---
license: other
base_model: nvidia/segformer-b0-finetuned-ade-512-512
tags:
- generated_from_keras_callback
model-index:
- name: Segformer-MRIseg_model
  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. -->

# Segformer-MRIseg_model

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 an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0049
- Validation Loss: 0.0133
- Epoch: 59

## 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': 0.001, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 0.2537     | 0.0685          | 0     |
| 0.0849     | 0.0639          | 1     |
| 0.0664     | 0.0532          | 2     |
| 0.0580     | 0.0503          | 3     |
| 0.0536     | 0.0497          | 4     |
| 0.0476     | 0.0396          | 5     |
| 0.0437     | 0.0477          | 6     |
| 0.0359     | 0.0397          | 7     |
| 0.0312     | 0.0289          | 8     |
| 0.0256     | 0.0322          | 9     |
| 0.0241     | 0.0279          | 10    |
| 0.0220     | 0.0229          | 11    |
| 0.0180     | 0.0226          | 12    |
| 0.0160     | 0.0192          | 13    |
| 0.0165     | 0.0227          | 14    |
| 0.0151     | 0.0194          | 15    |
| 0.0146     | 0.0184          | 16    |
| 0.0132     | 0.0177          | 17    |
| 0.0121     | 0.0211          | 18    |
| 0.0111     | 0.0197          | 19    |
| 0.0107     | 0.0175          | 20    |
| 0.0116     | 0.0131          | 21    |
| 0.0115     | 0.0181          | 22    |
| 0.0094     | 0.0153          | 23    |
| 0.0099     | 0.0140          | 24    |
| 0.0098     | 0.0151          | 25    |
| 0.0084     | 0.0126          | 26    |
| 0.0080     | 0.0140          | 27    |
| 0.0071     | 0.0128          | 28    |
| 0.0067     | 0.0169          | 29    |
| 0.0061     | 0.0131          | 30    |
| 0.0063     | 0.0207          | 31    |
| 0.0067     | 0.0129          | 32    |
| 0.0062     | 0.0152          | 33    |
| 0.0056     | 0.0148          | 34    |
| 0.0056     | 0.0171          | 35    |
| 0.0051     | 0.0154          | 36    |
| 0.0049     | 0.0172          | 37    |
| 0.0049     | 0.0180          | 38    |
| 0.0056     | 0.0168          | 39    |
| 0.0050     | 0.0142          | 40    |
| 0.0048     | 0.0165          | 41    |
| 0.0051     | 0.0195          | 42    |
| 0.0048     | 0.0232          | 43    |
| 0.0042     | 0.0208          | 44    |
| 0.0041     | 0.0249          | 45    |
| 0.0044     | 0.0220          | 46    |
| 0.0041     | 0.0234          | 47    |
| 0.0042     | 0.0198          | 48    |
| 0.0040     | 0.0282          | 49    |
| 0.0039     | 0.0251          | 50    |
| 0.0039     | 0.0302          | 51    |
| 0.0041     | 0.0219          | 52    |
| 0.0040     | 0.0187          | 53    |
| 0.0039     | 0.0203          | 54    |
| 0.0043     | 0.0180          | 55    |
| 0.0051     | 0.0150          | 56    |
| 0.0079     | 0.0205          | 57    |
| 0.0052     | 0.0152          | 58    |
| 0.0049     | 0.0133          | 59    |


### Framework versions

- Transformers 4.31.0
- TensorFlow 2.12.0
- Datasets 2.14.4
- Tokenizers 0.13.3