hushem_1x_beit_base_rms_001_fold5

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: 1.0249
• Accuracy: 0.5610

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
No log	1.0	6	4.0765	0.2683
4.3424	2.0	12	1.4584	0.2439
4.3424	3.0	18	1.4177	0.2439
1.6981	4.0	24	1.4396	0.2439
1.439	5.0	30	1.4302	0.2439
1.439	6.0	36	1.4113	0.2683
1.4514	7.0	42	1.4298	0.2439
1.4514	8.0	48	1.4142	0.2683
1.4037	9.0	54	1.3909	0.2683
1.4226	10.0	60	1.3819	0.2683
1.4226	11.0	66	1.3922	0.2683
1.3954	12.0	72	1.3475	0.2195
1.3954	13.0	78	1.3669	0.2439
1.4193	14.0	84	1.3582	0.2683
1.3817	15.0	90	1.3869	0.2439
1.3817	16.0	96	1.6362	0.2439
1.3794	17.0	102	1.4473	0.2439
1.3794	18.0	108	1.3118	0.4146
1.3773	19.0	114	1.3101	0.3415
1.3081	20.0	120	1.4119	0.2439
1.3081	21.0	126	1.2040	0.4634
1.2767	22.0	132	2.0544	0.2439
1.2767	23.0	138	1.2316	0.3415
1.3145	24.0	144	1.3728	0.2683
1.2519	25.0	150	1.3114	0.2927
1.2519	26.0	156	1.1523	0.5122
1.2177	27.0	162	1.1097	0.4634
1.2177	28.0	168	1.2516	0.3902
1.1299	29.0	174	1.1372	0.4390
1.1588	30.0	180	1.1704	0.4146
1.1588	31.0	186	1.0311	0.5610
1.1686	32.0	192	1.0730	0.4634
1.1686	33.0	198	1.0832	0.4634
1.038	34.0	204	1.1414	0.4878
1.0117	35.0	210	0.9564	0.6585
1.0117	36.0	216	1.1782	0.4146
1.0097	37.0	222	1.0629	0.5122
1.0097	38.0	228	1.0278	0.4634
0.9459	39.0	234	1.0014	0.5610
0.8786	40.0	240	0.9935	0.5854
0.8786	41.0	246	1.0190	0.5610
0.8792	42.0	252	1.0249	0.5610
0.8792	43.0	258	1.0249	0.5610
0.7834	44.0	264	1.0249	0.5610
0.8444	45.0	270	1.0249	0.5610
0.8444	46.0	276	1.0249	0.5610
0.8306	47.0	282	1.0249	0.5610
0.8306	48.0	288	1.0249	0.5610
0.8546	49.0	294	1.0249	0.5610
0.8485	50.0	300	1.0249	0.5610

Framework versions

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