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: 0.0191
  - Mean Iou: 0.3997
  - Mean Accuracy: 0.7995
  - Overall Accuracy: 0.7995
  - Accuracy Unlabeled: nan
  - Accuracy Trash: 0.7995
  - Iou Unlabeled: 0.0
  - Iou Trash: 0.7995
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:--------------:|:-------------:|:---------:|
  | 0.0748        | 1.0   | 90   | 0.0386          | 0.3630   | 0.7259        | 0.7259           | nan                | 0.7259         | 0.0           | 0.7259    |
  | 0.039         | 2.0   | 180  | 0.0242          | 0.3803   | 0.7607        | 0.7607           | nan                | 0.7607         | 0.0           | 0.7607    |
  | 0.0194        | 3.0   | 270  | 0.0242          | 0.3605   | 0.7210        | 0.7210           | nan                | 0.7210         | 0.0           | 0.7210    |
  | 0.0112        | 4.0   | 360  | 0.0205          | 0.3995   | 0.7991        | 0.7991           | nan                | 0.7991         | 0.0           | 0.7991    |
  | 0.0169        | 5.0   | 450  | 0.0192          | 0.4000   | 0.8000        | 0.8000           | nan                | 0.8000         | 0.0           | 0.8000    |
  | 0.041         | 6.0   | 540  | 0.0196          | 0.3838   | 0.7677        | 0.7677           | nan                | 0.7677         | 0.0           | 0.7677    |
  | 0.0188        | 7.0   | 630  | 0.0191          | 0.4139   | 0.8277        | 0.8277           | nan                | 0.8277         | 0.0           | 0.8277    |
  | 0.0073        | 8.0   | 720  | 0.0190          | 0.4069   | 0.8138        | 0.8138           | nan                | 0.8138         | 0.0           | 0.8138    |
  | 0.025         | 9.0   | 810  | 0.0191          | 0.4087   | 0.8174        | 0.8174           | nan                | 0.8174         | 0.0           | 0.8174    |
  | 0.006         | 10.0  | 900  | 0.0191          | 0.3997   | 0.7995        | 0.7995           | nan                | 0.7995         | 0.0           | 0.7995    |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.13.1+cu116
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  