
<!-- 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. -->

# ChristianMDahl/segFormer-b3-horizontal-vertical

This model is a fine-tuned version of [nvidia/mit-b3](https://huggingface.co/nvidia/mit-b3) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.1671
- Validation Loss: 0.2320
- Epoch: 19

## 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', 'learning_rate': 6e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 0.3203     | 0.2831          | 0     |
| 0.2822     | 0.2688          | 1     |
| 0.2662     | 0.2578          | 2     |
| 0.2526     | 0.2484          | 3     |
| 0.2396     | 0.2442          | 4     |
| 0.2288     | 0.2416          | 5     |
| 0.2195     | 0.2381          | 6     |
| 0.2121     | 0.2361          | 7     |
| 0.2058     | 0.2314          | 8     |
| 0.1999     | 0.2277          | 9     |
| 0.1952     | 0.2287          | 10    |
| 0.1912     | 0.2221          | 11    |
| 0.1869     | 0.2205          | 12    |
| 0.1835     | 0.2226          | 13    |
| 0.1804     | 0.2209          | 14    |
| 0.1775     | 0.2181          | 15    |
| 0.1745     | 0.2206          | 16    |
| 0.1721     | 0.2179          | 17    |
| 0.1693     | 0.2199          | 18    |
| 0.1671     | 0.2320          | 19    |


### Framework versions

- Transformers 4.29.2
- TensorFlow 2.10.1
- Tokenizers 0.13.3

{"license": "other", "tags": ["generated_from_keras_callback"], "base_model": "nvidia/mit-b3", "model-index": [{"name": "ChristianMDahl/segFormer-b3-horizontal-vertical", "results": []}]}
transformers tf segformer generated_from_keras_callback base_model:nvidia/mit-b3 license:other endpoints_compatible region:us
TAGS
#transformers #tf #segformer #generated_from_keras_callback #base_model-nvidia/mit-b3 #license-other #endpoints_compatible #region-us 

ChristianMDahl/segFormer-b3-horizontal-vertical
===============================================


This model is a fine-tuned version of nvidia/mit-b3 on an unknown dataset.
It achieves the following results on the evaluation set:


* Train Loss: 0.1671
* Validation Loss: 0.2320
* Epoch: 19


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', 'learning\_rate': 6e-05, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32


### Training results



### Framework versions


* Transformers 4.29.2
* TensorFlow 2.10.1
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'Adam', 'learning\_rate': 6e-05, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.29.2
* TensorFlow 2.10.1
* Tokenizers 0.13.3
TAGS
#transformers #tf #segformer #generated_from_keras_callback #base_model-nvidia/mit-b3 #license-other #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'Adam', 'learning\_rate': 6e-05, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.29.2
* TensorFlow 2.10.1
* Tokenizers 0.13.3