hushem_5x_deit_tiny_sgd_001_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: 1.5326
• 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: 0.001
• 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
1.5319	1.0	27	1.6147	0.1778
1.412	2.0	54	1.5641	0.2222
1.3305	3.0	81	1.5365	0.2
1.301	4.0	108	1.5559	0.2222
1.2455	5.0	135	1.5605	0.2444
1.184	6.0	162	1.5721	0.2444
1.1536	7.0	189	1.5847	0.2444
1.141	8.0	216	1.6070	0.2667
1.0813	9.0	243	1.6240	0.2667
1.0544	10.0	270	1.6212	0.2667
1.0306	11.0	297	1.6262	0.2667
0.9926	12.0	324	1.6270	0.2667
0.9991	13.0	351	1.6433	0.2444
0.9662	14.0	378	1.6269	0.2667
0.9752	15.0	405	1.6379	0.2444
0.9275	16.0	432	1.6386	0.2444
0.9112	17.0	459	1.6378	0.2667
0.8926	18.0	486	1.6345	0.2667
0.8698	19.0	513	1.6300	0.2444
0.8732	20.0	540	1.6217	0.2444
0.8587	21.0	567	1.6212	0.2667
0.8545	22.0	594	1.6207	0.2667
0.8339	23.0	621	1.6201	0.2444
0.8104	24.0	648	1.6072	0.2667
0.7957	25.0	675	1.6070	0.2667
0.8197	26.0	702	1.6043	0.2444
0.8076	27.0	729	1.6022	0.2667
0.7686	28.0	756	1.5925	0.2889
0.7691	29.0	783	1.5965	0.2889
0.7835	30.0	810	1.5836	0.2889
0.7441	31.0	837	1.5828	0.2889
0.7775	32.0	864	1.5709	0.2889
0.7317	33.0	891	1.5664	0.2889
0.7292	34.0	918	1.5626	0.2889
0.7179	35.0	945	1.5496	0.2667
0.7386	36.0	972	1.5502	0.2889
0.7342	37.0	999	1.5475	0.3111
0.734	38.0	1026	1.5457	0.3111
0.7069	39.0	1053	1.5425	0.3111
0.7143	40.0	1080	1.5429	0.3111
0.7105	41.0	1107	1.5401	0.3111
0.7189	42.0	1134	1.5394	0.3111
0.7216	43.0	1161	1.5376	0.3111
0.6896	44.0	1188	1.5358	0.3111
0.7099	45.0	1215	1.5345	0.3111
0.6751	46.0	1242	1.5331	0.3111
0.6824	47.0	1269	1.5327	0.3111
0.7027	48.0	1296	1.5326	0.3111
0.7357	49.0	1323	1.5326	0.3111
0.6799	50.0	1350	1.5326	0.3111

Framework versions

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