
<!-- 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. -->

# Artur01/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: 1.3943
- Validation Loss: 0.8293
- Validation Mean Iou: 0.2097
- Validation Mean Accuracy: 0.2617
- Validation Overall Accuracy: 0.7688
- Validation Accuracy Unlabeled: 0.0
- Validation Accuracy Flat-road: 0.6688
- Validation Accuracy Flat-sidewalk: 0.9258
- Validation Accuracy Flat-crosswalk: 0.4607
- Validation Accuracy Flat-cyclinglane: 0.7716
- Validation Accuracy Flat-parkingdriveway: 0.2329
- Validation Accuracy Flat-railtrack: nan
- Validation Accuracy Flat-curb: 0.1001
- Validation Accuracy Human-person: 0.0011
- Validation Accuracy Human-rider: 0.0
- Validation Accuracy Vehicle-car: 0.8806
- 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: 0.2446
- Validation Accuracy Vehicle-caravan: 0.0
- Validation Accuracy Vehicle-cartrailer: nan
- Validation Accuracy Construction-building: 0.8260
- Validation Accuracy Construction-door: 0.0
- Validation Accuracy Construction-wall: 0.2769
- Validation Accuracy Construction-fenceguardrail: 0.0618
- Validation Accuracy Construction-bridge: 0.0
- Validation Accuracy Construction-tunnel: nan
- Validation Accuracy Construction-stairs: 0.0
- Validation Accuracy Object-pole: 0.0127
- Validation Accuracy Object-trafficsign: 0.0
- Validation Accuracy Object-trafficlight: 0.0
- Validation Accuracy Nature-vegetation: 0.9125
- Validation Accuracy Nature-terrain: 0.7600
- Validation Accuracy Sky: 0.9223
- Validation Accuracy Void-ground: 0.0
- Validation Accuracy Void-dynamic: 0.0122
- Validation Accuracy Void-static: 0.0431
- Validation Accuracy Void-unclear: 0.0
- Validation Iou Unlabeled: 0.0
- Validation Iou Flat-road: 0.5491
- Validation Iou Flat-sidewalk: 0.7881
- Validation Iou Flat-crosswalk: 0.4034
- Validation Iou Flat-cyclinglane: 0.4981
- Validation Iou Flat-parkingdriveway: 0.1731
- Validation Iou Flat-railtrack: nan
- Validation Iou Flat-curb: 0.0869
- Validation Iou Human-person: 0.0011
- Validation Iou Human-rider: 0.0
- Validation Iou Vehicle-car: 0.6311
- 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: 0.2027
- Validation Iou Vehicle-caravan: 0.0
- Validation Iou Vehicle-cartrailer: nan
- Validation Iou Construction-building: 0.5921
- Validation Iou Construction-door: 0.0
- Validation Iou Construction-wall: 0.2356
- Validation Iou Construction-fenceguardrail: 0.0570
- Validation Iou Construction-bridge: 0.0
- Validation Iou Construction-tunnel: nan
- Validation Iou Construction-stairs: 0.0
- Validation Iou Object-pole: 0.0125
- Validation Iou Object-trafficsign: 0.0
- Validation Iou Object-trafficlight: 0.0
- Validation Iou Nature-vegetation: 0.7724
- Validation Iou Nature-terrain: 0.5932
- Validation Iou Sky: 0.8602
- Validation Iou Void-ground: 0.0
- Validation Iou Void-dynamic: 0.0120
- Validation Iou Void-static: 0.0323
- 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 |
|:----------:|:---------------:|:-------------------:|:------------------------:|:---------------------------:|:-----------------------------:|:-----------------------------:|:---------------------------------:|:----------------------------------:|:------------------------------------:|:----------------------------------------:|:----------------------------------:|:-----------------------------:|:--------------------------------:|:-------------------------------:|:-------------------------------:|:---------------------------------:|:-------------------------------:|:-------------------------------------:|:--------------------------------------:|:-----------------------------------:|:-----------------------------------:|:--------------------------------------:|:-----------------------------------------:|:-------------------------------------:|:-------------------------------------:|:-----------------------------------------------:|:---------------------------------------:|:---------------------------------------:|:---------------------------------------:|:-------------------------------:|:--------------------------------------:|:---------------------------------------:|:-------------------------------------:|:----------------------------------:|:-----------------------:|:-------------------------------:|:--------------------------------:|:-------------------------------:|:--------------------------------:|:------------------------:|:------------------------:|:----------------------------:|:-----------------------------:|:-------------------------------:|:-----------------------------------:|:-----------------------------:|:------------------------:|:---------------------------:|:--------------------------:|:--------------------------:|:----------------------------:|:--------------------------:|:--------------------------------:|:---------------------------------:|:------------------------------:|:------------------------------:|:---------------------------------:|:------------------------------------:|:--------------------------------:|:--------------------------------:|:------------------------------------------:|:----------------------------------:|:----------------------------------:|:----------------------------------:|:--------------------------:|:---------------------------------:|:----------------------------------:|:--------------------------------:|:-----------------------------:|:------------------:|:--------------------------:|:---------------------------:|:--------------------------:|:---------------------------:|:-----:|
| 1.3943     | 0.8293          | 0.2097              | 0.2617                   | 0.7688                      | 0.0                           | 0.6688                        | 0.9258                            | 0.4607                             | 0.7716                               | 0.2329                                   | nan                                | 0.1001                        | 0.0011                           | 0.0                             | 0.8806                          | 0.0                               | 0.0                             | nan                                   | 0.0                                    | 0.2446                              | 0.0                                 | nan                                    | 0.8260                                    | 0.0                                   | 0.2769                                | 0.0618                                          | 0.0                                     | nan                                     | 0.0                                     | 0.0127                          | 0.0                                    | 0.0                                     | 0.9125                                | 0.7600                             | 0.9223                  | 0.0                             | 0.0122                           | 0.0431                          | 0.0                              | 0.0                      | 0.5491                   | 0.7881                       | 0.4034                        | 0.4981                          | 0.1731                              | nan                           | 0.0869                   | 0.0011                      | 0.0                        | 0.6311                     | 0.0                          | 0.0                        | nan                              | 0.0                               | 0.2027                         | 0.0                            | nan                               | 0.5921                               | 0.0                              | 0.2356                           | 0.0570                                     | 0.0                                | nan                                | 0.0                                | 0.0125                     | 0.0                               | 0.0                                | 0.7724                           | 0.5932                        | 0.8602             | 0.0                        | 0.0120                      | 0.0323                     | 0.0                         | 0     |


### Framework versions

- Transformers 4.28.0
- TensorFlow 2.12.0
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "other", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "Artur01/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 

Artur01/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: 1.3943
* Validation Loss: 0.8293
* Validation Mean Iou: 0.2097
* Validation Mean Accuracy: 0.2617
* Validation Overall Accuracy: 0.7688
* Validation Accuracy Unlabeled: 0.0
* Validation Accuracy Flat-road: 0.6688
* Validation Accuracy Flat-sidewalk: 0.9258
* Validation Accuracy Flat-crosswalk: 0.4607
* Validation Accuracy Flat-cyclinglane: 0.7716
* Validation Accuracy Flat-parkingdriveway: 0.2329
* Validation Accuracy Flat-railtrack: nan
* Validation Accuracy Flat-curb: 0.1001
* Validation Accuracy Human-person: 0.0011
* Validation Accuracy Human-rider: 0.0
* Validation Accuracy Vehicle-car: 0.8806
* 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: 0.2446
* Validation Accuracy Vehicle-caravan: 0.0
* Validation Accuracy Vehicle-cartrailer: nan
* Validation Accuracy Construction-building: 0.8260
* Validation Accuracy Construction-door: 0.0
* Validation Accuracy Construction-wall: 0.2769
* Validation Accuracy Construction-fenceguardrail: 0.0618
* Validation Accuracy Construction-bridge: 0.0
* Validation Accuracy Construction-tunnel: nan
* Validation Accuracy Construction-stairs: 0.0
* Validation Accuracy Object-pole: 0.0127
* Validation Accuracy Object-trafficsign: 0.0
* Validation Accuracy Object-trafficlight: 0.0
* Validation Accuracy Nature-vegetation: 0.9125
* Validation Accuracy Nature-terrain: 0.7600
* Validation Accuracy Sky: 0.9223
* Validation Accuracy Void-ground: 0.0
* Validation Accuracy Void-dynamic: 0.0122
* Validation Accuracy Void-static: 0.0431
* Validation Accuracy Void-unclear: 0.0
* Validation Iou Unlabeled: 0.0
* Validation Iou Flat-road: 0.5491
* Validation Iou Flat-sidewalk: 0.7881
* Validation Iou Flat-crosswalk: 0.4034
* Validation Iou Flat-cyclinglane: 0.4981
* Validation Iou Flat-parkingdriveway: 0.1731
* Validation Iou Flat-railtrack: nan
* Validation Iou Flat-curb: 0.0869
* Validation Iou Human-person: 0.0011
* Validation Iou Human-rider: 0.0
* Validation Iou Vehicle-car: 0.6311
* 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: 0.2027
* Validation Iou Vehicle-caravan: 0.0
* Validation Iou Vehicle-cartrailer: nan
* Validation Iou Construction-building: 0.5921
* Validation Iou Construction-door: 0.0
* Validation Iou Construction-wall: 0.2356
* Validation Iou Construction-fenceguardrail: 0.0570
* Validation Iou Construction-bridge: 0.0
* Validation Iou Construction-tunnel: nan
* Validation Iou Construction-stairs: 0.0
* Validation Iou Object-pole: 0.0125
* Validation Iou Object-trafficsign: 0.0
* Validation Iou Object-trafficlight: 0.0
* Validation Iou Nature-vegetation: 0.7724
* Validation Iou Nature-terrain: 0.5932
* Validation Iou Sky: 0.8602
* Validation Iou Void-ground: 0.0
* Validation Iou Void-dynamic: 0.0120
* Validation Iou Void-static: 0.0323
* 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



### Framework versions


* Transformers 4.28.0
* 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 4.28.0
* 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 4.28.0
* TensorFlow 2.12.0
* Datasets 2.12.0
* Tokenizers 0.13.3