readme: ---
  license: other
  tags:
  - vision
  - image-segmentation
  - generated_from_trainer
  model-index:
  - name: segformer-b0-finetuned-segments-sidewalk-2
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # segformer-b0-finetuned-segments-sidewalk-2
  
  This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the segments/sidewalk-semantic dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.9042
  - Mean Iou: 0.1600
  - Mean Accuracy: 0.1997
  - Overall Accuracy: 0.7338
  - Per Category Iou: [nan, 0.27359520957005035, 0.6563592089876799, 0.0, 0.23344374046535918, 0.0, nan, 0.0, 0.0, 0.0, 0.5539341917024321, nan, nan, nan, nan, 0.0, 0.0, nan, 0.6213519498256361, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.8012808797206368, 0.0, 0.8609473035107046, nan, 0.0, 0.0, 0.0]
  - Per Category Accuracy: [nan, 0.38598740280061317, 0.9344800917343116, 0.0, 0.23402267811135147, 0.0, nan, 0.0, 0.0, 0.0, 0.6574569071869553, nan, nan, nan, nan, 0.0, 0.0, nan, 0.889953470705536, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.9339123774958169, 0.0, 0.9562267789312698, nan, 0.0, 0.0, 0.0]
  
  ## 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:
  - learning_rate: 6e-05
  - train_batch_size: 2
  - eval_batch_size: 2
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 2
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Per Category Iou                                                                                                                                                                                                                                                                                                                               | Per Category Accuracy                                                                                                                                                                                                                                                                                                                         |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
  | 2.8419        | 0.42  | 20   | 3.2243          | 0.1239   | 0.1973        | 0.6992           | [0.0, 0.221283072298205, 0.6482498250140304, 0.0, 0.36607695456244177, 0.013827775204570018, nan, 1.0254201659129828e-05, 0.0, 0.0, 0.5416500682753081, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.5339731316050166, 0.0, 0.0006440571922786744, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.7498440701547007, 0.0, 0.7659222854515146, 0.0, 0.0, 0.0, 0.0] | [nan, 0.3346613609105567, 0.8582083544770268, 0.0, 0.5101472837243907, 0.015482685970504024, nan, 1.0366454154356502e-05, 0.0, 0.0, 0.6745826026281508, nan, nan, nan, nan, 0.0, 0.0, nan, 0.8093545247364923, 0.0, 0.0006458279514337381, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.9324806212895075, 0.0, 0.797418357423677, nan, 0.0, 0.0, 0.0] |
  | 2.3662        | 0.83  | 40   | 2.5147          | 0.1402   | 0.1798        | 0.6989           | [nan, 0.19549119549985344, 0.6036027201962391, 0.0, 0.0019222772099991463, 0.000300503343099692, nan, 0.0, 0.0, 0.0, 0.47853978429259575, nan, nan, nan, nan, 0.0, 0.0, nan, 0.5820555774612892, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.7898452112422248, 0.0, 0.8521568687502872, nan, 0.0, 0.0, 0.0]                                 | [nan, 0.25107981668136076, 0.9396577375184628, 0.0, 0.0019233683746435017, 0.0003025228242666523, nan, 0.0, 0.0, 0.0, 0.5513810659584686, nan, nan, nan, nan, 0.0, 0.0, nan, 0.8953553793561865, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.9300976130892274, 0.0, 0.9250758451014455, nan, 0.0, 0.0, 0.0]                                |
  | 2.1745        | 1.25  | 60   | 2.0428          | 0.1485   | 0.1882        | 0.7162           | [nan, 0.24240648716131, 0.6262941164542789, 0.0, 0.044408460905