andrewljohnson
/

segformer-b5-finetuned-magic-cards-230117

@@ -16,16 +16,16 @@ should probably proofread and complete it, then remove this comment. -->
 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: 0.1361
-- Mean Iou: 0.6485
-- Mean Accuracy: 0.9729
-- Overall Accuracy: 0.9729
 - Accuracy Unlabeled: nan
-- Accuracy Front: 0.9744
-- Accuracy Back: 0.9714
 - Iou Unlabeled: 0.0
-- Iou Front: 0.9742
-- Iou Back: 0.9714
 ## Model description
@@ -45,19 +45,30 @@ More information needed
 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: 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 |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:--------------:|:-------------:|:-------------:|:---------:|:--------:|
-| 0.3743        | 2.5   | 20   | 0.2551          | 0.6392   | 0.9721        | 0.9720           | nan                | 0.9839         | 0.9603        | 0.0           | 0.9574    | 0.9603   |
-| 0.1906        | 5.0   | 40   | 0.1361          | 0.6485   | 0.9729        | 0.9729           | nan                | 0.9744         | 0.9714        | 0.0           | 0.9742    | 0.9714   |
 ### Framework versions

 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: 0.2096
+- Mean Iou: 0.6629
+- Mean Accuracy: 0.9944
+- Overall Accuracy: 0.9944
 - Accuracy Unlabeled: nan
+- Accuracy Front: 0.9997
+- Accuracy Back: 0.9891
 - Iou Unlabeled: 0.0
+- Iou Front: 0.9997
+- Iou Back: 0.9891
 ## Model description
 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: 10
 ### 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 |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:--------------:|:-------------:|:-------------:|:---------:|:--------:|
+| 0.496         | 0.74  | 20   | 0.4441          | 0.6552   | 0.9838        | 0.9838           | nan                | 0.9786         | 0.9890        | 0.0           | 0.9786    | 0.9869   |
+| 0.1693        | 1.48  | 40   | 0.4098          | 0.6597   | 0.9897        | 0.9897           | nan                | 0.9943         | 0.9851        | 0.0           | 0.9943    | 0.9849   |
+| 0.1172        | 2.22  | 60   | 0.2734          | 0.6582   | 0.9874        | 0.9874           | nan                | 0.9977         | 0.9770        | 0.0           | 0.9977    | 0.9770   |
+| 0.1335        | 2.96  | 80   | 0.2637          | 0.6609   | 0.9914        | 0.9914           | nan                | 0.9959         | 0.9869        | 0.0           | 0.9959    | 0.9869   |
+| 0.0781        | 3.7   | 100  | 0.5178          | 0.6644   | 0.9966        | 0.9966           | nan                | 0.9998         | 0.9933        | 0.0           | 0.9998    | 0.9933   |
+| 0.1302        | 4.44  | 120  | 0.2753          | 0.6652   | 0.9978        | 0.9978           | nan                | 0.9993         | 0.9962        | 0.0           | 0.9993    | 0.9962   |
+| 0.0688        | 5.19  | 140  | 0.1458          | 0.6618   | 0.9926        | 0.9926           | nan                | 0.9950         | 0.9903        | 0.0           | 0.9950    | 0.9903   |
+| 0.0866        | 5.93  | 160  | 0.1763          | 0.6636   | 0.9954        | 0.9954           | nan                | 0.9962         | 0.9946        | 0.0           | 0.9962    | 0.9946   |
+| 0.0525        | 6.67  | 180  | 0.1812          | 0.6627   | 0.9941        | 0.9941           | nan                | 0.9988         | 0.9895        | 0.0           | 0.9988    | 0.9895   |
+| 0.0679        | 7.41  | 200  | 0.2246          | 0.6625   | 0.9937        | 0.9937           | nan                | 0.9990         | 0.9884        | 0.0           | 0.9990    | 0.9884   |
+| 0.0424        | 8.15  | 220  | 0.2079          | 0.6623   | 0.9934        | 0.9935           | nan                | 0.9996         | 0.9873        | 0.0           | 0.9996    | 0.9873   |
+| 0.0349        | 8.89  | 240  | 0.1559          | 0.6626   | 0.9939        | 0.9940           | nan                | 0.9987         | 0.9892        | 0.0           | 0.9987    | 0.9892   |
+| 0.0357        | 9.63  | 260  | 0.2096          | 0.6629   | 0.9944        | 0.9944           | nan                | 0.9997         | 0.9891        | 0.0           | 0.9997    | 0.9891   |
 ### Framework versions