---
license: other
base_model: nvidia/segformer-b0-finetuned-ade-512-512
tags:
- generated_from_keras_callback
model-index:
- name: Segformer-MRIseg_Sep
  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_Sep

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: 0.0026
- Validation Loss: 0.0116
- 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 |
|:----------:|:---------------:|:-----:|
| 0.1563     | 0.0558          | 0     |
| 0.0488     | 0.0706          | 1     |
| 0.0290     | 0.0230          | 2     |
| 0.0207     | 0.0160          | 3     |
| 0.0164     | 0.0145          | 4     |
| 0.0136     | 0.0133          | 5     |
| 0.0117     | 0.0136          | 6     |
| 0.0106     | 0.0144          | 7     |
| 0.0104     | 0.0147          | 8     |
| 0.0091     | 0.0109          | 9     |
| 0.0078     | 0.0104          | 10    |
| 0.0071     | 0.0108          | 11    |
| 0.0067     | 0.0101          | 12    |
| 0.0064     | 0.0110          | 13    |
| 0.0058     | 0.0096          | 14    |
| 0.0057     | 0.0101          | 15    |
| 0.0055     | 0.0115          | 16    |
| 0.0055     | 0.0109          | 17    |
| 0.0051     | 0.0098          | 18    |
| 0.0051     | 0.0108          | 19    |
| 0.0048     | 0.0097          | 20    |
| 0.0050     | 0.0097          | 21    |
| 0.0047     | 0.0088          | 22    |
| 0.0045     | 0.0110          | 23    |
| 0.0043     | 0.0098          | 24    |
| 0.0041     | 0.0098          | 25    |
| 0.0041     | 0.0126          | 26    |
| 0.0040     | 0.0125          | 27    |
| 0.0042     | 0.0098          | 28    |
| 0.0039     | 0.0109          | 29    |
| 0.0037     | 0.0096          | 30    |
| 0.0038     | 0.0104          | 31    |
| 0.0036     | 0.0103          | 32    |
| 0.0034     | 0.0100          | 33    |
| 0.0033     | 0.0099          | 34    |
| 0.0038     | 0.0100          | 35    |
| 0.0036     | 0.0111          | 36    |
| 0.0036     | 0.0158          | 37    |
| 0.0034     | 0.0104          | 38    |
| 0.0032     | 0.0100          | 39    |
| 0.0030     | 0.0100          | 40    |
| 0.0030     | 0.0099          | 41    |
| 0.0029     | 0.0098          | 42    |
| 0.0028     | 0.0112          | 43    |
| 0.0030     | 0.0105          | 44    |
| 0.0029     | 0.0104          | 45    |
| 0.0029     | 0.0100          | 46    |
| 0.0027     | 0.0119          | 47    |
| 0.0030     | 0.0119          | 48    |
| 0.0028     | 0.0109          | 49    |
| 0.0029     | 0.0106          | 50    |
| 0.0027     | 0.0111          | 51    |
| 0.0027     | 0.0111          | 52    |
| 0.0027     | 0.0132          | 53    |
| 0.0029     | 0.0105          | 54    |
| 0.0026     | 0.0113          | 55    |
| 0.0027     | 0.0108          | 56    |
| 0.0025     | 0.0112          | 57    |
| 0.0025     | 0.0105          | 58    |
| 0.0026     | 0.0116          | 59    |


### Framework versions

- Transformers 4.31.0
- TensorFlow 2.13.0
- Datasets 2.14.5
- Tokenizers 0.13.3