readme: ---
  license: other
  tags:
  - vision
  - image-segmentation
  - generated_from_trainer
  model-index:
  - name: segformer-b0-finetuned-segments-trash-3
    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-trash-3
  
  This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the mraottth/excluding_ebo_town dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.3332
  - Mean Iou: 0.1637
  - Mean Accuracy: 0.2781
  - Overall Accuracy: 0.7488
  - Accuracy Unlabeled: nan
  - Accuracy Trash: 0.8344
  - Accuracy Litter: 0.0
  - Accuracy Building: nan
  - Accuracy Vegetation: nan
  - Accuracy Burnpit: 0.0
  - Accuracy Construction: nan
  - Iou Unlabeled: 0.0
  - Iou Trash: 0.8186
  - Iou Litter: 0.0
  - Iou Building: nan
  - Iou Vegetation: nan
  - Iou Burnpit: 0.0
  - Iou Construction: 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: 4
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Unlabeled | Accuracy Trash | Accuracy Litter | Accuracy Building | Accuracy Vegetation | Accuracy Burnpit | Accuracy Construction | Iou Unlabeled | Iou Trash | Iou Litter | Iou Building | Iou Vegetation | Iou Burnpit | Iou Construction |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:--------------:|:---------------:|:-----------------:|:-------------------:|:----------------:|:---------------------:|:-------------:|:---------:|:----------:|:------------:|:--------------:|:-----------:|:----------------:|
  | 1.8754        | 0.77  | 20   | 1.8873          | 0.1243   | 0.3109        | 0.8369           | nan                | 0.9326         | 0.0             | nan               | nan                 | 0.0              | nan                   | 0.0           | 0.8702    | 0.0        | 0.0          | 0.0            | 0.0         | 0.0              |
  | 1.7266        | 1.54  | 40   | 1.6986          | 0.1408   | 0.2930        | 0.7889           | nan                | 0.8791         | 0.0             | nan               | nan                 | 0.0              | nan                   | 0.0           | 0.8446    | 0.0        | 0.0          | nan            | 0.0         | 0.0              |
  | 1.4768        | 2.31  | 60   | 1.4567          | 0.1631   | 0.2801        | 0.7540           | nan                | 0.8402         | 0.0             | nan               | nan                 | 0.0              | nan                   | 0.0           | 0.8153    | 0.0        | nan          | nan            | 0.0         | 0.0              |
  | 1.5189        | 3.08  | 80   | 1.3385          | 0.1648   | 0.2800        | 0.7538           | nan                | 0.8400         | 0.0             | nan               | nan                 | 0.0              | nan                   | 0.0           | 0.8239    | 0.0        | nan          | nan            | 0.0         | 0.0              |
  | 1.503         | 3.85  | 100  | 1.3332          | 0.1637   | 0.2781        | 0.7488           | nan                | 0.8344         | 0.0             | nan               | nan                 | 0.0              | nan                   | 0.0           | 0.8186    | 0.0        | nan          | nan            | 0.0         | 0.0              |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.1+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  