hushem_40x_beit_large_adamax_001_fold1

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

• Loss: 3.2476
• Accuracy: 0.7333

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
0.3238	1.0	215	0.6915	0.7333
0.1477	2.0	430	1.2081	0.6444
0.0434	3.0	645	1.8202	0.6444
0.0459	4.0	860	1.9604	0.6222
0.0376	5.0	1075	0.7965	0.7778
0.0151	6.0	1290	1.6449	0.7111
0.0084	7.0	1505	2.7172	0.6222
0.0085	8.0	1720	2.4588	0.6667
0.0105	9.0	1935	3.0173	0.5333
0.0465	10.0	2150	1.5242	0.7778
0.0056	11.0	2365	2.2494	0.7333
0.0106	12.0	2580	2.3865	0.6889
0.0614	13.0	2795	1.3048	0.7778
0.0068	14.0	3010	2.7128	0.6889
0.0	15.0	3225	2.3042	0.7778
0.0001	16.0	3440	2.6333	0.7333
0.0483	17.0	3655	2.9792	0.7111
0.0	18.0	3870	2.6692	0.7111
0.0	19.0	4085	2.7990	0.7556
0.0	20.0	4300	2.7968	0.7333
0.0	21.0	4515	2.8289	0.7333
0.0	22.0	4730	2.8734	0.7333
0.0	23.0	4945	2.7220	0.7556
0.0742	24.0	5160	2.8716	0.7111
0.0011	25.0	5375	2.8927	0.7333
0.0	26.0	5590	2.8101	0.7333
0.0	27.0	5805	2.9619	0.7111
0.0	28.0	6020	3.0313	0.7111
0.0	29.0	6235	3.1395	0.7111
0.0	30.0	6450	3.4589	0.7111
0.0	31.0	6665	3.5502	0.6889
0.0	32.0	6880	3.7038	0.6667
0.0	33.0	7095	2.9949	0.7111
0.0	34.0	7310	3.0364	0.7111
0.0	35.0	7525	3.1096	0.7111
0.0	36.0	7740	3.1633	0.7333
0.0	37.0	7955	3.1868	0.7333
0.0	38.0	8170	3.2061	0.7333
0.0	39.0	8385	3.2444	0.7333
0.0	40.0	8600	3.2660	0.7333
0.0	41.0	8815	3.2861	0.7333
0.0	42.0	9030	3.3090	0.7333
0.0	43.0	9245	3.3340	0.7333
0.0	44.0	9460	3.3547	0.7333
0.0	45.0	9675	3.3742	0.7333
0.0	46.0	9890	3.3879	0.7333
0.0	47.0	10105	3.4047	0.7333
0.0	48.0	10320	3.2184	0.7333
0.0	49.0	10535	3.2219	0.7333
0.0	50.0	10750	3.2476	0.7333

Framework versions

• Transformers 4.32.1
• Pytorch 2.1.0+cu121
• Datasets 2.12.0
• Tokenizers 0.13.2