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---
library_name: transformers
license: other
base_model: nvidia/mit-b0
tags:
- generated_from_keras_callback
model-index:
- name: code135/scene_segmentation
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# code135/scene_segmentation
This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/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', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 6e-05, 'decay_steps': 120, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32
### Training results
| Train Loss | Validation Loss | Validation Mean Iou | Validation Mean Accuracy | Validation Overall Accuracy | Validation Accuracy Ciel | Validation Accuracy Vegetation | Validation Accuracy Batiment peu vitre (<50%) | Validation Accuracy Batiment tres vitre (>50%) | Validation Accuracy Couvert | Validation Accuracy Autre | Validation Iou Ciel | Validation Iou Vegetation | Validation Iou Batiment peu vitre (<50%) | Validation Iou Batiment tres vitre (>50%) | Validation Iou Couvert | Validation Iou Autre | Epoch |
|:----------:|:---------------:|:-------------------:|:------------------------:|:---------------------------:|:------------------------:|:------------------------------:|:---------------------------------------------:|:----------------------------------------------:|:---------------------------:|:-------------------------:|:-------------------:|:-------------------------:|:----------------------------------------:|:-----------------------------------------:|:----------------------:|:--------------------:|:-----:|
| nan | nan | 0.0183 | 0.1667 | 0.1607 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1098 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0 |
| nan | nan | 0.0183 | 0.1667 | 0.1607 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1098 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1 |
| nan | nan | 0.0183 | 0.1667 | 0.1607 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1098 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 2 |
### Framework versions
- Transformers 4.46.2
- TensorFlow 2.17.1
- Datasets 3.1.0
- Tokenizers 0.20.3
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