hushem_5x_deit_small_sgd_0001_fold1

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: 1.3695
• Accuracy: 0.3111

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: 0.0001
• 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
1.5195	1.0	27	1.4999	0.2889
1.4914	2.0	54	1.4892	0.2889
1.5108	3.0	81	1.4789	0.2889
1.5345	4.0	108	1.4698	0.2667
1.4684	5.0	135	1.4617	0.2667
1.4525	6.0	162	1.4534	0.2667
1.4298	7.0	189	1.4465	0.2667
1.4569	8.0	216	1.4397	0.2444
1.4283	9.0	243	1.4337	0.2444
1.4203	10.0	270	1.4280	0.2444
1.3871	11.0	297	1.4228	0.2444
1.4156	12.0	324	1.4180	0.2444
1.4346	13.0	351	1.4134	0.2444
1.4076	14.0	378	1.4093	0.2444
1.425	15.0	405	1.4059	0.2444
1.4406	16.0	432	1.4025	0.2444
1.4069	17.0	459	1.3996	0.2444
1.3779	18.0	486	1.3968	0.2444
1.3991	19.0	513	1.3941	0.2667
1.3962	20.0	540	1.3918	0.2667
1.3954	21.0	567	1.3897	0.2889
1.3886	22.0	594	1.3877	0.2889
1.3775	23.0	621	1.3858	0.2889
1.3714	24.0	648	1.3842	0.2889
1.4056	25.0	675	1.3826	0.2889
1.4026	26.0	702	1.3812	0.2889
1.359	27.0	729	1.3799	0.2889
1.3709	28.0	756	1.3787	0.2889
1.3667	29.0	783	1.3776	0.2889
1.3672	30.0	810	1.3766	0.2889
1.3762	31.0	837	1.3757	0.2889
1.3384	32.0	864	1.3749	0.2889
1.3698	33.0	891	1.3742	0.2889
1.3636	34.0	918	1.3735	0.3111
1.3439	35.0	945	1.3729	0.3111
1.3571	36.0	972	1.3723	0.3111
1.3688	37.0	999	1.3718	0.3111
1.3527	38.0	1026	1.3714	0.3111
1.3641	39.0	1053	1.3710	0.3111
1.3538	40.0	1080	1.3707	0.3111
1.3693	41.0	1107	1.3704	0.3111
1.3789	42.0	1134	1.3701	0.3111
1.3917	43.0	1161	1.3699	0.3111
1.3524	44.0	1188	1.3698	0.3111
1.367	45.0	1215	1.3696	0.3111
1.3553	46.0	1242	1.3696	0.3111
1.3523	47.0	1269	1.3695	0.3111
1.3646	48.0	1296	1.3695	0.3111
1.3891	49.0	1323	1.3695	0.3111
1.3396	50.0	1350	1.3695	0.3111

Framework versions

• Transformers 4.35.2
• Pytorch 2.1.0+cu118
• Datasets 2.15.0
• Tokenizers 0.15.0