hushem_5x_beit_base_adamax_001_fold1

This model is a fine-tuned version of microsoft/beit-base-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

• Loss: 6.2787
• Accuracy: 0.4444

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
1.4418	1.0	27	1.4079	0.2444
1.2606	2.0	54	1.4566	0.4
1.1141	3.0	81	1.4147	0.3111
0.9738	4.0	108	1.7371	0.3556
0.7887	5.0	135	1.5516	0.3778
0.7198	6.0	162	1.3626	0.4
0.8269	7.0	189	1.5448	0.3778
0.8171	8.0	216	1.4576	0.4
0.7255	9.0	243	2.3915	0.3778
0.6369	10.0	270	1.6627	0.3778
0.6809	11.0	297	1.5201	0.3556
0.6237	12.0	324	1.3289	0.4222
0.6768	13.0	351	1.6115	0.3556
0.6336	14.0	378	2.0397	0.3778
0.5238	15.0	405	1.5857	0.3778
0.5016	16.0	432	1.4047	0.4444
0.4321	17.0	459	2.2039	0.3556
0.4791	18.0	486	2.3823	0.3778
0.484	19.0	513	1.4706	0.4222
0.4812	20.0	540	1.6485	0.4222
0.4413	21.0	567	1.7092	0.4
0.4306	22.0	594	1.8582	0.4
0.37	23.0	621	1.8653	0.3778
0.3048	24.0	648	1.6342	0.4444
0.3515	25.0	675	1.5211	0.4889
0.3558	26.0	702	1.9714	0.4222
0.2599	27.0	729	1.7243	0.4667
0.267	28.0	756	1.7049	0.5111
0.2625	29.0	783	2.1704	0.4222
0.2368	30.0	810	2.2942	0.4667
0.2036	31.0	837	2.0691	0.4667
0.1938	32.0	864	2.7340	0.4
0.1597	33.0	891	3.0661	0.4
0.1166	34.0	918	2.8536	0.4667
0.1248	35.0	945	2.9508	0.4444
0.121	36.0	972	3.2153	0.4667
0.0801	37.0	999	3.0021	0.4222
0.0529	38.0	1026	3.3247	0.4222
0.0434	39.0	1053	4.0394	0.4667
0.0599	40.0	1080	4.1062	0.4889
0.0437	41.0	1107	5.3485	0.4667
0.0045	42.0	1134	5.3122	0.4667
0.0368	43.0	1161	5.1937	0.4667
0.0032	44.0	1188	5.6803	0.4889
0.0061	45.0	1215	5.8620	0.4444
0.0035	46.0	1242	5.9016	0.4889
0.0011	47.0	1269	6.3136	0.4444
0.0277	48.0	1296	6.2816	0.4444
0.0067	49.0	1323	6.2787	0.4444
0.0372	50.0	1350	6.2787	0.4444

Framework versions

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