hushem_1x_deit_base_sgd_001_fold1

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: 1.4169
• Accuracy: 0.2222

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
No log	1.0	6	1.5144	0.1333
1.4099	2.0	12	1.5058	0.1333
1.4099	3.0	18	1.4975	0.1333
1.3953	4.0	24	1.4914	0.1333
1.3839	5.0	30	1.4843	0.1556
1.3839	6.0	36	1.4779	0.1778
1.3707	7.0	42	1.4724	0.1778
1.3707	8.0	48	1.4679	0.1778
1.3722	9.0	54	1.4633	0.1778
1.3434	10.0	60	1.4589	0.1778
1.3434	11.0	66	1.4552	0.2
1.3467	12.0	72	1.4521	0.2
1.3467	13.0	78	1.4488	0.2
1.3313	14.0	84	1.4460	0.2
1.33	15.0	90	1.4434	0.2
1.33	16.0	96	1.4413	0.2
1.325	17.0	102	1.4392	0.2
1.325	18.0	108	1.4371	0.2
1.3231	19.0	114	1.4349	0.2222
1.3131	20.0	120	1.4330	0.2222
1.3131	21.0	126	1.4314	0.2444
1.3095	22.0	132	1.4300	0.2444
1.3095	23.0	138	1.4284	0.2444
1.3181	24.0	144	1.4271	0.2444
1.2959	25.0	150	1.4260	0.2222
1.2959	26.0	156	1.4247	0.2222
1.2924	27.0	162	1.4239	0.2222
1.2924	28.0	168	1.4230	0.2222
1.2867	29.0	174	1.4221	0.2222
1.2887	30.0	180	1.4212	0.2222
1.2887	31.0	186	1.4204	0.2222
1.2851	32.0	192	1.4198	0.2222
1.2851	33.0	198	1.4193	0.2222
1.2896	34.0	204	1.4187	0.2222
1.2742	35.0	210	1.4183	0.2222
1.2742	36.0	216	1.4179	0.2222
1.2726	37.0	222	1.4176	0.2222
1.2726	38.0	228	1.4173	0.2222
1.2881	39.0	234	1.4171	0.2222
1.2721	40.0	240	1.4170	0.2222
1.2721	41.0	246	1.4169	0.2222
1.2788	42.0	252	1.4169	0.2222
1.2788	43.0	258	1.4169	0.2222
1.2737	44.0	264	1.4169	0.2222
1.2763	45.0	270	1.4169	0.2222
1.2763	46.0	276	1.4169	0.2222
1.2804	47.0	282	1.4169	0.2222
1.2804	48.0	288	1.4169	0.2222
1.2603	49.0	294	1.4169	0.2222
1.275	50.0	300	1.4169	0.2222

Framework versions

• Transformers 4.35.2
• Pytorch 2.1.0+cu118
• Datasets 2.14.7
• Tokenizers 0.15.0