hushem_1x_deit_small_rms_001_fold4

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: 1.2235
• Accuracy: 0.4048

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	6.3906	0.2381
3.8063	2.0	12	1.7015	0.2619
3.8063	3.0	18	2.0641	0.2619
1.9221	4.0	24	1.7697	0.2381
1.6782	5.0	30	1.4022	0.2619
1.6782	6.0	36	1.7511	0.2381
1.5442	7.0	42	1.4627	0.2381
1.5442	8.0	48	1.4402	0.2619
1.4869	9.0	54	1.4717	0.2619
1.4572	10.0	60	1.4285	0.2381
1.4572	11.0	66	1.4073	0.2619
1.4861	12.0	72	1.4071	0.3095
1.4861	13.0	78	1.3676	0.3095
1.4283	14.0	84	1.4281	0.2381
1.4135	15.0	90	1.4437	0.2381
1.4135	16.0	96	1.3561	0.3095
1.375	17.0	102	1.3574	0.2857
1.375	18.0	108	1.2368	0.2857
1.3639	19.0	114	1.4601	0.2857
1.2891	20.0	120	1.7927	0.2381
1.2891	21.0	126	1.2451	0.4048
1.3173	22.0	132	1.1578	0.4762
1.3173	23.0	138	1.3222	0.3095
1.2505	24.0	144	1.3748	0.2381
1.263	25.0	150	1.3699	0.2857
1.263	26.0	156	1.2508	0.3810
1.2132	27.0	162	1.1843	0.4048
1.2132	28.0	168	1.4161	0.2619
1.1485	29.0	174	1.1305	0.4524
1.181	30.0	180	1.1818	0.4524
1.181	31.0	186	1.2906	0.4048
1.131	32.0	192	1.1623	0.4762
1.131	33.0	198	1.2826	0.4524
1.164	34.0	204	1.1932	0.4524
1.0879	35.0	210	1.1104	0.4286
1.0879	36.0	216	1.0661	0.5714
1.1012	37.0	222	1.2594	0.4048
1.1012	38.0	228	1.1459	0.4286
1.0505	39.0	234	1.1918	0.4524
1.0052	40.0	240	1.2662	0.4286
1.0052	41.0	246	1.2165	0.4048
0.9631	42.0	252	1.2235	0.4048
0.9631	43.0	258	1.2235	0.4048
0.9397	44.0	264	1.2235	0.4048
0.9545	45.0	270	1.2235	0.4048
0.9545	46.0	276	1.2235	0.4048
0.9591	47.0	282	1.2235	0.4048
0.9591	48.0	288	1.2235	0.4048
0.9579	49.0	294	1.2235	0.4048
0.9362	50.0	300	1.2235	0.4048

Framework versions

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