readme: ---
  license: other
  tags:
  - generated_from_trainer
  model-index:
  - name: nvidia-segformer-b0-finetuned-ade-512-512-finetuned-ISIC17
    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. -->
  
  # nvidia-segformer-b0-finetuned-ade-512-512-finetuned-ISIC17
  
  This model is a fine-tuned version of [nvidia/segformer-b0-finetuned-ade-512-512](https://huggingface.co/nvidia/segformer-b0-finetuned-ade-512-512) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1948
  - Mean Iou: 0.8064
  - Mean Accuracy: 0.8726
  - Overall Accuracy: 0.9381
  - Per Category Iou: [0.6841604127643356, 0.9285439643646547]
  - Per Category Accuracy: [0.7721651141608432, 0.9729809595315688]
  
  ## 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: 3e-05
  - train_batch_size: 32
  - eval_batch_size: 32
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 3
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Per Category Iou                         | Per Category Accuracy                     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:----------------------------------------:|:-----------------------------------------:|
  | 0.481         | 0.16  | 10   | 0.4235          | 0.6191   | 0.6970        | 0.8761           | [0.3719409076673884, 0.8662862424406493] | [0.42270204900152314, 0.9713331864930521] |
  | 0.4147        | 0.32  | 20   | 0.3894          | 0.7067   | 0.8502        | 0.8853           | [0.5464942438498753, 0.8668431573745645] | [0.7965579529885418, 0.9038859083170013]  |
  | 0.356         | 0.48  | 30   | 0.3148          | 0.7467   | 0.8513        | 0.9107           | [0.5963581593534901, 0.897077797385972]  | [0.7603709174964982, 0.9422313184595918]  |
  | 0.3039        | 0.63  | 40   | 0.3024          | 0.7620   | 0.8671        | 0.9162           | [0.6211722830632663, 0.9028139512386881] | [0.7918407335685692, 0.9422883932404167]  |
  | 0.2545        | 0.79  | 50   | 0.2849          | 0.7766   | 0.8898        | 0.9201           | [0.6468577863419183, 0.9063792530493855] | [0.8432862096150755, 0.9362151542385662]  |
  | 0.2635        | 0.95  | 60   | 0.2504          | 0.7828   | 0.8644        | 0.9279           | [0.6487213857926865, 0.9168129696986418] | [0.7671470887645524, 0.9616549114054705]  |
  | 0.2175        | 1.11  | 70   | 0.2497          | 0.7849   | 0.8682        | 0.9283           | [0.6526705030304356, 0.9171225024239068] | [0.7762677096648272, 0.9602225755678137]  |
  | 0.2025        | 1.27  | 80   | 0.2400          | 0.7840   | 0.8632        | 0.9288           | [0.6501844204669202, 0.9178944798865282] | [0.7627291445016801, 0.9636411137781736]  |
  | 0.2035        | 1.43  | 90   | 0.2288          | 0.7931   | 0.8749        | 0.9313           | [0.6657367286733036, 0.9203778068784213] | [0.7885027822639286, 0.9612655167036179]  |
  | 0.2488        | 1.59  | 100  | 0.2110          | 0.7978   | 0.8719        | 0.9341           | [0.6717638717220313, 0.923859975121704]  | [0.7766611302038285, 0.9672003292652145]  |
  | 0.1954        | 1.75  | 110  | 0.2067          | 0.7962   | 0.8597        | 0.9354           | [0.666599427783381, 0.9258672754383861]  | [0.7436428904928473, 0.9757231213956472]  |
  | 0.1806        | 1.9   | 120  | 0.2047          | 0.7926   | 0.8525        | 0.9349           | [0.6596059897565958, 0.925563006736469]  | [0.726197674685608, 0.9787940661520825]   |
  | 0.161         | 2.06  | 130  | 0.2047          | 0.7903   | 0.8505        | 0.9342           | [0.6558737849234609, 0.9247714617107691] | [0.7223974159771602, 0.9786951901233297]  |
  | 0.1736        | 2.22  | 140  | 0.2023          | 0.7948   | 0.8588        | 0.9349           | [0.6643652721485811, 0.9252950591002775] | [0.742124317828686, 0.9754152391272543]   |
  | 0.1947        | 2.38  | 150  | 0.2077          | 0.7985   | 0.8656        | 0.9355           | [0.6712414223331253, 0.9257326708494226] | [0.7585178608332249, 0.9726888331181641]  |
  | 0.1464        | 2.54  | 160  | 0.1960          | 0.8030   | 0.8680        | 0.9373           | [0.678274892507806, 0.9276935390097538]  | [0.7620104248788739, 0.9740685958478499]  |
  | 0.1644        | 2.7   | 170  | 0.1964          | 0.8064   | 0.8751        | 0.9377           | [0.6847175060674714, 0.9279857318627613] | [0.7791196258677832, 0.9710404169835255]  |
  | 0.1803        | 2.86  | 180  | 0.1948          | 0.8064   | 0.8726        | 0.9381           | [0.6841604127643356, 0.9285439643646547] | [0.7721651141608432, 0.9729809595315688]  |
  
  
  ###