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# ThomasLam/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: 0.5617
- Validation Loss: 0.5455
- Validation Mean Iou: 0.2981
- Validation Mean Accuracy: 0.3694
- Validation Overall Accuracy: 0.8400
- Validation Accuracy Unlabeled: 0.0
- Validation Accuracy Flat-road: 0.8592
- Validation Accuracy Flat-sidewalk: 0.9015
- Validation Accuracy Flat-crosswalk: 0.6943
- Validation Accuracy Flat-cyclinglane: 0.8471
- Validation Accuracy Flat-parkingdriveway: 0.5867
- Validation Accuracy Flat-railtrack: nan
- Validation Accuracy Flat-curb: 0.4839
- Validation Accuracy Human-person: 0.5402
- Validation Accuracy Human-rider: 0.0
- Validation Accuracy Vehicle-car: 0.9318
- 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: 0.6756
- Validation Accuracy Vehicle-caravan: 0.0
- Validation Accuracy Vehicle-cartrailer: 0.0
- Validation Accuracy Construction-building: 0.8796
- Validation Accuracy Construction-door: 0.0
- Validation Accuracy Construction-wall: 0.6019
- Validation Accuracy Construction-fenceguardrail: 0.5454
- Validation Accuracy Construction-bridge: 0.0
- Validation Accuracy Construction-tunnel: nan
- Validation Accuracy Construction-stairs: 0.0
- Validation Accuracy Object-pole: 0.3915
- Validation Accuracy Object-trafficsign: 0.0
- Validation Accuracy Object-trafficlight: 0.0
- Validation Accuracy Nature-vegetation: 0.9456
- Validation Accuracy Nature-terrain: 0.7224
- Validation Accuracy Sky: 0.9630
- Validation Accuracy Void-ground: 0.0
- Validation Accuracy Void-dynamic: 0.0005
- Validation Accuracy Void-static: 0.2520
- Validation Accuracy Void-unclear: 0.0
- Validation Iou Unlabeled: 0.0
- Validation Iou Flat-road: 0.6794
- Validation Iou Flat-sidewalk: 0.8423
- Validation Iou Flat-crosswalk: 0.4614
- Validation Iou Flat-cyclinglane: 0.7741
- Validation Iou Flat-parkingdriveway: 0.3965
- Validation Iou Flat-railtrack: nan
- Validation Iou Flat-curb: 0.3812
- Validation Iou Human-person: 0.3313
- Validation Iou Human-rider: 0.0
- Validation Iou Vehicle-car: 0.7684
- 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: 0.4625
- Validation Iou Vehicle-caravan: 0.0
- Validation Iou Vehicle-cartrailer: 0.0
- Validation Iou Construction-building: 0.7518
- Validation Iou Construction-door: 0.0
- Validation Iou Construction-wall: 0.4870
- Validation Iou Construction-fenceguardrail: 0.4067
- Validation Iou Construction-bridge: 0.0
- Validation Iou Construction-tunnel: nan
- Validation Iou Construction-stairs: 0.0
- Validation Iou Object-pole: 0.2774
- Validation Iou Object-trafficsign: 0.0
- Validation Iou Object-trafficlight: 0.0
- Validation Iou Nature-vegetation: 0.8138
- Validation Iou Nature-terrain: 0.5846
- Validation Iou Sky: 0.9136
- Validation Iou Void-ground: 0.0
- Validation Iou Void-dynamic: 0.0005
- Validation Iou Void-static: 0.2057
- Validation Iou Void-unclear: 0.0
- Epoch: 4

## 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 |
|:----------:|:---------------:|:-------------------:|:------------------------:|:---------------------------:|:-----------------------------:|:-----------------------------:|:---------------------------------:|:----------------------------------:|:------------------------------------:|:----------------------------------------:|:----------------------------------:|:-----------------------------:|:--------------------------------:|:-------------------------------:|:-------------------------------:|:---------------------------------:|:-------------------------------:|:-------------------------------------:|:--------------------------------------:|:-----------------------------------:|:-----------------------------------:|:--------------------------------------:|:-----------------------------------------:|:-------------------------------------:|:-------------------------------------:|:-----------------------------------------------:|:---------------------------------------:|:---------------------------------------:|:---------------------------------------:|:-------------------------------:|:--------------------------------------:|:---------------------------------------:|:-------------------------------------:|:----------------------------------:|:-----------------------:|:-------------------------------:|:--------------------------------:|:-------------------------------:|:--------------------------------:|:------------------------:|:------------------------:|:----------------------------:|:-----------------------------:|:-------------------------------:|:-----------------------------------:|:-----------------------------:|:------------------------:|:---------------------------:|:--------------------------:|:--------------------------:|:----------------------------:|:--------------------------:|:--------------------------------:|:---------------------------------:|:------------------------------:|:------------------------------:|:---------------------------------:|:------------------------------------:|:--------------------------------:|:--------------------------------:|:------------------------------------------:|:----------------------------------:|:----------------------------------:|:----------------------------------:|:--------------------------:|:---------------------------------:|:----------------------------------:|:--------------------------------:|:-----------------------------:|:------------------:|:--------------------------:|:---------------------------:|:--------------------------:|:---------------------------:|:-----:|
| 1.4680     | 0.9066          | 0.1798              | 0.2394                   | 0.7547                      | 0.0                           | 0.8669                        | 0.8589                            | 0.0                                | 0.6786                               | 0.0989                                   | nan                                | 0.0247                        | 0.2642                           | 0.0                             | 0.8952                          | 0.0                               | 0.0                             | nan                                   | 0.0                                    | 0.0006                              | 0.0                                 | 0.0                                    | 0.7945                                    | 0.0                                   | 0.4156                                | 0.1067                                          | 0.0                                     | nan                                     | 0.0                                     | 0.0810                          | 0.0                                    | 0.0                                     | 0.9131                                | 0.7232                             | 0.9213                  | 0.0                             | 0.0                              | 0.0180                          | 0.0                              | 0.0                      | 0.4849                   | 0.7637                       | 0.0                           | 0.6063                          | 0.0951                              | nan                           | 0.0240                   | 0.1986                      | 0.0                        | 0.6356                     | 0.0                          | 0.0                        | 0.0                              | 0.0                               | 0.0006                         | 0.0                            | 0.0                               | 0.6237                               | 0.0                              | 0.3020                           | 0.0966                                     | 0.0                                | nan                                | 0.0                                | 0.0755                     | 0.0                               | 0.0                                | 0.7648                           | 0.5032                        | 0.7422             | 0.0                        | 0.0                         | 0.0170                     | 0.0                         | 0     |
| 0.8567     | 0.6646          | 0.2541              | 0.3119                   | 0.8124                      | 0.0                           | 0.8596                        | 0.9440                            | 0.5084                             | 0.6331                               | 0.3103                                   | nan                                | 0.2047                        | 0.5405                           | 0.0                             | 0.9264                          | 0.0                               | 0.0                             | nan                                   | 0.0                                    | 0.3220                              | 0.0                                 | 0.0                                    | 0.8516                                    | 0.0                                   | 0.6289                                | 0.3390                                          | 0.0                                     | nan                                     | 0.0                                     | 0.2700                          | 0.0                                    | 0.0                                     | 0.9158                                | 0.7236                             | 0.9357                  | 0.0                             | 0.0                              | 0.0672                          | 0.0                              | 0.0                      | 0.6107                   | 0.8259                       | 0.4541                        | 0.6072                          | 0.2645                              | nan                           | 0.1822                   | 0.2658                      | 0.0                        | 0.7033                     | 0.0                          | 0.0                        | nan                              | 0.0                               | 0.2866                         | 0.0                            | 0.0                               | 0.6977                               | 0.0                              | 0.3962                           | 0.2965                                     | 0.0                                | nan                                | 0.0                                | 0.2208                     | 0.0                               | 0.0                                | 0.8041                           | 0.5809                        | 0.8706             | 0.0                        | 0.0                         | 0.0630                     | 0.0                         | 1     |
| 0.7002     | 0.6058          | 0.2747              | 0.3411                   | 0.8279                      | 0.0                           | 0.8420                        | 0.9339                            | 0.5835                             | 0.7672                               | 0.4334                                   | nan                                | 0.4080                        | 0.5484                           | 0.0                             | 0.9257                          | 0.0                               | 0.0                             | nan                                   | 0.0                                    | 0.4079                              | 0.0                                 | 0.0                                    | 0.8439                                    | 0.0                                   | 0.6765                                | 0.4692                                          | 0.0                                     | nan                                     | 0.0                                     | 0.3434                          | 0.0                                    | 0.0                                     | 0.9179                                | 0.7872                             | 0.9486                  | 0.0                             | 0.0                              | 0.0798                          | 0.0                              | 0.0                      | 0.6316                   | 0.8505                       | 0.4997                        | 0.6888                          | 0.3585                              | nan                           | 0.3261                   | 0.2850                      | 0.0                        | 0.7418                     | 0.0                          | 0.0                        | nan                              | 0.0                               | 0.3474                         | 0.0                            | 0.0                               | 0.7019                               | 0.0                              | 0.3816                           | 0.3688                                     | 0.0                                | nan                                | 0.0                                | 0.2469                     | 0.0                               | 0.0                                | 0.8183                           | 0.5924                        | 0.8755             | 0.0                        | 0.0                         | 0.0744                     | 0.0                         | 2     |
| 0.6213     | 0.5759          | 0.2858              | 0.3589                   | 0.8276                      | 0.0                           | 0.8817                        | 0.8784                            | 0.7087                             | 0.8404                               | 0.5910                                   | nan                                | 0.3922                        | 0.5252                           | 0.0                             | 0.9485                          | 0.0                               | 0.0                             | nan                                   | 0.0                                    | 0.5948                              | 0.0                                 | 0.0                                    | 0.8582                                    | 0.0                                   | 0.6432                                | 0.4867                                          | 0.0                                     | nan                                     | 0.0                                     | 0.3592                          | 0.0                                    | 0.0                                     | 0.9287                                | 0.7635                             | 0.9531                  | 0.0                             | 0.0000                           | 0.1312                          | 0.0                              | 0.0                      | 0.6807                   | 0.8223                       | 0.4667                        | 0.7441                          | 0.3268                              | nan                           | 0.3356                   | 0.3185                      | 0.0                        | 0.7325                     | 0.0                          | 0.0                        | nan                              | 0.0                               | 0.4012                         | 0.0                            | 0.0                               | 0.7425                               | 0.0                              | 0.4686                           | 0.3947                                     | 0.0                                | nan                                | 0.0                                | 0.2611                     | 0.0                               | 0.0                                | 0.8176                           | 0.6067                        | 0.9076             | 0.0                        | 0.0000                      | 0.1194                     | 0.0                         | 3     |
| 0.5617     | 0.5455          | 0.2981              | 0.3694                   | 0.8400                      | 0.0                           | 0.8592                        | 0.9015                            | 0.6943                             | 0.8471                               | 0.5867                                   | nan                                | 0.4839                        | 0.5402                           | 0.0                             | 0.9318                          | 0.0                               | 0.0                             | nan                                   | 0.0                                    | 0.6756                              | 0.0                                 | 0.0                                    | 0.8796                                    | 0.0                                   | 0.6019                                | 0.5454                                          | 0.0                                     | nan                                     | 0.0                                     | 0.3915                          | 0.0                                    | 0.0                                     | 0.9456                                | 0.7224                             | 0.9630                  | 0.0                             | 0.0005                           | 0.2520                          | 0.0                              | 0.0                      | 0.6794                   | 0.8423                       | 0.4614                        | 0.7741                          | 0.3965                              | nan                           | 0.3812                   | 0.3313                      | 0.0                        | 0.7684                     | 0.0                          | 0.0                        | nan                              | 0.0                               | 0.4625                         | 0.0                            | 0.0                               | 0.7518                               | 0.0                              | 0.4870                           | 0.4067                                     | 0.0                                | nan                                | 0.0                                | 0.2774                     | 0.0                               | 0.0                                | 0.8138                           | 0.5846                        | 0.9136             | 0.0                        | 0.0005                      | 0.2057                     | 0.0                         | 4     |


### Framework versions

- Transformers 4.27.3
- TensorFlow 2.11.0
- Datasets 2.10.1
- Tokenizers 0.13.2

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

ThomasLam/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: 0.5617
* Validation Loss: 0.5455
* Validation Mean Iou: 0.2981
* Validation Mean Accuracy: 0.3694
* Validation Overall Accuracy: 0.8400
* Validation Accuracy Unlabeled: 0.0
* Validation Accuracy Flat-road: 0.8592
* Validation Accuracy Flat-sidewalk: 0.9015
* Validation Accuracy Flat-crosswalk: 0.6943
* Validation Accuracy Flat-cyclinglane: 0.8471
* Validation Accuracy Flat-parkingdriveway: 0.5867
* Validation Accuracy Flat-railtrack: nan
* Validation Accuracy Flat-curb: 0.4839
* Validation Accuracy Human-person: 0.5402
* Validation Accuracy Human-rider: 0.0
* Validation Accuracy Vehicle-car: 0.9318
* 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: 0.6756
* Validation Accuracy Vehicle-caravan: 0.0
* Validation Accuracy Vehicle-cartrailer: 0.0
* Validation Accuracy Construction-building: 0.8796
* Validation Accuracy Construction-door: 0.0
* Validation Accuracy Construction-wall: 0.6019
* Validation Accuracy Construction-fenceguardrail: 0.5454
* Validation Accuracy Construction-bridge: 0.0
* Validation Accuracy Construction-tunnel: nan
* Validation Accuracy Construction-stairs: 0.0
* Validation Accuracy Object-pole: 0.3915
* Validation Accuracy Object-trafficsign: 0.0
* Validation Accuracy Object-trafficlight: 0.0
* Validation Accuracy Nature-vegetation: 0.9456
* Validation Accuracy Nature-terrain: 0.7224
* Validation Accuracy Sky: 0.9630
* Validation Accuracy Void-ground: 0.0
* Validation Accuracy Void-dynamic: 0.0005
* Validation Accuracy Void-static: 0.2520
* Validation Accuracy Void-unclear: 0.0
* Validation Iou Unlabeled: 0.0
* Validation Iou Flat-road: 0.6794
* Validation Iou Flat-sidewalk: 0.8423
* Validation Iou Flat-crosswalk: 0.4614
* Validation Iou Flat-cyclinglane: 0.7741
* Validation Iou Flat-parkingdriveway: 0.3965
* Validation Iou Flat-railtrack: nan
* Validation Iou Flat-curb: 0.3812
* Validation Iou Human-person: 0.3313
* Validation Iou Human-rider: 0.0
* Validation Iou Vehicle-car: 0.7684
* 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: 0.4625
* Validation Iou Vehicle-caravan: 0.0
* Validation Iou Vehicle-cartrailer: 0.0
* Validation Iou Construction-building: 0.7518
* Validation Iou Construction-door: 0.0
* Validation Iou Construction-wall: 0.4870
* Validation Iou Construction-fenceguardrail: 0.4067
* Validation Iou Construction-bridge: 0.0
* Validation Iou Construction-tunnel: nan
* Validation Iou Construction-stairs: 0.0
* Validation Iou Object-pole: 0.2774
* Validation Iou Object-trafficsign: 0.0
* Validation Iou Object-trafficlight: 0.0
* Validation Iou Nature-vegetation: 0.8138
* Validation Iou Nature-terrain: 0.5846
* Validation Iou Sky: 0.9136
* Validation Iou Void-ground: 0.0
* Validation Iou Void-dynamic: 0.0005
* Validation Iou Void-static: 0.2057
* Validation Iou Void-unclear: 0.0
* Epoch: 4


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 4.27.3
* TensorFlow 2.11.0
* Datasets 2.10.1
* Tokenizers 0.13.2



### 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 4.27.3
* TensorFlow 2.11.0
* Datasets 2.10.1
* 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', '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 4.27.3
* TensorFlow 2.11.0
* Datasets 2.10.1
* 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', '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 4.27.3
* TensorFlow 2.11.0
* Datasets 2.10.1
* Tokenizers 0.13.2