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: 1.4354
Accuracy: 0.2857

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	1.4991	0.2857
1.6033	2.0	12	1.4950	0.2857
1.6033	3.0	18	1.4913	0.2857
1.56	4.0	24	1.4878	0.2857
1.5624	5.0	30	1.4847	0.2857
1.5624	6.0	36	1.4813	0.2857
1.5652	7.0	42	1.4787	0.2857
1.5652	8.0	48	1.4758	0.2857
1.5644	9.0	54	1.4729	0.2857
1.5444	10.0	60	1.4702	0.2857
1.5444	11.0	66	1.4678	0.2857
1.5307	12.0	72	1.4653	0.2857
1.5307	13.0	78	1.4629	0.2857
1.518	14.0	84	1.4606	0.2857
1.5309	15.0	90	1.4585	0.2857
1.5309	16.0	96	1.4564	0.2857
1.5513	17.0	102	1.4547	0.2857
1.5513	18.0	108	1.4530	0.2857
1.5683	19.0	114	1.4515	0.2857
1.533	20.0	120	1.4498	0.2857
1.533	21.0	126	1.4484	0.2857
1.5308	22.0	132	1.4473	0.2857
1.5308	23.0	138	1.4462	0.2857
1.5033	24.0	144	1.4450	0.2857
1.4859	25.0	150	1.4438	0.2857
1.4859	26.0	156	1.4427	0.2857
1.5126	27.0	162	1.4416	0.2857
1.5126	28.0	168	1.4408	0.2857
1.5334	29.0	174	1.4400	0.2857
1.5073	30.0	180	1.4393	0.2857
1.5073	31.0	186	1.4387	0.2857
1.4951	32.0	192	1.4381	0.2857
1.4951	33.0	198	1.4376	0.2857
1.5148	34.0	204	1.4371	0.2857
1.5182	35.0	210	1.4366	0.2857
1.5182	36.0	216	1.4363	0.2857
1.5025	37.0	222	1.4360	0.2857
1.5025	38.0	228	1.4357	0.2857
1.5134	39.0	234	1.4356	0.2857
1.5013	40.0	240	1.4354	0.2857
1.5013	41.0	246	1.4354	0.2857
1.501	42.0	252	1.4354	0.2857
1.501	43.0	258	1.4354	0.2857
1.5486	44.0	264	1.4354	0.2857
1.4725	45.0	270	1.4354	0.2857
1.4725	46.0	276	1.4354	0.2857
1.4918	47.0	282	1.4354	0.2857
1.4918	48.0	288	1.4354	0.2857
1.5174	49.0	294	1.4354	0.2857
1.5195	50.0	300	1.4354	0.2857

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0

hkivancoral/hushem_1x_beit_base_sgd_0001_fold4

hushem_1x_beit_base_sgd_0001_fold4

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

hkivancoral/
hushem_1x_beit_base_sgd_0001_fold4