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

Loss: 1.1786
Accuracy: 0.8567

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
0.6005	1.0	75	0.4146	0.83
0.4739	2.0	150	0.5214	0.7783
0.3159	3.0	225	0.3979	0.8467
0.3044	4.0	300	0.4320	0.845
0.3525	5.0	375	0.3215	0.8817
0.1872	6.0	450	0.4978	0.8267
0.2467	7.0	525	0.5551	0.8
0.1504	8.0	600	0.5301	0.8367
0.1309	9.0	675	0.5781	0.84
0.2177	10.0	750	0.5269	0.865
0.0844	11.0	825	0.5112	0.865
0.0758	12.0	900	0.6543	0.8617
0.1176	13.0	975	0.5860	0.855
0.0455	14.0	1050	0.7995	0.8317
0.0687	15.0	1125	0.6395	0.8633
0.0296	16.0	1200	0.8580	0.8517
0.0214	17.0	1275	0.9274	0.85
0.0164	18.0	1350	0.8318	0.8733
0.0192	19.0	1425	0.9491	0.8567
0.0338	20.0	1500	0.7653	0.8567
0.0007	21.0	1575	0.9985	0.8517
0.0001	22.0	1650	0.9967	0.87
0.0156	23.0	1725	1.1459	0.85
0.0033	24.0	1800	1.1111	0.8517
0.005	25.0	1875	1.1114	0.8467
0.0195	26.0	1950	1.0184	0.8617
0.0001	27.0	2025	1.0582	0.8567
0.0022	28.0	2100	1.1162	0.86
0.0	29.0	2175	1.1193	0.86
0.0	30.0	2250	1.1254	0.8567
0.0	31.0	2325	1.1372	0.86
0.0016	32.0	2400	1.1758	0.8583
0.0051	33.0	2475	1.1778	0.845
0.0047	34.0	2550	1.0600	0.8667
0.01	35.0	2625	1.1195	0.855
0.0037	36.0	2700	1.1381	0.8533
0.0025	37.0	2775	1.1434	0.855
0.0	38.0	2850	1.1612	0.8583
0.0	39.0	2925	1.1652	0.8567
0.0	40.0	3000	1.1711	0.855
0.0	41.0	3075	1.1589	0.86
0.0028	42.0	3150	1.1617	0.8617
0.0032	43.0	3225	1.1622	0.86
0.0	44.0	3300	1.1672	0.86
0.0027	45.0	3375	1.1668	0.86
0.0026	46.0	3450	1.1710	0.86
0.0057	47.0	3525	1.1686	0.86
0.0	48.0	3600	1.1767	0.8567
0.0	49.0	3675	1.1760	0.8583
0.0044	50.0	3750	1.1786	0.8567

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0

hkivancoral/smids_1x_deit_small_adamax_001_fold3

smids_1x_deit_small_adamax_001_fold3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

hkivancoral/
smids_1x_deit_small_adamax_001_fold3