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: 1.6210
Accuracy: 0.3953

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	4.8894	0.2326
4.4417	2.0	12	1.8176	0.2558
4.4417	3.0	18	1.7138	0.2558
1.6178	4.0	24	1.4939	0.2558
1.4727	5.0	30	1.4012	0.2326
1.4727	6.0	36	1.4010	0.2558
1.3417	7.0	42	1.4942	0.3023
1.3417	8.0	48	1.4300	0.2558
1.3201	9.0	54	1.3963	0.2326
1.3475	10.0	60	1.4128	0.3488
1.3475	11.0	66	1.4248	0.3023
1.286	12.0	72	1.4058	0.3488
1.286	13.0	78	1.3763	0.3023
1.2349	14.0	84	1.3835	0.2791
1.2129	15.0	90	1.3655	0.3488
1.2129	16.0	96	1.3765	0.2558
1.215	17.0	102	1.3898	0.3488
1.215	18.0	108	1.4215	0.3721
1.1858	19.0	114	1.4008	0.3023
1.1772	20.0	120	1.3543	0.2791
1.1772	21.0	126	1.5020	0.2791
1.1365	22.0	132	1.4006	0.3256
1.1365	23.0	138	1.4145	0.3256
1.1417	24.0	144	1.3987	0.2791
1.0966	25.0	150	1.4121	0.3023
1.0966	26.0	156	1.3953	0.2791
1.0941	27.0	162	1.5116	0.3256
1.0941	28.0	168	1.3871	0.3488
1.0777	29.0	174	1.3779	0.3488
1.0766	30.0	180	1.3806	0.3488
1.0766	31.0	186	1.4716	0.3256
1.0237	32.0	192	1.4549	0.3488
1.0237	33.0	198	1.5155	0.3721
1.0081	34.0	204	1.4254	0.3488
0.9905	35.0	210	1.4408	0.3953
0.9905	36.0	216	1.6753	0.3953
0.9364	37.0	222	1.7926	0.3488
0.9364	38.0	228	1.6780	0.4186
0.8986	39.0	234	1.6075	0.3953
0.8892	40.0	240	1.5788	0.4419
0.8892	41.0	246	1.6155	0.4186
0.8545	42.0	252	1.6210	0.3953
0.8545	43.0	258	1.6210	0.3953
0.8504	44.0	264	1.6210	0.3953
0.8795	45.0	270	1.6210	0.3953
0.8795	46.0	276	1.6210	0.3953
0.8368	47.0	282	1.6210	0.3953
0.8368	48.0	288	1.6210	0.3953
0.8886	49.0	294	1.6210	0.3953
0.8644	50.0	300	1.6210	0.3953

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_001_fold3

hushem_1x_beit_base_rms_001_fold3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

hkivancoral/
hushem_1x_beit_base_rms_001_fold3