---
license: other
base_model: nvidia/segformer-b0-finetuned-ade-512-512
tags:
- generated_from_keras_callback
model-index:
- name: Segformer-MRIseg_model_Mar24
  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_Mar24

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: 0.0037
- Validation Loss: 0.0081
- 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 |
|:----------:|:---------------:|:-----:|
| 0.5861     | 0.0929          | 0     |
| 0.0953     | 0.0606          | 1     |
| 0.0509     | 0.0350          | 2     |
| 0.0308     | 0.0231          | 3     |
| 0.0253     | 0.0219          | 4     |
| 0.0202     | 0.0179          | 5     |
| 0.0162     | 0.0184          | 6     |
| 0.0152     | 0.0188          | 7     |
| 0.0135     | 0.0157          | 8     |
| 0.0119     | 0.0170          | 9     |
| 0.0110     | 0.0150          | 10    |
| 0.0102     | 0.0157          | 11    |
| 0.0097     | 0.0137          | 12    |
| 0.0095     | 0.0141          | 13    |
| 0.0087     | 0.0118          | 14    |
| 0.0079     | 0.0116          | 15    |
| 0.0075     | 0.0119          | 16    |
| 0.0072     | 0.0109          | 17    |
| 0.0069     | 0.0118          | 18    |
| 0.0068     | 0.0104          | 19    |
| 0.0065     | 0.0108          | 20    |
| 0.0064     | 0.0124          | 21    |
| 0.0062     | 0.0095          | 22    |
| 0.0058     | 0.0111          | 23    |
| 0.0058     | 0.0094          | 24    |
| 0.0056     | 0.0111          | 25    |
| 0.0055     | 0.0125          | 26    |
| 0.0057     | 0.0104          | 27    |
| 0.0053     | 0.0096          | 28    |
| 0.0051     | 0.0105          | 29    |
| 0.0050     | 0.0103          | 30    |
| 0.0048     | 0.0091          | 31    |
| 0.0047     | 0.0097          | 32    |
| 0.0044     | 0.0094          | 33    |
| 0.0045     | 0.0092          | 34    |
| 0.0045     | 0.0093          | 35    |
| 0.0047     | 0.0088          | 36    |
| 0.0048     | 0.0089          | 37    |
| 0.0045     | 0.0108          | 38    |
| 0.0043     | 0.0088          | 39    |
| 0.0043     | 0.0090          | 40    |
| 0.0044     | 0.0106          | 41    |
| 0.0053     | 0.0100          | 42    |
| 0.0051     | 0.0102          | 43    |
| 0.0044     | 0.0097          | 44    |
| 0.0039     | 0.0088          | 45    |
| 0.0040     | 0.0097          | 46    |
| 0.0040     | 0.0089          | 47    |
| 0.0037     | 0.0095          | 48    |
| 0.0034     | 0.0085          | 49    |
| 0.0041     | 0.0082          | 50    |
| 0.0054     | 0.0098          | 51    |
| 0.0053     | 0.0085          | 52    |
| 0.0044     | 0.0086          | 53    |
| 0.0040     | 0.0082          | 54    |
| 0.0038     | 0.0082          | 55    |
| 0.0035     | 0.0092          | 56    |
| 0.0034     | 0.0090          | 57    |
| 0.0035     | 0.0079          | 58    |
| 0.0037     | 0.0081          | 59    |


### Framework versions

- Transformers 4.38.1
- TensorFlow 2.15.0
- Datasets 2.18.0
- Tokenizers 0.15.2