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---
license: other
base_model: nvidia/mit-b0
tags:
- generated_from_keras_callback
model-index:
- name: luca-g97/mit-b0-finetuned-sidewalks
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. -->
# luca-g97/mit-b0-finetuned-sidewalks
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: 1.3678
- Validation Loss: 0.8166
- Validation Mean Iou: 0.1980
- Validation Mean Accuracy: 0.2461
- Validation Overall Accuracy: 0.7806
- Validation Accuracy Unlabeled: 0.0
- Validation Accuracy Flat-road: 0.7198
- Validation Accuracy Flat-sidewalk: 0.9333
- Validation Accuracy Flat-crosswalk: 0.1239
- Validation Accuracy Flat-cyclinglane: 0.6224
- Validation Accuracy Flat-parkingdriveway: 0.2909
- Validation Accuracy Flat-railtrack: nan
- Validation Accuracy Flat-curb: 0.2044
- Validation Accuracy Human-person: 0.0227
- Validation Accuracy Human-rider: 0.0
- Validation Accuracy Vehicle-car: 0.8980
- Validation Accuracy Vehicle-truck: 0.0
- Validation Accuracy Vehicle-bus: nan
- Validation Accuracy Vehicle-tramtrain: nan
- Validation Accuracy Vehicle-motorcycle: 0.0
- Validation Accuracy Vehicle-bicycle: 0.0
- Validation Accuracy Vehicle-caravan: 0.0
- Validation Accuracy Vehicle-cartrailer: 0.0
- Validation Accuracy Construction-building: 0.8838
- Validation Accuracy Construction-door: 0.0
- Validation Accuracy Construction-wall: 0.0930
- Validation Accuracy Construction-fenceguardrail: 0.0426
- Validation Accuracy Construction-bridge: 0.0
- Validation Accuracy Construction-tunnel: nan
- Validation Accuracy Construction-stairs: 0.0
- Validation Accuracy Object-pole: 0.0725
- Validation Accuracy Object-trafficsign: 0.0
- Validation Accuracy Object-trafficlight: 0.0
- Validation Accuracy Nature-vegetation: 0.9093
- Validation Accuracy Nature-terrain: 0.8657
- Validation Accuracy Sky: 0.9392
- Validation Accuracy Void-ground: 0.0
- Validation Accuracy Void-dynamic: 0.0
- Validation Accuracy Void-static: 0.0062
- Validation Accuracy Void-unclear: 0.0
- Validation Iou Unlabeled: 0.0
- Validation Iou Flat-road: 0.5656
- Validation Iou Flat-sidewalk: 0.7927
- Validation Iou Flat-crosswalk: 0.1207
- Validation Iou Flat-cyclinglane: 0.5722
- Validation Iou Flat-parkingdriveway: 0.1948
- Validation Iou Flat-railtrack: nan
- Validation Iou Flat-curb: 0.1673
- Validation Iou Human-person: 0.0225
- Validation Iou Human-rider: 0.0
- Validation Iou Vehicle-car: 0.5772
- Validation Iou Vehicle-truck: 0.0
- Validation Iou Vehicle-bus: nan
- Validation Iou Vehicle-tramtrain: nan
- Validation Iou Vehicle-motorcycle: 0.0
- Validation Iou Vehicle-bicycle: 0.0
- Validation Iou Vehicle-caravan: 0.0
- Validation Iou Vehicle-cartrailer: 0.0
- Validation Iou Construction-building: 0.5809
- Validation Iou Construction-door: 0.0
- Validation Iou Construction-wall: 0.0864
- Validation Iou Construction-fenceguardrail: 0.0425
- Validation Iou Construction-bridge: 0.0
- Validation Iou Construction-tunnel: nan
- Validation Iou Construction-stairs: 0.0
- Validation Iou Object-pole: 0.0692
- Validation Iou Object-trafficsign: 0.0
- Validation Iou Object-trafficlight: 0.0
- Validation Iou Nature-vegetation: 0.7793
- Validation Iou Nature-terrain: 0.6938
- Validation Iou Sky: 0.8673
- Validation Iou Void-ground: 0.0
- Validation Iou Void-dynamic: 0.0
- Validation Iou Void-static: 0.0061
- Validation Iou Void-unclear: 0.0
- Epoch: 0
## 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': 6e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32
### Training results
| Train Loss | Validation Loss | Validation Mean Iou | Validation Mean Accuracy | Validation Overall Accuracy | Validation Accuracy Unlabeled | Validation Accuracy Flat-road | Validation Accuracy Flat-sidewalk | Validation Accuracy Flat-crosswalk | Validation Accuracy Flat-cyclinglane | Validation Accuracy Flat-parkingdriveway | Validation Accuracy Flat-railtrack | Validation Accuracy Flat-curb | Validation Accuracy Human-person | Validation Accuracy Human-rider | Validation Accuracy Vehicle-car | Validation Accuracy Vehicle-truck | Validation Accuracy Vehicle-bus | Validation Accuracy Vehicle-tramtrain | Validation Accuracy Vehicle-motorcycle | Validation Accuracy Vehicle-bicycle | Validation Accuracy Vehicle-caravan | Validation Accuracy Vehicle-cartrailer | Validation Accuracy Construction-building | Validation Accuracy Construction-door | Validation Accuracy Construction-wall | Validation Accuracy Construction-fenceguardrail | Validation Accuracy Construction-bridge | Validation Accuracy Construction-tunnel | Validation Accuracy Construction-stairs | Validation Accuracy Object-pole | Validation Accuracy Object-trafficsign | Validation Accuracy Object-trafficlight | Validation Accuracy Nature-vegetation | Validation Accuracy Nature-terrain | Validation Accuracy Sky | Validation Accuracy Void-ground | Validation Accuracy Void-dynamic | Validation Accuracy Void-static | Validation Accuracy Void-unclear | Validation Iou Unlabeled | Validation Iou Flat-road | Validation Iou Flat-sidewalk | Validation Iou Flat-crosswalk | Validation Iou Flat-cyclinglane | Validation Iou Flat-parkingdriveway | Validation Iou Flat-railtrack | Validation Iou Flat-curb | Validation Iou Human-person | Validation Iou Human-rider | Validation Iou Vehicle-car | Validation Iou Vehicle-truck | Validation Iou Vehicle-bus | Validation Iou Vehicle-tramtrain | Validation Iou Vehicle-motorcycle | Validation Iou Vehicle-bicycle | Validation Iou Vehicle-caravan | Validation Iou Vehicle-cartrailer | Validation Iou Construction-building | Validation Iou Construction-door | Validation Iou Construction-wall | Validation Iou Construction-fenceguardrail | Validation Iou Construction-bridge | Validation Iou Construction-tunnel | Validation Iou Construction-stairs | Validation Iou Object-pole | Validation Iou Object-trafficsign | Validation Iou Object-trafficlight | Validation Iou Nature-vegetation | Validation Iou Nature-terrain | Validation Iou Sky | Validation Iou Void-ground | Validation Iou Void-dynamic | Validation Iou Void-static | Validation Iou Void-unclear | Epoch |
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| 1.3678 | 0.8166 | 0.1980 | 0.2461 | 0.7806 | 0.0 | 0.7198 | 0.9333 | 0.1239 | 0.6224 | 0.2909 | nan | 0.2044 | 0.0227 | 0.0 | 0.8980 | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8838 | 0.0 | 0.0930 | 0.0426 | 0.0 | nan | 0.0 | 0.0725 | 0.0 | 0.0 | 0.9093 | 0.8657 | 0.9392 | 0.0 | 0.0 | 0.0062 | 0.0 | 0.0 | 0.5656 | 0.7927 | 0.1207 | 0.5722 | 0.1948 | nan | 0.1673 | 0.0225 | 0.0 | 0.5772 | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.5809 | 0.0 | 0.0864 | 0.0425 | 0.0 | nan | 0.0 | 0.0692 | 0.0 | 0.0 | 0.7793 | 0.6938 | 0.8673 | 0.0 | 0.0 | 0.0061 | 0.0 | 0 |
### Framework versions
- Transformers 4.35.0
- TensorFlow 2.14.0
- Datasets 2.14.6
- Tokenizers 0.14.1
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