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# segformer-b5-finetuned-magic-cards-230117-3

This model is a fine-tuned version of [nvidia/mit-b5](https://huggingface.co/nvidia/mit-b5) on the andrewljohnson/magic_cards dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0691
- Mean Iou: 0.6585
- Mean Accuracy: 0.9878
- Overall Accuracy: 0.9912
- Accuracy Unlabeled: nan
- Accuracy Front: 0.9978
- Accuracy Back: 0.9777
- Iou Unlabeled: 0.0
- Iou Front: 0.9978
- Iou Back: 0.9777

## 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:
- learning_rate: 6e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Unlabeled | Accuracy Front | Accuracy Back | Iou Unlabeled | Iou Front | Iou Back |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:--------------:|:-------------:|:-------------:|:---------:|:--------:|
| 1.2232        | 0.37  | 20   | 0.4691          | 0.6041   | 0.9201        | 0.9218           | nan                | 0.9252         | 0.9150        | 0.0           | 0.9252    | 0.8870   |
| 0.2718        | 0.74  | 40   | 0.1983          | 0.6509   | 0.9764        | 0.9785           | nan                | 0.9826         | 0.9702        | 0.0           | 0.9826    | 0.9702   |
| 0.255         | 1.11  | 60   | 0.0939          | 0.6524   | 0.9785        | 0.9794           | nan                | 0.9812         | 0.9758        | 0.0           | 0.9812    | 0.9758   |
| 0.1103        | 1.48  | 80   | 0.0682          | 0.6536   | 0.9804        | 0.9813           | nan                | 0.9830         | 0.9779        | 0.0           | 0.9830    | 0.9779   |
| 0.1373        | 1.85  | 100  | 0.1260          | 0.6631   | 0.9946        | 0.9961           | nan                | 0.9989         | 0.9903        | 0.0           | 0.9989    | 0.9903   |
| 0.0566        | 2.22  | 120  | 0.1558          | 0.6578   | 0.9868        | 0.9912           | nan                | 0.9999         | 0.9736        | 0.0           | 0.9999    | 0.9736   |
| 0.1535        | 2.59  | 140  | 0.1330          | 0.6558   | 0.9838        | 0.9883           | nan                | 0.9973         | 0.9703        | 0.0           | 0.9973    | 0.9703   |
| 0.0586        | 2.96  | 160  | 0.2317          | 0.6599   | 0.9899        | 0.9933           | nan                | 1.0000         | 0.9798        | 0.0           | 1.0000    | 0.9798   |
| 0.0727        | 3.33  | 180  | 0.1018          | 0.6586   | 0.9880        | 0.9919           | nan                | 0.9995         | 0.9764        | 0.0           | 0.9995    | 0.9764   |
| 0.3588        | 3.7   | 200  | 0.1151          | 0.6608   | 0.9912        | 0.9939           | nan                | 0.9993         | 0.9831        | 0.0           | 0.9993    | 0.9831   |
| 0.0463        | 4.07  | 220  | 0.0538          | 0.6610   | 0.9915        | 0.9934           | nan                | 0.9969         | 0.9862        | 0.0           | 0.9969    | 0.9862   |
| 0.046         | 4.44  | 240  | 0.1201          | 0.6581   | 0.9871        | 0.9912           | nan                | 0.9991         | 0.9751        | 0.0           | 0.9991    | 0.9751   |
| 0.0468        | 4.81  | 260  | 0.0691          | 0.6585   | 0.9878        | 0.9912           | nan                | 0.9978         | 0.9777        | 0.0           | 0.9978    | 0.9777   |


### 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-b5-finetuned-magic-cards-230117-3", "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-b5-finetuned-magic-cards-230117-3
===========================================


This model is a fine-tuned version of nvidia/mit-b5 on the andrewljohnson/magic\_cards dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0691
* Mean Iou: 0.6585
* Mean Accuracy: 0.9878
* Overall Accuracy: 0.9912
* Accuracy Unlabeled: nan
* Accuracy Front: 0.9978
* Accuracy Back: 0.9777
* Iou Unlabeled: 0.0
* Iou Front: 0.9978
* Iou Back: 0.9777


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:


* learning\_rate: 6e-05
* train\_batch\_size: 1
* eval\_batch\_size: 1
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5


### Training results



### Framework versions


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



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 6e-05
* train\_batch\_size: 1
* eval\_batch\_size: 1
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5 ### 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 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 6e-05
* train\_batch\_size: 1
* eval\_batch\_size: 1
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5 ### 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 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 6e-05
* train\_batch\_size: 1
* eval\_batch\_size: 1
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5### Training results### Framework versions


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