readme: ---
  license: apache-2.0
  tags:
  - generated_from_keras_callback
  - vision
  - image-segmentation
  model-index:
  - name: mit-b0-finetuned-sidewalk-semantic
    results: []
  datasets:
  - segments/sidewalk-semantic
  ---
  
  <!-- This model card has been generated automatically according to the information Keras had access to. You should
  probably proofread and complete it, then remove this comment. -->
  
  # mit-b0-finetuned-sidewalk-semantic
  
  This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Train Loss: 0.2125
  - Validation Loss: 0.5151
  - Epoch: 49
  
  ## Model description
  
  The model was fine-tuned from [this model](https://huggingface.co/nvidia/mit-b0). More information about the model is available
  [here](https://huggingface.co/docs/transformers/model_doc/segformer).
  
  ## Intended uses & limitations
  
  This fine-tuned model is just for demonstration purposes. Before using it in production, it should be thoroughly inspected and adjusted
  if needed. 
  
  ## Training and evaluation data
  
  [`segments/sidewalk-semantic`](https://huggingface.co/datasets/segments/sidewalk-semantic)
  
  ## Training procedure
  
  More information is available here: [deep-diver/segformer-tf-transformers](https://github.com/deep-diver/segformer-tf-transformers).
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - optimizer: {'name': 'Adam', 'learning_rate': 6e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
  - training_precision: float32
  
  ### Training results
  
  | Train Loss | Validation Loss | Epoch |
  |:----------:|:---------------:|:-----:|
  | 2.0785     | 1.1753          | 0     |
  | 1.1312     | 0.8807          | 1     |
  | 0.9315     | 0.7585          | 2     |
  | 0.7952     | 0.7261          | 3     |
  | 0.7273     | 0.6701          | 4     |
  | 0.6603     | 0.6396          | 5     |
  | 0.6198     | 0.6238          | 6     |
  | 0.5958     | 0.5925          | 7     |
  | 0.5378     | 0.5714          | 8     |
  | 0.5236     | 0.5786          | 9     |
  | 0.4960     | 0.5588          | 10    |
  | 0.4633     | 0.5624          | 11    |
  | 0.4562     | 0.5450          | 12    |
  | 0.4167     | 0.5438          | 13    |
  | 0.4100     | 0.5248          | 14    |
  | 0.3947     | 0.5354          | 15    |
  | 0.3867     | 0.5069          | 16    |
  | 0.3803     | 0.5285          | 17    |
  | 0.3696     | 0.5318          | 18    |
  | 0.3386     | 0.5162          | 19    |
  | 0.3349     | 0.5312          | 20    |
  | 0.3233     | 0.5304          | 21    |
  | 0.3328     | 0.5178          | 22    |
  | 0.3140     | 0.5131          | 23    |
  | 0.3081     | 0.5049          | 24    |
  | 0.3046     | 0.5011          | 25    |
  | 0.3209     | 0.5197          | 26    |
  | 0.2966     | 0.5151          | 27    |
  | 0.2829     | 0.5166          | 28    |
  | 0.2968     | 0.5210          | 29    |
  | 0.2818     | 0.5300          | 30    |
  | 0.2739     | 0.5221          | 31    |
  | 0.2602     | 0.5340          | 32    |
  | 0.2570     | 0.5124          | 33    |
  | 0.2557     | 0.5234          | 34    |
  | 0.2593     | 0.5098          | 35    |
  | 0.2582     | 0.5329          | 36    |
  | 0.2439     | 0.5373          | 37    |
  | 0.2413     | 0.5141          | 38    |
  | 0.2423     | 0.5210          | 39    |
  | 0.2340     | 0.5043          | 40    |
  | 0.2244     | 0.5300          | 41    |
  | 0.2246     | 0.4978          | 42    |
  | 0.2270     | 0.5385          | 43    |
  | 0.2254     | 0.5125          | 44    |
  | 0.2176     | 0.5510          | 45    |
  | 0.2194     | 0.5384          | 46    |
  | 0.2136     | 0.5186          | 47    |
  | 0.2121     | 0.5356          | 48    |
  | 0.2125     | 0.5151          | 49    |
  
  
  ### Framework versions
  
  - Transformers 4.21.0.dev0
  - TensorFlow 2.8.0
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  