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

Loss: 1.3872
Accuracy: 0.1667

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
1.4331	1.0	28	1.4140	0.1429
1.407	2.0	56	1.4126	0.1667
1.4098	3.0	84	1.4112	0.1667
1.4223	4.0	112	1.4100	0.1905
1.4411	5.0	140	1.4087	0.1905
1.4173	6.0	168	1.4075	0.1905
1.4276	7.0	196	1.4064	0.1905
1.4071	8.0	224	1.4054	0.1905
1.3997	9.0	252	1.4043	0.1905
1.3965	10.0	280	1.4034	0.1905
1.3989	11.0	308	1.4024	0.1667
1.3964	12.0	336	1.4014	0.1667
1.3857	13.0	364	1.4005	0.1667
1.3798	14.0	392	1.3997	0.1667
1.3951	15.0	420	1.3990	0.1667
1.4132	16.0	448	1.3982	0.1667
1.4034	17.0	476	1.3975	0.1667
1.3759	18.0	504	1.3968	0.1667
1.3925	19.0	532	1.3961	0.1667
1.3819	20.0	560	1.3955	0.1667
1.3696	21.0	588	1.3949	0.1667
1.369	22.0	616	1.3944	0.1667
1.3858	23.0	644	1.3938	0.1667
1.3737	24.0	672	1.3933	0.1905
1.3918	25.0	700	1.3928	0.1905
1.383	26.0	728	1.3923	0.1905
1.3591	27.0	756	1.3919	0.1905
1.373	28.0	784	1.3914	0.1905
1.3774	29.0	812	1.3910	0.1905
1.4107	30.0	840	1.3906	0.1905
1.3774	31.0	868	1.3903	0.1905
1.372	32.0	896	1.3899	0.1905
1.3576	33.0	924	1.3896	0.1905
1.3584	34.0	952	1.3892	0.1905
1.3749	35.0	980	1.3889	0.1905
1.3548	36.0	1008	1.3887	0.1905
1.3718	37.0	1036	1.3884	0.1905
1.3762	38.0	1064	1.3882	0.1667
1.367	39.0	1092	1.3880	0.1667
1.3764	40.0	1120	1.3878	0.1667
1.3651	41.0	1148	1.3877	0.1667
1.3606	42.0	1176	1.3876	0.1667
1.3658	43.0	1204	1.3874	0.1667
1.3704	44.0	1232	1.3874	0.1667
1.3557	45.0	1260	1.3873	0.1667
1.3731	46.0	1288	1.3872	0.1667
1.3663	47.0	1316	1.3872	0.1667
1.3426	48.0	1344	1.3872	0.1667
1.3656	49.0	1372	1.3872	0.1667
1.3695	50.0	1400	1.3872	0.1667

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0

hkivancoral/hushem_5x_deit_base_sgd_0001_fold4

hushem_5x_deit_base_sgd_0001_fold4

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

hkivancoral/
hushem_5x_deit_base_sgd_0001_fold4