hushem_1x_beit_base_adamax_001_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: 1.8097
• Accuracy: 0.5349

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	1.4381	0.2326
2.0527	2.0	12	1.4022	0.2558
2.0527	3.0	18	1.3682	0.3256
1.3782	4.0	24	1.3387	0.3953
1.2679	5.0	30	1.3721	0.3256
1.2679	6.0	36	1.7451	0.3488
1.2756	7.0	42	1.3183	0.3953
1.2756	8.0	48	1.4225	0.3023
1.173	9.0	54	1.4215	0.3953
1.1959	10.0	60	1.4072	0.3721
1.1959	11.0	66	1.4852	0.4186
1.1344	12.0	72	1.4523	0.2791
1.1344	13.0	78	1.4043	0.4651
1.0854	14.0	84	1.3638	0.3953
1.1124	15.0	90	1.4323	0.3953
1.1124	16.0	96	1.4664	0.4884
1.0108	17.0	102	1.5473	0.3721
1.0108	18.0	108	1.2300	0.4651
0.9443	19.0	114	1.2523	0.4419
0.9125	20.0	120	1.4134	0.3721
0.9125	21.0	126	1.1280	0.4884
0.8328	22.0	132	1.1054	0.4884
0.8328	23.0	138	1.6081	0.4419
0.7565	24.0	144	1.0331	0.5349
0.7135	25.0	150	1.6384	0.5116
0.7135	26.0	156	1.9524	0.4651
0.7048	27.0	162	1.1399	0.5349
0.7048	28.0	168	1.0504	0.5581
0.7074	29.0	174	1.0452	0.5581
0.7008	30.0	180	1.4757	0.5581
0.7008	31.0	186	1.0663	0.4419
0.5976	32.0	192	1.0991	0.5349
0.5976	33.0	198	1.5330	0.5814
0.5565	34.0	204	1.1511	0.5349
0.458	35.0	210	1.5836	0.5349
0.458	36.0	216	1.4225	0.5581
0.5542	37.0	222	1.4182	0.6047
0.5542	38.0	228	1.3407	0.5581
0.3706	39.0	234	1.4368	0.5581
0.3087	40.0	240	1.6899	0.5814
0.3087	41.0	246	1.8110	0.5116
0.3001	42.0	252	1.8097	0.5349
0.3001	43.0	258	1.8097	0.5349
0.3061	44.0	264	1.8097	0.5349
0.2986	45.0	270	1.8097	0.5349
0.2986	46.0	276	1.8097	0.5349
0.2791	47.0	282	1.8097	0.5349
0.2791	48.0	288	1.8097	0.5349
0.2908	49.0	294	1.8097	0.5349
0.2986	50.0	300	1.8097	0.5349

Framework versions

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