hushem_1x_deit_tiny_adamax_001_fold1

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

• Loss: 1.8804
• Accuracy: 0.5778

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	1.3266	0.3778
1.1956	2.0	12	1.1674	0.4667
1.1956	3.0	18	1.1849	0.4889
0.4784	4.0	24	1.2723	0.4667
0.1535	5.0	30	1.2811	0.4889
0.1535	6.0	36	1.5643	0.4667
0.0259	7.0	42	1.3477	0.5556
0.0259	8.0	48	1.7927	0.4889
0.0051	9.0	54	1.7277	0.5556
0.0016	10.0	60	1.5795	0.6222
0.0016	11.0	66	1.6103	0.6
0.0008	12.0	72	1.7043	0.5778
0.0008	13.0	78	1.7832	0.5778
0.0005	14.0	84	1.8224	0.5778
0.0004	15.0	90	1.8294	0.5778
0.0004	16.0	96	1.8185	0.5778
0.0004	17.0	102	1.8150	0.5778
0.0004	18.0	108	1.8206	0.5778
0.0004	19.0	114	1.8349	0.5778
0.0003	20.0	120	1.8491	0.5778
0.0003	21.0	126	1.8590	0.5778
0.0003	22.0	132	1.8667	0.5556
0.0003	23.0	138	1.8640	0.5556
0.0003	24.0	144	1.8624	0.5556
0.0003	25.0	150	1.8632	0.5778
0.0003	26.0	156	1.8651	0.5556
0.0003	27.0	162	1.8642	0.5778
0.0003	28.0	168	1.8659	0.5778
0.0003	29.0	174	1.8666	0.5778
0.0003	30.0	180	1.8680	0.5778
0.0003	31.0	186	1.8684	0.5778
0.0002	32.0	192	1.8677	0.5778
0.0002	33.0	198	1.8709	0.5778
0.0002	34.0	204	1.8723	0.5778
0.0002	35.0	210	1.8730	0.5778
0.0002	36.0	216	1.8757	0.5778
0.0002	37.0	222	1.8766	0.5778
0.0002	38.0	228	1.8780	0.5778
0.0002	39.0	234	1.8793	0.5778
0.0002	40.0	240	1.8801	0.5778
0.0002	41.0	246	1.8804	0.5778
0.0002	42.0	252	1.8804	0.5778
0.0002	43.0	258	1.8804	0.5778
0.0002	44.0	264	1.8804	0.5778
0.0002	45.0	270	1.8804	0.5778
0.0002	46.0	276	1.8804	0.5778
0.0002	47.0	282	1.8804	0.5778
0.0002	48.0	288	1.8804	0.5778
0.0002	49.0	294	1.8804	0.5778
0.0002	50.0	300	1.8804	0.5778

Framework versions

• Transformers 4.35.0
• Pytorch 2.1.0+cu118
• Datasets 2.14.6
• Tokenizers 0.14.1