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--- |
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license: other |
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base_model: nvidia/segformer-b0-finetuned-ade-512-512 |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: bhaskarSingha/segformer-finetuned-paddyV1 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information Keras had access to. You should |
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probably proofread and complete it, then remove this comment. --> |
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# bhaskarSingha/segformer-finetuned-paddyV1 |
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This model is a fine-tuned version of [nvidia/segformer-b0-finetuned-ade-512-512](https://huggingface.co/nvidia/segformer-b0-finetuned-ade-512-512) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: nan |
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- Validation Loss: nan |
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- Validation Mean Iou: 0.0004 |
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- Validation Mean Accuracy: 0.5 |
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- Validation Overall Accuracy: 0.1499 |
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- Validation Accuracy Healthy: 1.0 |
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- Validation Accuracy Brownspot: 0.0 |
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- Validation Accuracy Leafblast: nan |
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- Validation Iou Healthy: 0.0009 |
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- Validation Iou Brownspot: 0.0 |
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- Validation Iou Leafblast: nan |
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- Epoch: 2 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- 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} |
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- training_precision: float32 |
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### Training results |
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| Train Loss | Validation Loss | Validation Mean Iou | Validation Mean Accuracy | Validation Overall Accuracy | Validation Accuracy Healthy | Validation Accuracy Brownspot | Validation Accuracy Leafblast | Validation Iou Healthy | Validation Iou Brownspot | Validation Iou Leafblast | Epoch | |
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|:----------:|:---------------:|:-------------------:|:------------------------:|:---------------------------:|:---------------------------:|:-----------------------------:|:-----------------------------:|:----------------------:|:------------------------:|:------------------------:|:-----:| |
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| nan | nan | 0.0004 | 0.5 | 0.1499 | 1.0 | 0.0 | nan | 0.0009 | 0.0 | nan | 0 | |
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| nan | nan | 0.0004 | 0.5 | 0.1499 | 1.0 | 0.0 | nan | 0.0009 | 0.0 | nan | 1 | |
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| nan | nan | 0.0004 | 0.5 | 0.1499 | 1.0 | 0.0 | nan | 0.0009 | 0.0 | nan | 2 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- TensorFlow 2.15.0 |
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- Datasets 2.15.0 |
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- Tokenizers 0.19.1 |
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