This model is a fine-tuned version of microsoft/beit-base-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 1.7755
Accuracy: 0.6341

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: 0.0001
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	6	1.4246	0.2683
1.7592	2.0	12	1.3851	0.2683
1.7592	3.0	18	1.3804	0.2439
1.4204	4.0	24	1.4010	0.2683
1.3988	5.0	30	1.3776	0.2439
1.3988	6.0	36	1.3196	0.3171
1.3741	7.0	42	1.2653	0.3659
1.3741	8.0	48	1.3284	0.3902
1.3098	9.0	54	1.2504	0.4146
1.2944	10.0	60	1.2840	0.2927
1.2944	11.0	66	1.3400	0.3902
1.3252	12.0	72	1.2889	0.3659
1.3252	13.0	78	1.1547	0.4634
1.2379	14.0	84	1.1463	0.3415
1.1874	15.0	90	1.1230	0.5122
1.1874	16.0	96	4.2155	0.3902
1.374	17.0	102	0.9374	0.6098
1.374	18.0	108	0.9748	0.6341
1.0858	19.0	114	0.9498	0.5366
0.9929	20.0	120	1.0346	0.4878
0.9929	21.0	126	1.2495	0.4634
0.9078	22.0	132	1.0142	0.5366
0.9078	23.0	138	0.9571	0.6341
0.8585	24.0	144	0.7607	0.7073
0.9707	25.0	150	0.9749	0.4878
0.9707	26.0	156	1.2739	0.6341
0.8033	27.0	162	0.7831	0.6585
0.8033	28.0	168	0.9134	0.5610
0.8358	29.0	174	0.9940	0.6098
0.7373	30.0	180	0.9448	0.6341
0.7373	31.0	186	1.0065	0.6341
0.693	32.0	192	1.2616	0.6585
0.693	33.0	198	1.0510	0.6098
0.6403	34.0	204	1.2334	0.6341
0.6359	35.0	210	1.2865	0.6341
0.6359	36.0	216	1.2812	0.6098
0.5717	37.0	222	1.4784	0.6341
0.5717	38.0	228	1.6714	0.6341
0.5294	39.0	234	1.7953	0.5854
0.5043	40.0	240	1.6946	0.6341
0.5043	41.0	246	1.7411	0.6585
0.4865	42.0	252	1.7755	0.6341
0.4865	43.0	258	1.7755	0.6341
0.4648	44.0	264	1.7755	0.6341
0.4795	45.0	270	1.7755	0.6341
0.4795	46.0	276	1.7755	0.6341
0.4544	47.0	282	1.7755	0.6341
0.4544	48.0	288	1.7755	0.6341
0.519	49.0	294	1.7755	0.6341
0.4907	50.0	300	1.7755	0.6341

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0

hkivancoral/hushem_1x_beit_base_rms_0001_fold5

hushem_1x_beit_base_rms_0001_fold5

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

hkivancoral/
hushem_1x_beit_base_rms_0001_fold5