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# pecra/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: 0.8276
- Validation Loss: 0.7087
- Validation Mean Iou: 0.2488
- Validation Mean Accuracy: 0.3100
- Validation Overall Accuracy: 0.7987
- Validation Accuracy Unlabeled: 0.0
- Validation Accuracy Flat-road: 0.7917
- Validation Accuracy Flat-sidewalk: 0.9332
- Validation Accuracy Flat-crosswalk: 0.7636
- Validation Accuracy Flat-cyclinglane: 0.8238
- Validation Accuracy Flat-parkingdriveway: 0.1196
- Validation Accuracy Flat-railtrack: nan
- Validation Accuracy Flat-curb: 0.3568
- Validation Accuracy Human-person: 0.7259
- Validation Accuracy Human-rider: 0.0
- Validation Accuracy Vehicle-car: 0.8780
- Validation Accuracy Vehicle-truck: 0.0
- Validation Accuracy Vehicle-bus: 0.0
- Validation Accuracy Vehicle-tramtrain: nan
- Validation Accuracy Vehicle-motorcycle: 0.0
- Validation Accuracy Vehicle-bicycle: 0.3959
- Validation Accuracy Vehicle-caravan: 0.0
- Validation Accuracy Vehicle-cartrailer: 0.0
- Validation Accuracy Construction-building: 0.8757
- Validation Accuracy Construction-door: 0.0
- Validation Accuracy Construction-wall: 0.2241
- Validation Accuracy Construction-fenceguardrail: 0.3394
- Validation Accuracy Construction-bridge: 0.0
- Validation Accuracy Construction-tunnel: 0.0
- Validation Accuracy Construction-stairs: 0.0
- Validation Accuracy Object-pole: 0.1857
- Validation Accuracy Object-trafficsign: 0.0
- Validation Accuracy Object-trafficlight: 0.0
- Validation Accuracy Nature-vegetation: 0.9210
- Validation Accuracy Nature-terrain: 0.7914
- Validation Accuracy Sky: 0.9488
- Validation Accuracy Void-ground: 0.0
- Validation Accuracy Void-dynamic: 0.0
- Validation Accuracy Void-static: 0.1548
- Validation Accuracy Void-unclear: 0.0
- Validation Iou Unlabeled: 0.0
- Validation Iou Flat-road: 0.6333
- Validation Iou Flat-sidewalk: 0.8196
- Validation Iou Flat-crosswalk: 0.5763
- Validation Iou Flat-cyclinglane: 0.7280
- Validation Iou Flat-parkingdriveway: 0.1057
- Validation Iou Flat-railtrack: nan
- Validation Iou Flat-curb: 0.2409
- Validation Iou Human-person: 0.4810
- Validation Iou Human-rider: 0.0
- Validation Iou Vehicle-car: 0.7216
- Validation Iou Vehicle-truck: 0.0
- Validation Iou Vehicle-bus: 0.0
- Validation Iou Vehicle-tramtrain: nan
- Validation Iou Vehicle-motorcycle: 0.0
- Validation Iou Vehicle-bicycle: 0.2825
- Validation Iou Vehicle-caravan: 0.0
- Validation Iou Vehicle-cartrailer: 0.0
- Validation Iou Construction-building: 0.6307
- Validation Iou Construction-door: 0.0
- Validation Iou Construction-wall: 0.1908
- Validation Iou Construction-fenceguardrail: 0.2551
- Validation Iou Construction-bridge: 0.0
- Validation Iou Construction-tunnel: 0.0
- Validation Iou Construction-stairs: 0.0
- Validation Iou Object-pole: 0.1625
- Validation Iou Object-trafficsign: 0.0
- Validation Iou Object-trafficlight: 0.0
- Validation Iou Nature-vegetation: 0.7648
- Validation Iou Nature-terrain: 0.6071
- Validation Iou Sky: 0.8958
- Validation Iou Void-ground: 0.0
- Validation Iou Void-dynamic: 0.0
- Validation Iou Void-static: 0.1149
- Validation Iou Void-unclear: 0.0
- Epoch: 1

## 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 |
|:----------:|:---------------:|:-------------------:|:------------------------:|:---------------------------:|:-----------------------------:|:-----------------------------:|:---------------------------------:|:----------------------------------:|:------------------------------------:|:----------------------------------------:|:----------------------------------:|:-----------------------------:|:--------------------------------:|:-------------------------------:|:-------------------------------:|:---------------------------------:|:-------------------------------:|:-------------------------------------:|:--------------------------------------:|:-----------------------------------:|:-----------------------------------:|:--------------------------------------:|:-----------------------------------------:|:-------------------------------------:|:-------------------------------------:|:-----------------------------------------------:|:---------------------------------------:|:---------------------------------------:|:---------------------------------------:|:-------------------------------:|:--------------------------------------:|:---------------------------------------:|:-------------------------------------:|:----------------------------------:|:-----------------------:|:-------------------------------:|:--------------------------------:|:-------------------------------:|:--------------------------------:|:------------------------:|:------------------------:|:----------------------------:|:-----------------------------:|:-------------------------------:|:-----------------------------------:|:-----------------------------:|:------------------------:|:---------------------------:|:--------------------------:|:--------------------------:|:----------------------------:|:--------------------------:|:--------------------------------:|:---------------------------------:|:------------------------------:|:------------------------------:|:---------------------------------:|:------------------------------------:|:--------------------------------:|:--------------------------------:|:------------------------------------------:|:----------------------------------:|:----------------------------------:|:----------------------------------:|:--------------------------:|:---------------------------------:|:----------------------------------:|:--------------------------------:|:-----------------------------:|:------------------:|:--------------------------:|:---------------------------:|:--------------------------:|:---------------------------:|:-----:|
| 1.3899     | 0.8648          | 0.1967              | 0.2417                   | 0.7536                      | 0.0                           | 0.6349                        | 0.9590                            | 0.1580                             | 0.7351                               | 0.1644                                   | nan                                | 0.1925                        | 0.4170                           | 0.0                             | 0.8121                          | 0.0                               | 0.0                             | nan                                   | 0.0                                    | 0.1536                              | 0.0                                 | 0.0                                    | 0.8972                                    | 0.0                                   | 0.1150                                | 0.0695                                          | 0.0                                     | 0.0                                     | 0.0                                     | 0.0352                          | 0.0                                    | 0.0                                     | 0.8874                                | 0.7578                             | 0.9500                  | 0.0                             | 0.0                              | 0.0383                          | 0.0                              | 0.0                      | 0.4984                   | 0.7628                       | 0.1568                        | 0.6469                          | 0.1219                              | nan                           | 0.1421                   | 0.3436                      | 0.0                        | 0.6648                     | 0.0                          | 0.0                        | nan                              | 0.0                               | 0.1348                         | 0.0                            | 0.0                               | 0.5662                               | 0.0                              | 0.1019                           | 0.0655                                     | 0.0                                | 0.0                                | 0.0                                | 0.0345                     | 0.0                               | 0.0                                | 0.7491                           | 0.5971                        | 0.8673             | 0.0                        | 0.0                         | 0.0366                     | 0.0                         | 0     |
| 0.8276     | 0.7087          | 0.2488              | 0.3100                   | 0.7987                      | 0.0                           | 0.7917                        | 0.9332                            | 0.7636                             | 0.8238                               | 0.1196                                   | nan                                | 0.3568                        | 0.7259                           | 0.0                             | 0.8780                          | 0.0                               | 0.0                             | nan                                   | 0.0                                    | 0.3959                              | 0.0                                 | 0.0                                    | 0.8757                                    | 0.0                                   | 0.2241                                | 0.3394                                          | 0.0                                     | 0.0                                     | 0.0                                     | 0.1857                          | 0.0                                    | 0.0                                     | 0.9210                                | 0.7914                             | 0.9488                  | 0.0                             | 0.0                              | 0.1548                          | 0.0                              | 0.0                      | 0.6333                   | 0.8196                       | 0.5763                        | 0.7280                          | 0.1057                              | nan                           | 0.2409                   | 0.4810                      | 0.0                        | 0.7216                     | 0.0                          | 0.0                        | nan                              | 0.0                               | 0.2825                         | 0.0                            | 0.0                               | 0.6307                               | 0.0                              | 0.1908                           | 0.2551                                     | 0.0                                | 0.0                                | 0.0                                | 0.1625                     | 0.0                               | 0.0                                | 0.7648                           | 0.6071                        | 0.8958             | 0.0                        | 0.0                         | 0.1149                     | 0.0                         | 1     |


### Framework versions

- Transformers 4.28.1
- TensorFlow 2.12.0
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "other", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "pecra/mit-b0-finetuned-sidewalks", "results": []}]}
transformers tf segformer generated_from_keras_callback license:other endpoints_compatible region:us
TAGS
#transformers #tf #segformer #generated_from_keras_callback #license-other #endpoints_compatible #region-us 

pecra/mit-b0-finetuned-sidewalks
================================


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: 0.8276
* Validation Loss: 0.7087
* Validation Mean Iou: 0.2488
* Validation Mean Accuracy: 0.3100
* Validation Overall Accuracy: 0.7987
* Validation Accuracy Unlabeled: 0.0
* Validation Accuracy Flat-road: 0.7917
* Validation Accuracy Flat-sidewalk: 0.9332
* Validation Accuracy Flat-crosswalk: 0.7636
* Validation Accuracy Flat-cyclinglane: 0.8238
* Validation Accuracy Flat-parkingdriveway: 0.1196
* Validation Accuracy Flat-railtrack: nan
* Validation Accuracy Flat-curb: 0.3568
* Validation Accuracy Human-person: 0.7259
* Validation Accuracy Human-rider: 0.0
* Validation Accuracy Vehicle-car: 0.8780
* Validation Accuracy Vehicle-truck: 0.0
* Validation Accuracy Vehicle-bus: 0.0
* Validation Accuracy Vehicle-tramtrain: nan
* Validation Accuracy Vehicle-motorcycle: 0.0
* Validation Accuracy Vehicle-bicycle: 0.3959
* Validation Accuracy Vehicle-caravan: 0.0
* Validation Accuracy Vehicle-cartrailer: 0.0
* Validation Accuracy Construction-building: 0.8757
* Validation Accuracy Construction-door: 0.0
* Validation Accuracy Construction-wall: 0.2241
* Validation Accuracy Construction-fenceguardrail: 0.3394
* Validation Accuracy Construction-bridge: 0.0
* Validation Accuracy Construction-tunnel: 0.0
* Validation Accuracy Construction-stairs: 0.0
* Validation Accuracy Object-pole: 0.1857
* Validation Accuracy Object-trafficsign: 0.0
* Validation Accuracy Object-trafficlight: 0.0
* Validation Accuracy Nature-vegetation: 0.9210
* Validation Accuracy Nature-terrain: 0.7914
* Validation Accuracy Sky: 0.9488
* Validation Accuracy Void-ground: 0.0
* Validation Accuracy Void-dynamic: 0.0
* Validation Accuracy Void-static: 0.1548
* Validation Accuracy Void-unclear: 0.0
* Validation Iou Unlabeled: 0.0
* Validation Iou Flat-road: 0.6333
* Validation Iou Flat-sidewalk: 0.8196
* Validation Iou Flat-crosswalk: 0.5763
* Validation Iou Flat-cyclinglane: 0.7280
* Validation Iou Flat-parkingdriveway: 0.1057
* Validation Iou Flat-railtrack: nan
* Validation Iou Flat-curb: 0.2409
* Validation Iou Human-person: 0.4810
* Validation Iou Human-rider: 0.0
* Validation Iou Vehicle-car: 0.7216
* Validation Iou Vehicle-truck: 0.0
* Validation Iou Vehicle-bus: 0.0
* Validation Iou Vehicle-tramtrain: nan
* Validation Iou Vehicle-motorcycle: 0.0
* Validation Iou Vehicle-bicycle: 0.2825
* Validation Iou Vehicle-caravan: 0.0
* Validation Iou Vehicle-cartrailer: 0.0
* Validation Iou Construction-building: 0.6307
* Validation Iou Construction-door: 0.0
* Validation Iou Construction-wall: 0.1908
* Validation Iou Construction-fenceguardrail: 0.2551
* Validation Iou Construction-bridge: 0.0
* Validation Iou Construction-tunnel: 0.0
* Validation Iou Construction-stairs: 0.0
* Validation Iou Object-pole: 0.1625
* Validation Iou Object-trafficsign: 0.0
* Validation Iou Object-trafficlight: 0.0
* Validation Iou Nature-vegetation: 0.7648
* Validation Iou Nature-terrain: 0.6071
* Validation Iou Sky: 0.8958
* Validation Iou Void-ground: 0.0
* Validation Iou Void-dynamic: 0.0
* Validation Iou Void-static: 0.1149
* Validation Iou Void-unclear: 0.0
* Epoch: 1


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



### Framework versions


* Transformers 4.28.1
* TensorFlow 2.12.0
* Datasets 2.12.0
* Tokenizers 0.13.3



### 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 ### Framework versions


* Transformers 4.28.1
* TensorFlow 2.12.0
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #tf #segformer #generated_from_keras_callback #license-other #endpoints_compatible #region-us 
 ### 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 ### Framework versions


* Transformers 4.28.1
* TensorFlow 2.12.0
* Datasets 2.12.0
* Tokenizers 0.13.3