readme: ---
  license: other
  tags:
  - vision
  - image-segmentation
  - generated_from_trainer
  model-index:
  - name: trashbot
    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. -->
  
  # trashbot
  
  This model is a fine-tuned version of [nvidia/mit-b5](https://huggingface.co/nvidia/mit-b5) on the mraottth/all_locations_pooled dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0189
  - Mean Iou: 0.4050
  - Mean Accuracy: 0.8101
  - Overall Accuracy: 0.8101
  - Accuracy Unlabeled: nan
  - Accuracy Trash: 0.8101
  - Iou Unlabeled: 0.0
  - Iou Trash: 0.8101
  
  ## 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: 3
  - eval_batch_size: 3
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Unlabeled | Accuracy Trash | Iou Unlabeled | Iou Trash |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:--------------:|:-------------:|:---------:|
  | 0.0592        | 1.0   | 90   | 0.0387          | 0.3723   | 0.7446        | 0.7446           | nan                | 0.7446         | 0.0           | 0.7446    |
  | 0.0402        | 2.0   | 180  | 0.0281          | 0.4123   | 0.8247        | 0.8247           | nan                | 0.8247         | 0.0           | 0.8247    |
  | 0.0209        | 3.0   | 270  | 0.0246          | 0.3691   | 0.7382        | 0.7382           | nan                | 0.7382         | 0.0           | 0.7382    |
  | 0.0117        | 4.0   | 360  | 0.0210          | 0.3882   | 0.7763        | 0.7763           | nan                | 0.7763         | 0.0           | 0.7763    |
  | 0.019         | 5.0   | 450  | 0.0198          | 0.3822   | 0.7644        | 0.7644           | nan                | 0.7644         | 0.0           | 0.7644    |
  | 0.0445        | 6.0   | 540  | 0.0199          | 0.3771   | 0.7542        | 0.7542           | nan                | 0.7542         | 0.0           | 0.7542    |
  | 0.0195        | 7.0   | 630  | 0.0191          | 0.4177   | 0.8354        | 0.8354           | nan                | 0.8354         | 0.0           | 0.8354    |
  | 0.008         | 8.0   | 720  | 0.0191          | 0.4060   | 0.8119        | 0.8119           | nan                | 0.8119         | 0.0           | 0.8119    |
  | 0.0268        | 9.0   | 810  | 0.0188          | 0.4083   | 0.8166        | 0.8166           | nan                | 0.8166         | 0.0           | 0.8166    |
  | 0.0061        | 10.0  | 900  | 0.0189          | 0.4050   | 0.8101        | 0.8101           | nan                | 0.8101         | 0.0           | 0.8101    |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.13.1+cu116
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  