hushem_1x_beit_base_sgd_001_fold2

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: 1.2883
• Accuracy: 0.3333

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: 0.001
• 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	1.5095	0.2667
1.5706	2.0	12	1.4767	0.2667
1.5706	3.0	18	1.4520	0.2667
1.4609	4.0	24	1.4339	0.3111
1.4723	5.0	30	1.4175	0.3111
1.4723	6.0	36	1.4043	0.3111
1.4256	7.0	42	1.3928	0.3111
1.4256	8.0	48	1.3810	0.3111
1.3951	9.0	54	1.3717	0.3111
1.359	10.0	60	1.3630	0.3111
1.359	11.0	66	1.3563	0.3111
1.3542	12.0	72	1.3514	0.2889
1.3542	13.0	78	1.3444	0.2889
1.3277	14.0	84	1.3408	0.2667
1.3111	15.0	90	1.3350	0.2667
1.3111	16.0	96	1.3320	0.2889
1.3054	17.0	102	1.3278	0.2889
1.3054	18.0	108	1.3233	0.2889
1.2953	19.0	114	1.3199	0.2889
1.2867	20.0	120	1.3171	0.2889
1.2867	21.0	126	1.3151	0.2889
1.2581	22.0	132	1.3144	0.2889
1.2581	23.0	138	1.3095	0.2889
1.2646	24.0	144	1.3068	0.3111
1.2188	25.0	150	1.3045	0.3111
1.2188	26.0	156	1.3025	0.3333
1.2206	27.0	162	1.3017	0.3333
1.2206	28.0	168	1.2992	0.3333
1.2061	29.0	174	1.2990	0.3333
1.2221	30.0	180	1.2969	0.3333
1.2221	31.0	186	1.2951	0.3333
1.2025	32.0	192	1.2945	0.3333
1.2025	33.0	198	1.2933	0.3333
1.2187	34.0	204	1.2926	0.3333
1.2089	35.0	210	1.2913	0.3333
1.2089	36.0	216	1.2899	0.3333
1.1998	37.0	222	1.2891	0.3333
1.1998	38.0	228	1.2890	0.3333
1.2017	39.0	234	1.2884	0.3333
1.1887	40.0	240	1.2883	0.3333
1.1887	41.0	246	1.2883	0.3333
1.1807	42.0	252	1.2883	0.3333
1.1807	43.0	258	1.2883	0.3333
1.2122	44.0	264	1.2883	0.3333
1.2003	45.0	270	1.2883	0.3333
1.2003	46.0	276	1.2883	0.3333
1.1882	47.0	282	1.2883	0.3333
1.1882	48.0	288	1.2883	0.3333
1.1992	49.0	294	1.2883	0.3333
1.1934	50.0	300	1.2883	0.3333

Framework versions

• Transformers 4.35.2
• Pytorch 2.1.0+cu118
• Datasets 2.15.0
• Tokenizers 0.15.0