hushem_40x_deit_base_rms_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: 7.0637
• Accuracy: 0.5333

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
1.3874	1.0	215	1.5845	0.2667
1.2829	2.0	430	1.2221	0.4
0.7962	3.0	645	2.1065	0.4
0.7528	4.0	860	1.0651	0.5556
0.6029	5.0	1075	1.5642	0.4889
0.6246	6.0	1290	1.7962	0.4222
0.589	7.0	1505	1.4819	0.4444
0.6081	8.0	1720	1.4452	0.4222
0.4808	9.0	1935	1.4389	0.4444
0.4155	10.0	2150	1.7698	0.4667
0.4393	11.0	2365	1.4569	0.5778
0.4007	12.0	2580	2.1115	0.4
0.3758	13.0	2795	1.5230	0.5556
0.3244	14.0	3010	2.2901	0.4444
0.3063	15.0	3225	2.0129	0.4889
0.3072	16.0	3440	2.2969	0.5333
0.2444	17.0	3655	2.5054	0.4667
0.2293	18.0	3870	2.3449	0.4889
0.2391	19.0	4085	2.0401	0.6444
0.1843	20.0	4300	2.7271	0.5333
0.2073	21.0	4515	2.2599	0.4889
0.194	22.0	4730	3.1378	0.4444
0.2943	23.0	4945	2.7236	0.5333
0.2089	24.0	5160	2.5054	0.5778
0.2145	25.0	5375	3.8073	0.4667
0.1232	26.0	5590	3.5697	0.4889
0.1349	27.0	5805	3.5985	0.5333
0.1548	28.0	6020	3.0930	0.4889
0.0655	29.0	6235	4.3232	0.4889
0.1304	30.0	6450	3.6994	0.5333
0.0997	31.0	6665	3.7329	0.5333
0.0825	32.0	6880	3.4793	0.5333
0.154	33.0	7095	5.2562	0.4667
0.1206	34.0	7310	4.5299	0.4889
0.1019	35.0	7525	3.6522	0.5111
0.019	36.0	7740	3.9235	0.5333
0.0485	37.0	7955	4.7342	0.5556
0.0155	38.0	8170	4.4779	0.5778
0.0142	39.0	8385	4.2139	0.5556
0.0256	40.0	8600	5.0724	0.5333
0.0211	41.0	8815	4.8895	0.4889
0.019	42.0	9030	4.8291	0.5556
0.0047	43.0	9245	5.9102	0.5333
0.0027	44.0	9460	5.9480	0.5556
0.0009	45.0	9675	6.2260	0.5333
0.0008	46.0	9890	6.6029	0.5556
0.0001	47.0	10105	6.7925	0.5556
0.0001	48.0	10320	6.7039	0.5333
0.0	49.0	10535	7.0556	0.5333
0.0001	50.0	10750	7.0637	0.5333

Framework versions

• Transformers 4.32.1
• Pytorch 2.1.0+cu121
• Datasets 2.12.0
• Tokenizers 0.13.2