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sshk/
segformer-b3-fashion-finetuned-polo-segments-aug-07-v1.2

Name: segformer-b3-fashion-finetuned-polo-segments-aug-07-v1.2
Availability: InStock

generated_from_trainer

sayeed99/segformer-b3-fashion

finetune

other

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segformer-b3-fashion-finetuned-polo-segments-aug-07-v1.2

This model is a fine-tuned version of sayeed99/segformer-b3-fashion on the sshk/polo-badges-segmentation dataset. It achieves the following results on the evaluation set:

Loss: 0.0801
Mean Iou: 0.8698
Mean Accuracy: 0.9244
Overall Accuracy: 0.9721
Accuracy Unlabeled: nan
Accuracy Collar: 0.8554
Accuracy Polo: 0.9713
Accuracy Lines-cuff: 0.8045
Accuracy Lines-chest: 0.9543
Accuracy Human: 0.9710
Accuracy Background: 0.9896
Iou Unlabeled: nan
Iou Collar: 0.7817
Iou Polo: 0.9387
Iou Lines-cuff: 0.7252
Iou Lines-chest: 0.8492
Iou Human: 0.9456
Iou Background: 0.9783

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Mean Iou	Mean Accuracy	Overall Accuracy	Accuracy Unlabeled	Accuracy Collar	Accuracy Polo	Accuracy Lines-cuff	Accuracy Lines-chest	Accuracy Human	Accuracy Background	Iou Unlabeled	Iou Collar	Iou Polo	Iou Lines-cuff	Iou Lines-chest	Iou Human	Iou Background
0.1958	4.0	20	0.1935	0.5473	0.5809	0.9484	nan	0.5688	0.9710	0.0	0.0	0.9699	0.9754	nan	0.5048	0.8825	0.0	0.0	0.9291	0.9676
0.0878	8.0	40	0.1158	0.7585	0.7864	0.9643	nan	0.7548	0.9721	0.3063	0.7322	0.9787	0.9740	nan	0.7084	0.9275	0.3054	0.7048	0.9353	0.9694
0.0737	12.0	60	0.0929	0.8595	0.9043	0.9708	nan	0.8229	0.9704	0.7743	0.8982	0.9757	0.9842	nan	0.7641	0.9366	0.7031	0.8330	0.9436	0.9766
0.0646	16.0	80	0.0868	0.8643	0.9140	0.9711	nan	0.8521	0.9747	0.7778	0.9226	0.9662	0.9909	nan	0.7807	0.9359	0.7101	0.8379	0.9435	0.9774
0.0688	20.0	100	0.0819	0.8665	0.9176	0.9720	nan	0.8502	0.9721	0.7841	0.9386	0.9709	0.9899	nan	0.7814	0.9384	0.7139	0.8418	0.9459	0.9778
0.052	24.0	120	0.0821	0.8652	0.9207	0.9716	nan	0.8302	0.9646	0.8053	0.9590	0.9769	0.9883	nan	0.7694	0.9381	0.7210	0.8400	0.9445	0.9781
0.0483	28.0	140	0.0801	0.8698	0.9244	0.9721	nan	0.8554	0.9713	0.8045	0.9543	0.9710	0.9896	nan	0.7817	0.9387	0.7252	0.8492	0.9456	0.9783

Framework versions

Transformers 4.44.0
Pytorch 2.4.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1

sshk/segformer-b3-fashion-finetuned-polo-segments-aug-07-v1.2

segformer-b3-fashion-finetuned-polo-segments-aug-07-v1.2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

sshk/
segformer-b3-fashion-finetuned-polo-segments-aug-07-v1.2