hushem_5x_beit_base_adamax_00001_fold3

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: 0.4974
• Accuracy: 0.9070

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: 1e-05
• 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
1.2118	1.0	28	1.1325	0.6047
0.7198	2.0	56	0.8388	0.6744
0.3881	3.0	84	0.6224	0.7674
0.2597	4.0	112	0.4679	0.8140
0.1551	5.0	140	0.4682	0.8140
0.1015	6.0	168	0.3870	0.8372
0.0767	7.0	196	0.3615	0.8837
0.0522	8.0	224	0.3630	0.8837
0.0344	9.0	252	0.4112	0.8837
0.0303	10.0	280	0.4026	0.8837
0.0199	11.0	308	0.3842	0.9070
0.0106	12.0	336	0.3943	0.8605
0.0205	13.0	364	0.3879	0.9070
0.008	14.0	392	0.3444	0.8837
0.0066	15.0	420	0.3829	0.9070
0.0068	16.0	448	0.4064	0.8837
0.0104	17.0	476	0.3534	0.9302
0.0048	18.0	504	0.3744	0.9070
0.0062	19.0	532	0.4146	0.9070
0.0025	20.0	560	0.3803	0.9070
0.0032	21.0	588	0.4244	0.9070
0.0031	22.0	616	0.4663	0.9070
0.0021	23.0	644	0.4157	0.9070
0.0026	24.0	672	0.4816	0.9070
0.0013	25.0	700	0.4216	0.9070
0.0017	26.0	728	0.4591	0.9070
0.0021	27.0	756	0.4515	0.9070
0.0024	28.0	784	0.4442	0.8837
0.0026	29.0	812	0.4504	0.9070
0.0009	30.0	840	0.4703	0.9070
0.0047	31.0	868	0.4689	0.9070
0.0067	32.0	896	0.4798	0.9070
0.0009	33.0	924	0.5058	0.9070
0.0013	34.0	952	0.4786	0.9070
0.0022	35.0	980	0.4689	0.9070
0.009	36.0	1008	0.4633	0.9070
0.0009	37.0	1036	0.4823	0.9070
0.0013	38.0	1064	0.4868	0.9070
0.0024	39.0	1092	0.5030	0.9070
0.004	40.0	1120	0.4969	0.9070
0.0014	41.0	1148	0.4951	0.9070
0.0017	42.0	1176	0.4894	0.9070
0.0014	43.0	1204	0.4881	0.9070
0.0013	44.0	1232	0.4878	0.9070
0.0022	45.0	1260	0.4914	0.9070
0.0023	46.0	1288	0.4962	0.9070
0.0015	47.0	1316	0.4961	0.9070
0.0017	48.0	1344	0.4974	0.9070
0.0007	49.0	1372	0.4974	0.9070
0.0006	50.0	1400	0.4974	0.9070

Framework versions

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