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sbaner24/
vit-base-patch16-224-Trial006-007-008-YEL_STEM4

Name: vit-base-patch16-224-Trial006-007-008-YEL_STEM4
Availability: InStock

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vit-base-patch16-224-Trial006-007-008-YEL_STEM4

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

Loss: 0.1729
Accuracy: 0.9355

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: 5e-05
train_batch_size: 60
eval_batch_size: 60
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 240
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
0.6572	1.0	6	0.6719	0.5677
0.6279	2.0	12	0.6436	0.6516
0.5282	3.0	18	0.5677	0.7871
0.5405	4.0	24	0.4718	0.8258
0.5276	5.0	30	0.4959	0.7419
0.412	6.0	36	0.3081	0.8581
0.3011	7.0	42	0.2542	0.8839
0.3329	8.0	48	0.2350	0.8774
0.4478	9.0	54	0.1743	0.9290
0.268	10.0	60	0.1708	0.9161
0.2177	11.0	66	0.1729	0.9355
0.2675	12.0	72	0.1913	0.8968
0.4784	13.0	78	0.1826	0.9032
0.2456	14.0	84	0.1774	0.9032
0.6229	15.0	90	0.2196	0.8968
0.2561	16.0	96	0.1823	0.9226
0.3785	17.0	102	0.1770	0.9032
0.2334	18.0	108	0.2056	0.8903
0.1904	19.0	114	0.1564	0.9097
0.2256	20.0	120	0.1407	0.9226
0.2547	21.0	126	0.1552	0.9032
0.3468	22.0	132	0.1819	0.8968
0.4116	23.0	138	0.1537	0.9290
0.3689	24.0	144	0.1645	0.9097
0.3541	25.0	150	0.1527	0.9290
0.2498	26.0	156	0.1670	0.9161
0.3625	27.0	162	0.1522	0.9161
0.2463	28.0	168	0.1552	0.9226
0.3447	29.0	174	0.1510	0.9097
0.205	30.0	180	0.1924	0.9032
0.2023	31.0	186	0.1376	0.9355
0.3617	32.0	192	0.1518	0.9097
0.3515	33.0	198	0.1473	0.9097
0.1927	34.0	204	0.1544	0.9097
0.4567	35.0	210	0.1528	0.9097
0.3113	36.0	216	0.1510	0.9226
0.3475	37.0	222	0.1594	0.9161
0.1889	38.0	228	0.1448	0.9290
0.1979	39.0	234	0.1533	0.9226
0.3578	40.0	240	0.1627	0.9097
0.2004	41.0	246	0.1620	0.9161
0.3567	42.0	252	0.1475	0.9226
0.192	43.0	258	0.1504	0.9032
0.1872	44.0	264	0.1535	0.9097
0.2079	45.0	270	0.1490	0.9161
0.1503	46.0	276	0.1459	0.9161
0.169	47.0	282	0.1506	0.8968
0.1884	48.0	288	0.1556	0.8968
0.1638	49.0	294	0.1573	0.8968
0.1921	50.0	300	0.1570	0.8968

Framework versions

Transformers 4.30.0.dev0
Pytorch 1.12.1
Datasets 2.12.0
Tokenizers 0.13.1

sbaner24/vit-base-patch16-224-Trial006-007-008-YEL_STEM4

vit-base-patch16-224-Trial006-007-008-YEL_STEM4

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

sbaner24/
vit-base-patch16-224-Trial006-007-008-YEL_STEM4