readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  - vision
  - image-segmentation
  datasets:
  - segments/sidewalk-semantic
  widget:
  - src: https://segmentsai-prod.s3.eu-west-2.amazonaws.com/assets/admin-tobias/439f6843-80c5-47ce-9b17-0b2a1d54dbeb.jpg
    example_title: Brugge
  model-index:
  - name: segformer-b3-finetuned-segments-sidewalk
    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-b3-finetuned-segments-sidewalk
  
  This model is a fine-tuned version of [nvidia/mit-b3](https://huggingface.co/nvidia/mit-b3) on the [`sidewalk-semantic`](https://huggingface.co/datasets/segments/sidewalk-semantic) dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.8527
  - Miou: 0.4345
  - Macc: 0.5079
  - Overall Accuracy: 0.8871
  - Per Category Iou: [nan, 0.8382620833593052, 0.8876413942052827, 0.6261839847460975, 0.6590417473673477, 0.48228357004057837, 0.0, 0.6202905105623743, 0.748344409080285, 0.39096811362981676, 0.8848513296576286, 0.2415092028297553, 0.0, 0.07068982339740462, 0.41356382978723405, 0.6474134903246308, 0.0, 0.3062052505966587, 0.7704161510118073, 0.16108765491481541, 0.49752934863906867, 0.4734664813860761, 0.09820294554789893, nan, 0.17153699720635862, 0.514555863370054, 0.4660696051735875, 0.08826901031715705, 0.8991007829081079, 0.829742650939299, 0.9612781430019607, 0.01112666737555973, 0.1861992251927429, 0.391388886866003, 0.0]
  - Per Category Accuracy: [nan, 0.9255583122183136, 0.9555184973850358, 0.8927561553139153, 0.7130378697969978, 0.6275811980710011, 0.0, 0.7474676455043131, 0.8545937449541465, 0.43523520560447965, 0.9672661630501664, 0.28627436744473084, 0.0, 0.0707036205718747, 0.47675012774655084, 0.7689381524189783, 0.0, 0.31600985221674877, 0.9278457312029238, 0.2055231456928555, 0.6363063556709445, 0.5255962863991213, 0.10240946878962942, nan, 0.30514996921453075, 0.6575213496395762, 0.6054551483999336, 0.08830275229357798, 0.9550074747938649, 0.8984159398975186, 0.9823971352874257, 0.013025497748978224, 0.3256981066248004, 0.49491941043060034, 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: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 200
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Miou   | Macc   | Overall Accuracy | Per Category Iou                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                       | Per Category Accuracy                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           |
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