hushem_1x_deit_tiny_sgd_lr00001_fold2

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: 1.6351
• Accuracy: 0.1333

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
No log	1.0	6	1.6407	0.1333
1.6149	2.0	12	1.6404	0.1333
1.6149	3.0	18	1.6401	0.1333
1.588	4.0	24	1.6398	0.1333
1.6243	5.0	30	1.6396	0.1333
1.6243	6.0	36	1.6393	0.1333
1.6041	7.0	42	1.6390	0.1333
1.6041	8.0	48	1.6388	0.1333
1.5784	9.0	54	1.6386	0.1333
1.61	10.0	60	1.6383	0.1333
1.61	11.0	66	1.6381	0.1333
1.5857	12.0	72	1.6379	0.1333
1.5857	13.0	78	1.6377	0.1333
1.6282	14.0	84	1.6375	0.1333
1.5739	15.0	90	1.6373	0.1333
1.5739	16.0	96	1.6372	0.1333
1.5784	17.0	102	1.6370	0.1333
1.5784	18.0	108	1.6368	0.1333
1.6525	19.0	114	1.6367	0.1333
1.5978	20.0	120	1.6365	0.1333
1.5978	21.0	126	1.6364	0.1333
1.6239	22.0	132	1.6362	0.1333
1.6239	23.0	138	1.6361	0.1333
1.581	24.0	144	1.6360	0.1333
1.597	25.0	150	1.6359	0.1333
1.597	26.0	156	1.6358	0.1333
1.5864	27.0	162	1.6357	0.1333
1.5864	28.0	168	1.6356	0.1333
1.6236	29.0	174	1.6355	0.1333
1.6201	30.0	180	1.6354	0.1333
1.6201	31.0	186	1.6354	0.1333
1.6018	32.0	192	1.6353	0.1333
1.6018	33.0	198	1.6352	0.1333
1.5711	34.0	204	1.6352	0.1333
1.6003	35.0	210	1.6352	0.1333
1.6003	36.0	216	1.6351	0.1333
1.5762	37.0	222	1.6351	0.1333
1.5762	38.0	228	1.6351	0.1333
1.5979	39.0	234	1.6351	0.1333
1.6035	40.0	240	1.6351	0.1333
1.6035	41.0	246	1.6351	0.1333
1.5976	42.0	252	1.6351	0.1333
1.5976	43.0	258	1.6351	0.1333
1.5981	44.0	264	1.6351	0.1333
1.5912	45.0	270	1.6351	0.1333
1.5912	46.0	276	1.6351	0.1333
1.5981	47.0	282	1.6351	0.1333
1.5981	48.0	288	1.6351	0.1333
1.6158	49.0	294	1.6351	0.1333
1.593	50.0	300	1.6351	0.1333

Framework versions

• Transformers 4.35.0
• Pytorch 2.1.0+cu118
• Datasets 2.14.6
• Tokenizers 0.14.1