Modelpublic

Dhyey8/swin-tiny-patch4-window7-224-finetuned-teeth_dataset-finetuned-teeth_dataset-V2

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face

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Model Card

swin-tiny-patch4-window7-224-finetuned-teethdataset-finetuned-teethdataset-V2

This model is a fine-tuned version of Dhyey8/swin-tiny-patch4-window7-224-finetuned-teeth_dataset on the imagefolder dataset. It achieves the following results on the evaluation set:

—Loss: 0.3081
—Accuracy: 0.9261

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: 5e-05
—trainbatchsize: 32
—evalbatchsize: 32
—seed: 42
—gradientaccumulationsteps: 4
—totaltrainbatch_size: 128
—optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
—lrschedulertype: linear
—lrschedulerwarmup_ratio: 0.1
—num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	0.8	3	1.1267	0.8391
No log	1.87	7	1.0719	0.8304
0.5709	2.93	11	0.9447	0.8478
0.5709	4.0	15	0.8442	0.8652
0.5709	4.8	18	0.7065	0.8826
0.3317	5.87	22	0.6930	0.8891
0.3317	6.93	26	0.5630	0.8978
0.1576	8.0	30	0.5882	0.8826
0.1576	8.8	33	0.5198	0.9087
0.1576	9.87	37	0.4425	0.9043
0.0883	10.93	41	0.4727	0.8978
0.0883	12.0	45	0.4314	0.9022
0.0883	12.8	48	0.4011	0.9022
0.051	13.87	52	0.4045	0.9174
0.051	14.93	56	0.3745	0.9109
0.0415	16.0	60	0.3597	0.9152
0.0415	16.8	63	0.4016	0.9065
0.0415	17.87	67	0.3804	0.9152
0.0307	18.93	71	0.3519	0.9217
0.0307	20.0	75	0.4131	0.8935
0.0307	20.8	78	0.4047	0.9
0.0262	21.87	82	0.3450	0.9174
0.0262	22.93	86	0.3639	0.9109
0.0208	24.0	90	0.3843	0.9043
0.0208	24.8	93	0.3797	0.8978
0.0208	25.87	97	0.3660	0.9152
0.0141	26.93	101	0.3445	0.9152
0.0141	28.0	105	0.3131	0.9239
0.0141	28.8	108	0.3069	0.9196
0.0114	29.87	112	0.3006	0.9196
0.0114	30.93	116	0.3097	0.9239
0.014	32.0	120	0.3121	0.9174
0.014	32.8	123	0.3242	0.9174
0.014	33.87	127	0.3291	0.9217
0.016	34.93	131	0.3156	0.9217
0.016	36.0	135	0.3081	0.9261
0.016	36.8	138	0.3084	0.9261
0.0114	37.87	142	0.3148	0.9196
0.0114	38.93	146	0.3191	0.9174
0.0091	40.0	150	0.3191	0.9174

Framework versions

—Transformers 4.38.2
—Pytorch 2.2.1+cu121
—Datasets 2.18.0
—Tokenizers 0.15.2