segformer-b5-finetuned-magic-cards-230117-2

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: 0.0491
• Mean Iou: 0.6649
• Mean Accuracy: 0.9974
• Overall Accuracy: 0.9972
• Accuracy Unlabeled: nan
• Accuracy Front: 0.9990
• Accuracy Back: 0.9957
• Iou Unlabeled: 0.0
• Iou Front: 0.9990
• Iou Back: 0.9957

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
0.5968	0.33	20	0.4422	0.6366	0.9701	0.9690	nan	0.9812	0.9590	0.0	0.9507	0.9590
0.8955	0.66	40	0.2353	0.6496	0.9819	0.9807	nan	0.9944	0.9695	0.0	0.9792	0.9695
0.1269	0.98	60	0.1739	0.6566	0.9922	0.9916	nan	0.9979	0.9866	0.0	0.9832	0.9866
0.7629	1.31	80	0.1664	0.6561	0.9915	0.9909	nan	0.9975	0.9856	0.0	0.9826	0.9856
0.106	1.64	100	0.1005	0.6641	0.9968	0.9967	nan	0.9978	0.9959	0.0	0.9966	0.9959
0.3278	1.97	120	0.0577	0.6632	0.9948	0.9947	nan	0.9963	0.9934	0.0	0.9963	0.9934
0.061	2.3	140	0.0655	0.6642	0.9963	0.9962	nan	0.9972	0.9953	0.0	0.9972	0.9953
0.0766	2.62	160	0.0470	0.6635	0.9953	0.9954	nan	0.9940	0.9966	0.0	0.9940	0.9966
0.0664	2.95	180	0.0436	0.6617	0.9926	0.9931	nan	0.9877	0.9975	0.0	0.9877	0.9975
0.0655	3.28	200	0.0632	0.6649	0.9973	0.9971	nan	0.9994	0.9953	0.0	0.9994	0.9953
0.0356	3.61	220	0.0755	0.6661	0.9991	0.9991	nan	0.9992	0.9991	0.0	0.9992	0.9991
0.0516	3.93	240	0.0470	0.6643	0.9965	0.9963	nan	0.9987	0.9943	0.0	0.9987	0.9943
0.0517	4.26	260	0.0481	0.6645	0.9967	0.9965	nan	0.9989	0.9945	0.0	0.9989	0.9945
0.1886	4.59	280	0.0823	0.6659	0.9988	0.9987	nan	0.9999	0.9977	0.0	0.9999	0.9977
0.0453	4.92	300	0.0491	0.6649	0.9974	0.9972	nan	0.9990	0.9957	0.0	0.9990	0.9957

Framework versions

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