hushem_1x_beit_base_rms_0001_fold2

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: 3.2742
• Accuracy: 0.5333

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: 0.0001
• 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	1.4059	0.2444
2.1162	2.0	12	1.4011	0.2444
2.1162	3.0	18	1.4001	0.2444
1.4079	4.0	24	1.4023	0.2444
1.3851	5.0	30	1.3440	0.4
1.3851	6.0	36	1.6621	0.2444
1.3464	7.0	42	1.3490	0.2889
1.3464	8.0	48	1.3162	0.2667
1.2763	9.0	54	1.5389	0.2444
1.2353	10.0	60	1.1918	0.5111
1.2353	11.0	66	1.2702	0.3111
1.1503	12.0	72	1.1819	0.4667
1.1503	13.0	78	1.1946	0.4
1.1428	14.0	84	1.2858	0.4222
0.9448	15.0	90	1.2191	0.5333
0.9448	16.0	96	1.0792	0.4667
0.8793	17.0	102	1.0942	0.5333
0.8793	18.0	108	1.0695	0.5333
0.7925	19.0	114	1.5298	0.4889
0.7637	20.0	120	1.4292	0.4889
0.7637	21.0	126	1.1665	0.4889
0.6936	22.0	132	1.2681	0.4444
0.6936	23.0	138	1.4911	0.4667
0.6862	24.0	144	1.6737	0.4889
0.6196	25.0	150	1.3333	0.5111
0.6196	26.0	156	2.1751	0.4889
0.5849	27.0	162	1.6904	0.4444
0.5849	28.0	168	2.4209	0.5333
0.5413	29.0	174	1.3664	0.4444
0.4937	30.0	180	2.0398	0.5111
0.4937	31.0	186	1.5682	0.5111
0.4704	32.0	192	2.0516	0.5556
0.4704	33.0	198	2.7441	0.5778
0.4133	34.0	204	2.2801	0.5111
0.354	35.0	210	2.5861	0.5333
0.354	36.0	216	2.6593	0.5333
0.3074	37.0	222	2.7263	0.5333
0.3074	38.0	228	2.8622	0.4889
0.2263	39.0	234	3.1445	0.5556
0.2656	40.0	240	3.2265	0.5333
0.2656	41.0	246	3.2774	0.5333
0.2527	42.0	252	3.2742	0.5333
0.2527	43.0	258	3.2742	0.5333
0.2167	44.0	264	3.2742	0.5333
0.2791	45.0	270	3.2742	0.5333
0.2791	46.0	276	3.2742	0.5333
0.2024	47.0	282	3.2742	0.5333
0.2024	48.0	288	3.2742	0.5333
0.2259	49.0	294	3.2742	0.5333
0.2149	50.0	300	3.2742	0.5333

Framework versions

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