine-tuned version of nvidia/segformer-b0-finetuned-ade-512-512 on an unknown dataset. It achieves the following results on the evaluation set:

• Train Loss: nan
• Validation Loss: nan
• Validation Mean Iou: 0.0004
• Validation Mean Accuracy: 0.5
• Validation Overall Accuracy: 0.1499
• Validation Accuracy Healthy: 1.0
• Validation Accuracy Brownspot: 0.0
• Validation Accuracy Leafblast: nan
• Validation Iou Healthy: 0.0009
• Validation Iou Brownspot: 0.0
• Validation Iou Leafblast: nan
• 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': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'CosineDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 1000, 'alpha': 0.0, 'name': 'CosineDecay', 'warmup_target': 5e-05, 'warmup_steps': 100}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
• training_precision: float32

Training results

Framework versions

• Transformers 4.40.2
• TensorFlow 2.15.0
• Datasets 2.15.0
• Tokenizers 0.19.1