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

Loss: 0.9428
Accuracy: 0.8140

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: 1e-05
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
1.0538	1.0	28	0.9038	0.5581
0.398	2.0	56	0.5639	0.8140
0.1369	3.0	84	0.4267	0.8372
0.0653	4.0	112	0.4017	0.8140
0.0168	5.0	140	0.6872	0.7209
0.0118	6.0	168	0.5013	0.8140
0.0023	7.0	196	0.4979	0.8140
0.0012	8.0	224	0.5003	0.8372
0.0008	9.0	252	0.5851	0.7907
0.0005	10.0	280	0.5426	0.8372
0.0005	11.0	308	0.5660	0.8140
0.0004	12.0	336	0.6863	0.8140
0.0003	13.0	364	0.6233	0.8140
0.0003	14.0	392	0.6061	0.8372
0.0002	15.0	420	0.6182	0.8372
0.0002	16.0	448	0.6408	0.8372
0.0002	17.0	476	0.6614	0.8372
0.0001	18.0	504	0.6673	0.8372
0.0001	19.0	532	0.6855	0.8372
0.0001	20.0	560	0.6977	0.8372
0.0001	21.0	588	0.7002	0.8372
0.0001	22.0	616	0.7103	0.8372
0.0001	23.0	644	0.7324	0.8372
0.0001	24.0	672	0.7411	0.8372
0.0001	25.0	700	0.7527	0.8372
0.0	26.0	728	0.7686	0.8372
0.0	27.0	756	0.8040	0.8140
0.0	28.0	784	0.7774	0.8372
0.0	29.0	812	0.8203	0.8372
0.0	30.0	840	0.8005	0.8372
0.0	31.0	868	0.8113	0.8372
0.0	32.0	896	0.8306	0.8372
0.0	33.0	924	0.8462	0.8140
0.0	34.0	952	0.8513	0.8140
0.0	35.0	980	0.8701	0.8140
0.0	36.0	1008	0.8672	0.8140
0.0	37.0	1036	0.8573	0.8372
0.0	38.0	1064	0.8825	0.8372
0.0	39.0	1092	0.8710	0.8372
0.0	40.0	1120	0.9055	0.8372
0.0	41.0	1148	0.9033	0.8140
0.0	42.0	1176	0.9214	0.8372
0.0	43.0	1204	0.9275	0.8140
0.0	44.0	1232	0.9420	0.8140
0.0	45.0	1260	0.9318	0.8372
0.0	46.0	1288	0.9417	0.8140
0.0	47.0	1316	0.9424	0.8140
0.0	48.0	1344	0.9429	0.8140
0.0	49.0	1372	0.9428	0.8140
0.0	50.0	1400	0.9428	0.8140

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0

hkivancoral/hushem_5x_deit_tiny_rms_00001_fold3

hushem_5x_deit_tiny_rms_00001_fold3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

hkivancoral/
hushem_5x_deit_tiny_rms_00001_fold3