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# mit-b0-finetuned-sidewalk-semantic

This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.2125
- Validation Loss: 0.5151
- Epoch: 49

## Model description

The model was fine-tuned from [this model](https://huggingface.co/nvidia/mit-b0). More information about the model is available
[here](https://huggingface.co/docs/transformers/model_doc/segformer).

## Intended uses & limitations

This fine-tuned model is just for demonstration purposes. Before using it in production, it should be thoroughly inspected and adjusted
if needed. 

## Training and evaluation data

[`segments/sidewalk-semantic`](https://huggingface.co/datasets/segments/sidewalk-semantic)

## Training procedure

More information is available here: [deep-diver/segformer-tf-transformers](https://github.com/deep-diver/segformer-tf-transformers).

### 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 |
|:----------:|:---------------:|:-----:|
| 2.0785     | 1.1753          | 0     |
| 1.1312     | 0.8807          | 1     |
| 0.9315     | 0.7585          | 2     |
| 0.7952     | 0.7261          | 3     |
| 0.7273     | 0.6701          | 4     |
| 0.6603     | 0.6396          | 5     |
| 0.6198     | 0.6238          | 6     |
| 0.5958     | 0.5925          | 7     |
| 0.5378     | 0.5714          | 8     |
| 0.5236     | 0.5786          | 9     |
| 0.4960     | 0.5588          | 10    |
| 0.4633     | 0.5624          | 11    |
| 0.4562     | 0.5450          | 12    |
| 0.4167     | 0.5438          | 13    |
| 0.4100     | 0.5248          | 14    |
| 0.3947     | 0.5354          | 15    |
| 0.3867     | 0.5069          | 16    |
| 0.3803     | 0.5285          | 17    |
| 0.3696     | 0.5318          | 18    |
| 0.3386     | 0.5162          | 19    |
| 0.3349     | 0.5312          | 20    |
| 0.3233     | 0.5304          | 21    |
| 0.3328     | 0.5178          | 22    |
| 0.3140     | 0.5131          | 23    |
| 0.3081     | 0.5049          | 24    |
| 0.3046     | 0.5011          | 25    |
| 0.3209     | 0.5197          | 26    |
| 0.2966     | 0.5151          | 27    |
| 0.2829     | 0.5166          | 28    |
| 0.2968     | 0.5210          | 29    |
| 0.2818     | 0.5300          | 30    |
| 0.2739     | 0.5221          | 31    |
| 0.2602     | 0.5340          | 32    |
| 0.2570     | 0.5124          | 33    |
| 0.2557     | 0.5234          | 34    |
| 0.2593     | 0.5098          | 35    |
| 0.2582     | 0.5329          | 36    |
| 0.2439     | 0.5373          | 37    |
| 0.2413     | 0.5141          | 38    |
| 0.2423     | 0.5210          | 39    |
| 0.2340     | 0.5043          | 40    |
| 0.2244     | 0.5300          | 41    |
| 0.2246     | 0.4978          | 42    |
| 0.2270     | 0.5385          | 43    |
| 0.2254     | 0.5125          | 44    |
| 0.2176     | 0.5510          | 45    |
| 0.2194     | 0.5384          | 46    |
| 0.2136     | 0.5186          | 47    |
| 0.2121     | 0.5356          | 48    |
| 0.2125     | 0.5151          | 49    |


### Framework versions

- Transformers 4.21.0.dev0
- TensorFlow 2.8.0
- Datasets 2.3.2
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_keras_callback", "vision", "image-segmentation"], "datasets": ["segments/sidewalk-semantic"], "model-index": [{"name": "mit-b0-finetuned-sidewalk-semantic", "results": []}]}
transformers tf segformer generated_from_keras_callback vision image-segmentation dataset:segments/sidewalk-semantic license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #tf #segformer #generated_from_keras_callback #vision #image-segmentation #dataset-segments/sidewalk-semantic #license-apache-2.0 #endpoints_compatible #region-us 

mit-b0-finetuned-sidewalk-semantic
==================================


This model is a fine-tuned version of nvidia/mit-b0 on an unknown dataset.
It achieves the following results on the evaluation set:


* Train Loss: 0.2125
* Validation Loss: 0.5151
* Epoch: 49


Model description
-----------------


The model was fine-tuned from this model. More information about the model is available
here.


Intended uses & limitations
---------------------------


This fine-tuned model is just for demonstration purposes. Before using it in production, it should be thoroughly inspected and adjusted
if needed.


Training and evaluation data
----------------------------


'segments/sidewalk-semantic'


Training procedure
------------------


More information is available here: deep-diver/segformer-tf-transformers.


### 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 4.21.0.dev0
* TensorFlow 2.8.0
* Datasets 2.3.2
* Tokenizers 0.12.1



### 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 4.21.0.dev0
* TensorFlow 2.8.0
* Datasets 2.3.2
* Tokenizers 0.12.1
TAGS
#transformers #tf #segformer #generated_from_keras_callback #vision #image-segmentation #dataset-segments/sidewalk-semantic #license-apache-2.0 #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 4.21.0.dev0
* TensorFlow 2.8.0
* Datasets 2.3.2
* Tokenizers 0.12.1
passage: TAGS
#transformers #tf #segformer #generated_from_keras_callback #vision #image-segmentation #dataset-segments/sidewalk-semantic #license-apache-2.0 #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 4.21.0.dev0
* TensorFlow 2.8.0
* Datasets 2.3.2
* Tokenizers 0.12.1