---
license: other
base_model: nvidia/segformer-b0-finetuned-ade-512-512
tags:
- generated_from_keras_callback
model-index:
- name: akar49/MRI_segmentation-1
  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. -->

# akar49/MRI_segmentation-1

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: 0.0034
- Validation Loss: 0.0098
- 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 |
|:----------:|:---------------:|:-----:|
| 0.3300     | 0.0731          | 0     |
| 0.0881     | 0.0651          | 1     |
| 0.0660     | 0.0632          | 2     |
| 0.0573     | 0.0463          | 3     |
| 0.0525     | 0.0495          | 4     |
| 0.0475     | 0.0431          | 5     |
| 0.0379     | 0.0367          | 6     |
| 0.0318     | 0.0319          | 7     |
| 0.0280     | 0.0260          | 8     |
| 0.0246     | 0.0253          | 9     |
| 0.0235     | 0.0267          | 10    |
| 0.0205     | 0.0205          | 11    |
| 0.0182     | 0.0227          | 12    |
| 0.0182     | 0.0234          | 13    |
| 0.0169     | 0.0197          | 14    |
| 0.0163     | 0.0200          | 15    |
| 0.0173     | 0.0192          | 16    |
| 0.0130     | 0.0179          | 17    |
| 0.0123     | 0.0123          | 18    |
| 0.0103     | 0.0137          | 19    |
| 0.0098     | 0.0121          | 20    |
| 0.0114     | 0.0115          | 21    |
| 0.0097     | 0.0116          | 22    |
| 0.0083     | 0.0108          | 23    |
| 0.0078     | 0.0116          | 24    |
| 0.0074     | 0.0102          | 25    |
| 0.0071     | 0.0121          | 26    |
| 0.0073     | 0.0104          | 27    |
| 0.0071     | 0.0128          | 28    |
| 0.0066     | 0.0110          | 29    |
| 0.0061     | 0.0103          | 30    |
| 0.0067     | 0.0115          | 31    |
| 0.0071     | 0.0246          | 32    |
| 0.0091     | 0.0106          | 33    |
| 0.0079     | 0.0107          | 34    |
| 0.0066     | 0.0109          | 35    |
| 0.0059     | 0.0104          | 36    |
| 0.0057     | 0.0092          | 37    |
| 0.0055     | 0.0096          | 38    |
| 0.0052     | 0.0099          | 39    |
| 0.0051     | 0.0102          | 40    |
| 0.0057     | 0.0108          | 41    |
| 0.0049     | 0.0097          | 42    |
| 0.0048     | 0.0093          | 43    |
| 0.0047     | 0.0095          | 44    |
| 0.0045     | 0.0115          | 45    |
| 0.0047     | 0.0114          | 46    |
| 0.0048     | 0.0105          | 47    |
| 0.0049     | 0.0093          | 48    |
| 0.0050     | 0.0093          | 49    |
| 0.0044     | 0.0097          | 50    |
| 0.0040     | 0.0101          | 51    |
| 0.0041     | 0.0098          | 52    |
| 0.0041     | 0.0099          | 53    |
| 0.0039     | 0.0109          | 54    |
| 0.0040     | 0.0099          | 55    |
| 0.0038     | 0.0112          | 56    |
| 0.0037     | 0.0096          | 57    |
| 0.0035     | 0.0106          | 58    |
| 0.0034     | 0.0098          | 59    |


### Framework versions

- Transformers 4.31.0
- TensorFlow 2.12.0
- Datasets 2.14.2
- Tokenizers 0.13.3