---
license: mit
base_model: nvidia/mit-b1
tags:
- generated_from_keras_callback
model-index:
- name: slm-segformer-080823-b1
  results: []
---

<!-- 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. -->

# slm-segformer-080823-b1

This model is a fine-tuned version of [nvidia/mit-b1](https://huggingface.co/nvidia/mit-b1) on patches from [sketched boundaries](https://www.kaggle.com/datasets/aurioldegbelo/slm-boundaries) during the SmartLandMaps project.
It achieves the following results on the evaluation set:
- Train Loss: 0.0257
- Validation Loss: 0.0271
- Validation Mean Iou: 0.8583
- Validation Mean Accuracy: 0.9196
- Validation Overall Accuracy: 0.9888
- Validation Per Category Iou: [0.98849374 0.72800628]
- Validation Per Category Accuracy: [0.99410982 0.84499592]
- Epoch: 9

## 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:
- optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': 6e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Validation Mean Iou | Validation Mean Accuracy | Validation Overall Accuracy | Validation Per Category Iou | Validation Per Category Accuracy | Epoch |
|:----------:|:---------------:|:-------------------:|:------------------------:|:---------------------------:|:---------------------------:|:--------------------------------:|:-----:|
| 0.1099     | 0.0958          | 0.8134              | 0.9461                   | 0.9824                      | [0.98176563 0.64502586]     | [0.98511039 0.90705184]          | 0     |
| 0.0478     | 0.0523          | 0.8440              | 0.9449                   | 0.9865                      | [0.9860406 0.7019479]       | [0.98964683 0.90022015]          | 1     |
| 0.0379     | 0.0409          | 0.8476              | 0.9325                   | 0.9873                      | [0.98687303 0.70826431]     | [0.99144882 0.87350047]          | 2     |
| 0.0336     | 0.0331          | 0.8551              | 0.9394                   | 0.9880                      | [0.98757544 0.72269531]     | [0.99166337 0.88706795]          | 3     |
| 0.0310     | 0.0329          | 0.8541              | 0.9426                   | 0.9878                      | [0.98735586 0.72081351]     | [0.99118853 0.89409615]          | 4     |
| 0.0292     | 0.0317          | 0.8516              | 0.9348                   | 0.9877                      | [0.98729336 0.71599644]     | [0.99171219 0.87789181]          | 5     |
| 0.0282     | 0.0296          | 0.8572              | 0.9336                   | 0.9884                      | [0.98798391 0.72647977]     | [0.99252058 0.87472321]          | 6     |
| 0.0271     | 0.0319          | 0.8476              | 0.9253                   | 0.9875                      | [0.98709267 0.70802268]     | [0.99221744 0.85835533]          | 7     |
| 0.0267     | 0.0295          | 0.8549              | 0.9298                   | 0.9882                      | [0.98782022 0.72192985]     | [0.9926388  0.86691624]          | 8     |
| 0.0257     | 0.0271          | 0.8583              | 0.9196                   | 0.9888                      | [0.98849374 0.72800628]     | [0.99410982 0.84499592]          | 9     |


### Framework versions

- Transformers 4.31.0
- TensorFlow 2.12.0
- Tokenizers 0.13.3