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# MariaK/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: 0.8550
- Validation Loss: 0.8639
- Validation Mean Iou: 0.2220
- Validation Mean Accuracy: 0.2670
- Validation Overall Accuracy: 0.7725
- Validation Accuracy Unlabeled: 0.0
- Validation Accuracy Flat-road: 0.6015
- Validation Accuracy Flat-sidewalk: 0.9708
- Validation Accuracy Flat-crosswalk: 0.3807
- Validation Accuracy Flat-cyclinglane: 0.7538
- Validation Accuracy Flat-parkingdriveway: 0.1524
- Validation Accuracy Flat-railtrack: nan
- Validation Accuracy Flat-curb: 0.1957
- Validation Accuracy Human-person: 0.2585
- Validation Accuracy Human-rider: 0.0
- Validation Accuracy Vehicle-car: 0.8971
- 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: 0.0716
- Validation Accuracy Vehicle-caravan: 0.0
- Validation Accuracy Vehicle-cartrailer: 0.0
- Validation Accuracy Construction-building: 0.8784
- Validation Accuracy Construction-door: 0.0
- Validation Accuracy Construction-wall: 0.4315
- Validation Accuracy Construction-fenceguardrail: 0.1948
- Validation Accuracy Construction-bridge: 0.0
- Validation Accuracy Construction-tunnel: nan
- Validation Accuracy Construction-stairs: 0.0
- Validation Accuracy Object-pole: 0.1201
- Validation Accuracy Object-trafficsign: 0.0
- Validation Accuracy Object-trafficlight: 0.0
- Validation Accuracy Nature-vegetation: 0.8952
- Validation Accuracy Nature-terrain: 0.8231
- Validation Accuracy Sky: 0.8496
- Validation Accuracy Void-ground: 0.0
- Validation Accuracy Void-dynamic: 0.0
- Validation Accuracy Void-static: 0.0692
- Validation Accuracy Void-unclear: 0.0
- Validation Iou Unlabeled: 0.0
- Validation Iou Flat-road: 0.5568
- Validation Iou Flat-sidewalk: 0.7479
- Validation Iou Flat-crosswalk: 0.3509
- Validation Iou Flat-cyclinglane: 0.6355
- Validation Iou Flat-parkingdriveway: 0.1298
- Validation Iou Flat-railtrack: nan
- Validation Iou Flat-curb: 0.1326
- Validation Iou Human-person: 0.2455
- Validation Iou Human-rider: 0.0
- Validation Iou Vehicle-car: 0.6973
- 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: 0.0610
- Validation Iou Vehicle-caravan: 0.0
- Validation Iou Vehicle-cartrailer: 0.0
- Validation Iou Construction-building: 0.6479
- Validation Iou Construction-door: 0.0
- Validation Iou Construction-wall: 0.3003
- Validation Iou Construction-fenceguardrail: 0.1727
- Validation Iou Construction-bridge: 0.0
- Validation Iou Construction-tunnel: nan
- Validation Iou Construction-stairs: 0.0
- Validation Iou Object-pole: 0.0927
- Validation Iou Object-trafficsign: 0.0
- Validation Iou Object-trafficlight: 0.0
- Validation Iou Nature-vegetation: 0.7758
- Validation Iou Nature-terrain: 0.7000
- Validation Iou Sky: 0.8002
- Validation Iou Void-ground: 0.0
- Validation Iou Void-dynamic: 0.0
- Validation Iou Void-static: 0.0573
- 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', 'learning_rate': 6e-05, 'decay': 0.0, '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 |
|:----------:|:---------------:|:-------------------:|:------------------------:|:---------------------------:|:-----------------------------:|:-----------------------------:|:---------------------------------:|:----------------------------------:|:------------------------------------:|:----------------------------------------:|:----------------------------------:|:-----------------------------:|:--------------------------------:|:-------------------------------:|:-------------------------------:|:---------------------------------:|:-------------------------------:|:-------------------------------------:|:--------------------------------------:|:-----------------------------------:|:-----------------------------------:|:--------------------------------------:|:-----------------------------------------:|:-------------------------------------:|:-------------------------------------:|:-----------------------------------------------:|:---------------------------------------:|:---------------------------------------:|:---------------------------------------:|:-------------------------------:|:--------------------------------------:|:---------------------------------------:|:-------------------------------------:|:----------------------------------:|:-----------------------:|:-------------------------------:|:--------------------------------:|:-------------------------------:|:--------------------------------:|:------------------------:|:------------------------:|:----------------------------:|:-----------------------------:|:-------------------------------:|:-----------------------------------:|:-----------------------------:|:------------------------:|:---------------------------:|:--------------------------:|:--------------------------:|:----------------------------:|:--------------------------:|:--------------------------------:|:---------------------------------:|:------------------------------:|:------------------------------:|:---------------------------------:|:------------------------------------:|:--------------------------------:|:--------------------------------:|:------------------------------------------:|:----------------------------------:|:----------------------------------:|:----------------------------------:|:--------------------------:|:---------------------------------:|:----------------------------------:|:--------------------------------:|:-----------------------------:|:------------------:|:--------------------------:|:---------------------------:|:--------------------------:|:---------------------------:|:-----:|
| 1.4362     | 0.9804          | 0.1752              | 0.2219                   | 0.7360                      | 0.0                           | 0.7417                        | 0.9512                            | 0.0213                             | 0.3662                               | 0.1475                                   | nan                                | 0.1397                        | 0.0055                           | 0.0                             | 0.8653                          | 0.0                               | 0.0                             | nan                                   | 0.0                                    | 0.0002                              | 0.0                                 | 0.0                                    | 0.7778                                    | 0.0                                   | 0.3370                                | 0.0429                                          | 0.0                                     | nan                                     | 0.0                                     | 0.0177                          | 0.0                                    | 0.0                                     | 0.9324                                | 0.7967                             | 0.9157                  | 0.0                             | 0.0                              | 0.0409                          | 0.0                              | 0.0                      | 0.5263                   | 0.7377                       | 0.0213                        | 0.3517                          | 0.1232                              | nan                           | 0.1053                   | 0.0055                      | 0.0                        | 0.6423                     | 0.0                          | 0.0                        | nan                              | 0.0                               | 0.0002                         | 0.0                            | 0.0                               | 0.6012                               | 0.0                              | 0.2315                           | 0.0424                                     | 0.0                                | nan                                | 0.0                                | 0.0163                     | 0.0                               | 0.0                                | 0.7258                           | 0.6752                        | 0.7692             | 0.0                        | 0.0                         | 0.0321                     | 0.0                         | 0     |
| 0.8550     | 0.8639          | 0.2220              | 0.2670                   | 0.7725                      | 0.0                           | 0.6015                        | 0.9708                            | 0.3807                             | 0.7538                               | 0.1524                                   | nan                                | 0.1957                        | 0.2585                           | 0.0                             | 0.8971                          | 0.0                               | 0.0                             | nan                                   | 0.0                                    | 0.0716                              | 0.0                                 | 0.0                                    | 0.8784                                    | 0.0                                   | 0.4315                                | 0.1948                                          | 0.0                                     | nan                                     | 0.0                                     | 0.1201                          | 0.0                                    | 0.0                                     | 0.8952                                | 0.8231                             | 0.8496                  | 0.0                             | 0.0                              | 0.0692                          | 0.0                              | 0.0                      | 0.5568                   | 0.7479                       | 0.3509                        | 0.6355                          | 0.1298                              | nan                           | 0.1326                   | 0.2455                      | 0.0                        | 0.6973                     | 0.0                          | 0.0                        | nan                              | 0.0                               | 0.0610                         | 0.0                            | 0.0                               | 0.6479                               | 0.0                              | 0.3003                           | 0.1727                                     | 0.0                                | nan                                | 0.0                                | 0.0927                     | 0.0                               | 0.0                                | 0.7758                           | 0.7000                        | 0.8002             | 0.0                        | 0.0                         | 0.0573                     | 0.0                         | 1     |


### Framework versions

- Transformers 4.25.1
- TensorFlow 2.9.2
- Datasets 2.8.0
- Tokenizers 0.13.2

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

MariaK/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: 0.8550
* Validation Loss: 0.8639
* Validation Mean Iou: 0.2220
* Validation Mean Accuracy: 0.2670
* Validation Overall Accuracy: 0.7725
* Validation Accuracy Unlabeled: 0.0
* Validation Accuracy Flat-road: 0.6015
* Validation Accuracy Flat-sidewalk: 0.9708
* Validation Accuracy Flat-crosswalk: 0.3807
* Validation Accuracy Flat-cyclinglane: 0.7538
* Validation Accuracy Flat-parkingdriveway: 0.1524
* Validation Accuracy Flat-railtrack: nan
* Validation Accuracy Flat-curb: 0.1957
* Validation Accuracy Human-person: 0.2585
* Validation Accuracy Human-rider: 0.0
* Validation Accuracy Vehicle-car: 0.8971
* 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: 0.0716
* Validation Accuracy Vehicle-caravan: 0.0
* Validation Accuracy Vehicle-cartrailer: 0.0
* Validation Accuracy Construction-building: 0.8784
* Validation Accuracy Construction-door: 0.0
* Validation Accuracy Construction-wall: 0.4315
* Validation Accuracy Construction-fenceguardrail: 0.1948
* Validation Accuracy Construction-bridge: 0.0
* Validation Accuracy Construction-tunnel: nan
* Validation Accuracy Construction-stairs: 0.0
* Validation Accuracy Object-pole: 0.1201
* Validation Accuracy Object-trafficsign: 0.0
* Validation Accuracy Object-trafficlight: 0.0
* Validation Accuracy Nature-vegetation: 0.8952
* Validation Accuracy Nature-terrain: 0.8231
* Validation Accuracy Sky: 0.8496
* Validation Accuracy Void-ground: 0.0
* Validation Accuracy Void-dynamic: 0.0
* Validation Accuracy Void-static: 0.0692
* Validation Accuracy Void-unclear: 0.0
* Validation Iou Unlabeled: 0.0
* Validation Iou Flat-road: 0.5568
* Validation Iou Flat-sidewalk: 0.7479
* Validation Iou Flat-crosswalk: 0.3509
* Validation Iou Flat-cyclinglane: 0.6355
* Validation Iou Flat-parkingdriveway: 0.1298
* Validation Iou Flat-railtrack: nan
* Validation Iou Flat-curb: 0.1326
* Validation Iou Human-person: 0.2455
* Validation Iou Human-rider: 0.0
* Validation Iou Vehicle-car: 0.6973
* 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: 0.0610
* Validation Iou Vehicle-caravan: 0.0
* Validation Iou Vehicle-cartrailer: 0.0
* Validation Iou Construction-building: 0.6479
* Validation Iou Construction-door: 0.0
* Validation Iou Construction-wall: 0.3003
* Validation Iou Construction-fenceguardrail: 0.1727
* Validation Iou Construction-bridge: 0.0
* Validation Iou Construction-tunnel: nan
* Validation Iou Construction-stairs: 0.0
* Validation Iou Object-pole: 0.0927
* Validation Iou Object-trafficsign: 0.0
* Validation Iou Object-trafficlight: 0.0
* Validation Iou Nature-vegetation: 0.7758
* Validation Iou Nature-terrain: 0.7000
* Validation Iou Sky: 0.8002
* Validation Iou Void-ground: 0.0
* Validation Iou Void-dynamic: 0.0
* Validation Iou Void-static: 0.0573
* 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', 'learning\_rate': 6e-05, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32


### Training results



### Framework versions


* Transformers 4.25.1
* TensorFlow 2.9.2
* Datasets 2.8.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'Adam', 'learning\_rate': 6e-05, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.25.1
* TensorFlow 2.9.2
* Datasets 2.8.0
* Tokenizers 0.13.2
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', 'learning\_rate': 6e-05, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.25.1
* TensorFlow 2.9.2
* Datasets 2.8.0
* Tokenizers 0.13.2
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', 'learning\_rate': 6e-05, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32### Training results### Framework versions


* Transformers 4.25.1
* TensorFlow 2.9.2
* Datasets 2.8.0
* Tokenizers 0.13.2