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# segformer-b0-finetuned-magic-cards-230117

This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the andrewljohnson/magic_cards dataset.
It achieves the following results on the evaluation set:
- Loss: 0.059
- Mean Iou: 0.654
- Mean Accuracy: 0.981
- Overall Accuracy: 0.983
- Accuracy Unlabeled: nan
- Accuracy Front: 0.964
- Accuracy Back: 0.998
- Iou Unlabeled: 0.0
- Iou Front: 0.965
- Iou Back: 0.998

## Model description

Segment magic card front and backs.

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 6e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results


### Framework versions

- Transformers 4.25.1
- Pytorch 1.12.1
- Datasets 2.8.0
- Tokenizers 0.13.0.dev0

{"license": "other", "tags": ["vision", "image-segmentation", "generated_from_trainer"], "model-index": [{"name": "segformer-b0-finetuned-magic-cards-230117", "results": []}]}
transformers pytorch segformer vision image-segmentation generated_from_trainer license:other endpoints_compatible region:us
TAGS
#transformers #pytorch #segformer #vision #image-segmentation #generated_from_trainer #license-other #endpoints_compatible #region-us 




# segformer-b0-finetuned-magic-cards-230117

This model is a fine-tuned version of nvidia/mit-b0 on the andrewljohnson/magic_cards dataset.
It achieves the following results on the evaluation set:
- Loss: 0.059
- Mean Iou: 0.654
- Mean Accuracy: 0.981
- Overall Accuracy: 0.983
- Accuracy Unlabeled: nan
- Accuracy Front: 0.964
- Accuracy Back: 0.998
- Iou Unlabeled: 0.0
- Iou Front: 0.965
- Iou Back: 0.998

## Model description

Segment magic card front and backs.

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 6e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results


### Framework versions

- Transformers 4.25.1
- Pytorch 1.12.1
- Datasets 2.8.0
- Tokenizers 0.13.0.dev0

# segformer-b0-finetuned-magic-cards-230117

This model is a fine-tuned version of nvidia/mit-b0 on the andrewljohnson/magic_cards dataset.
It achieves the following results on the evaluation set:
- Loss: 0.059
- Mean Iou: 0.654
- Mean Accuracy: 0.981
- Overall Accuracy: 0.983
- Accuracy Unlabeled: nan
- Accuracy Front: 0.964
- Accuracy Back: 0.998
- Iou Unlabeled: 0.0
- Iou Front: 0.965
- Iou Back: 0.998 ## Model description

Segment magic card front and backs. ## Intended uses & limitations

More information needed ## Training and evaluation data

More information needed ## Training procedure ### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 6e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50 ### Training results ### Framework versions

- Transformers 4.25.1
- Pytorch 1.12.1
- Datasets 2.8.0
- Tokenizers 0.13.0.dev0
TAGS
#transformers #pytorch #segformer #vision #image-segmentation #generated_from_trainer #license-other #endpoints_compatible #region-us 
 # segformer-b0-finetuned-magic-cards-230117

This model is a fine-tuned version of nvidia/mit-b0 on the andrewljohnson/magic_cards dataset.
It achieves the following results on the evaluation set:
- Loss: 0.059
- Mean Iou: 0.654
- Mean Accuracy: 0.981
- Overall Accuracy: 0.983
- Accuracy Unlabeled: nan
- Accuracy Front: 0.964
- Accuracy Back: 0.998
- Iou Unlabeled: 0.0
- Iou Front: 0.965
- Iou Back: 0.998 ## Model description

Segment magic card front and backs. ## Intended uses & limitations

More information needed ## Training and evaluation data

More information needed ## Training procedure ### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 6e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50 ### Training results ### Framework versions

- Transformers 4.25.1
- Pytorch 1.12.1
- Datasets 2.8.0
- Tokenizers 0.13.0.dev0
TAGS
#transformers #pytorch #segformer #vision #image-segmentation #generated_from_trainer #license-other #endpoints_compatible #region-us 
# segformer-b0-finetuned-magic-cards-230117

This model is a fine-tuned version of nvidia/mit-b0 on the andrewljohnson/magic_cards dataset.
It achieves the following results on the evaluation set:
- Loss: 0.059
- Mean Iou: 0.654
- Mean Accuracy: 0.981
- Overall Accuracy: 0.983
- Accuracy Unlabeled: nan
- Accuracy Front: 0.964
- Accuracy Back: 0.998
- Iou Unlabeled: 0.0
- Iou Front: 0.965
- Iou Back: 0.998## Model description

Segment magic card front and backs.## Intended uses & limitations

More information needed## Training and evaluation data

More information needed## Training procedure### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 6e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50### Training results### Framework versions

- Transformers 4.25.1
- Pytorch 1.12.1
- Datasets 2.8.0
- Tokenizers 0.13.0.dev0