---
license: other
base_model: nvidia/segformer-b0-finetuned-ade-512-512
tags:
- generated_from_keras_callback
model-index:
- name: Segformer-MRIseg_model_Dec28
  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_Dec28

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: 0.0035
- Validation Loss: 0.0096
- 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 |
|:----------:|:---------------:|:-----:|
| 0.1321     | 0.0670          | 0     |
| 0.0670     | 0.0541          | 1     |
| 0.0551     | 0.0481          | 2     |
| 0.0455     | 0.0458          | 3     |
| 0.0393     | 0.0377          | 4     |
| 0.0335     | 0.0329          | 5     |
| 0.0316     | 0.0322          | 6     |
| 0.0269     | 0.0255          | 7     |
| 0.0218     | 0.0249          | 8     |
| 0.0204     | 0.0187          | 9     |
| 0.0182     | 0.0231          | 10    |
| 0.0186     | 0.0244          | 11    |
| 0.0166     | 0.0175          | 12    |
| 0.0150     | 0.0157          | 13    |
| 0.0132     | 0.0163          | 14    |
| 0.0123     | 0.0161          | 15    |
| 0.0111     | 0.0147          | 16    |
| 0.0112     | 0.0231          | 17    |
| 0.0122     | 0.0145          | 18    |
| 0.0101     | 0.0134          | 19    |
| 0.0094     | 0.0122          | 20    |
| 0.0088     | 0.0117          | 21    |
| 0.0080     | 0.0128          | 22    |
| 0.0082     | 0.0140          | 23    |
| 0.0074     | 0.0125          | 24    |
| 0.0073     | 0.0110          | 25    |
| 0.0071     | 0.0107          | 26    |
| 0.0065     | 0.0111          | 27    |
| 0.0073     | 0.0109          | 28    |
| 0.0068     | 0.0104          | 29    |
| 0.0064     | 0.0100          | 30    |
| 0.0062     | 0.0098          | 31    |
| 0.0065     | 0.0112          | 32    |
| 0.0064     | 0.0107          | 33    |
| 0.0059     | 0.0105          | 34    |
| 0.0065     | 0.0107          | 35    |
| 0.0058     | 0.0100          | 36    |
| 0.0052     | 0.0099          | 37    |
| 0.0052     | 0.0107          | 38    |
| 0.0055     | 0.0123          | 39    |
| 0.0052     | 0.0097          | 40    |
| 0.0051     | 0.0101          | 41    |
| 0.0051     | 0.0102          | 42    |
| 0.0046     | 0.0105          | 43    |
| 0.0048     | 0.0093          | 44    |
| 0.0044     | 0.0096          | 45    |
| 0.0043     | 0.0094          | 46    |
| 0.0040     | 0.0119          | 47    |
| 0.0041     | 0.0110          | 48    |
| 0.0043     | 0.0095          | 49    |
| 0.0041     | 0.0099          | 50    |
| 0.0040     | 0.0097          | 51    |
| 0.0041     | 0.0098          | 52    |
| 0.0041     | 0.0097          | 53    |
| 0.0041     | 0.0094          | 54    |
| 0.0042     | 0.0097          | 55    |
| 0.0038     | 0.0101          | 56    |
| 0.0037     | 0.0096          | 57    |
| 0.0036     | 0.0096          | 58    |
| 0.0035     | 0.0096          | 59    |


### Framework versions

- Transformers 4.35.2
- TensorFlow 2.15.0
- Datasets 2.16.0
- Tokenizers 0.15.0