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: 0.9763
Accuracy: 0.86

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
0.7004	1.0	75	0.6502	0.7417
0.5011	2.0	150	0.4927	0.795
0.387	3.0	225	0.4418	0.8133
0.32	4.0	300	0.4153	0.835
0.2817	5.0	375	0.4075	0.8333
0.2233	6.0	450	0.3963	0.8433
0.2099	7.0	525	0.3993	0.8517
0.1587	8.0	600	0.4089	0.8517
0.1492	9.0	675	0.4263	0.8533
0.1374	10.0	750	0.4223	0.86
0.1106	11.0	825	0.4566	0.8533
0.0777	12.0	900	0.4729	0.8433
0.0787	13.0	975	0.4848	0.8567
0.0407	14.0	1050	0.5231	0.85
0.0237	15.0	1125	0.5607	0.8533
0.0206	16.0	1200	0.6045	0.8483
0.0395	17.0	1275	0.6305	0.855
0.0399	18.0	1350	0.6575	0.85
0.0183	19.0	1425	0.7037	0.8467
0.0153	20.0	1500	0.7259	0.855
0.005	21.0	1575	0.7531	0.85
0.0017	22.0	1650	0.7833	0.85
0.0025	23.0	1725	0.8056	0.8467
0.0157	24.0	1800	0.8300	0.855
0.007	25.0	1875	0.8590	0.85
0.0006	26.0	1950	0.8573	0.8483
0.0006	27.0	2025	0.8637	0.8483
0.0055	28.0	2100	0.8671	0.8533
0.0223	29.0	2175	0.8791	0.85
0.0007	30.0	2250	0.8908	0.845
0.0004	31.0	2325	0.8875	0.85
0.0003	32.0	2400	0.8993	0.8533
0.0004	33.0	2475	0.9065	0.8517
0.0002	34.0	2550	0.9107	0.855
0.0003	35.0	2625	0.9197	0.855
0.0002	36.0	2700	0.9278	0.8517
0.02	37.0	2775	0.9327	0.8633
0.0002	38.0	2850	0.9380	0.8617
0.0002	39.0	2925	0.9441	0.8567
0.0003	40.0	3000	0.9479	0.86
0.0203	41.0	3075	0.9563	0.8583
0.0002	42.0	3150	0.9601	0.86
0.0002	43.0	3225	0.9632	0.86
0.0002	44.0	3300	0.9684	0.8533
0.0002	45.0	3375	0.9703	0.86
0.0002	46.0	3450	0.9720	0.86
0.0002	47.0	3525	0.9736	0.86
0.0002	48.0	3600	0.9753	0.86
0.0001	49.0	3675	0.9759	0.86
0.0001	50.0	3750	0.9763	0.86

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0

hkivancoral/smids_1x_deit_tiny_adamax_00001_fold4

smids_1x_deit_tiny_adamax_00001_fold4

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

hkivancoral/
smids_1x_deit_tiny_adamax_00001_fold4