hushem_1x_deit_tiny_sgd_001_fold4

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: 1.2335
• Accuracy: 0.4524

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	1.5918	0.2857
1.6404	2.0	12	1.5188	0.2857
1.6404	3.0	18	1.4665	0.2857
1.5241	4.0	24	1.4299	0.3333
1.4755	5.0	30	1.4106	0.3571
1.4755	6.0	36	1.3938	0.3095
1.4186	7.0	42	1.3803	0.2857
1.4186	8.0	48	1.3677	0.3810
1.3819	9.0	54	1.3558	0.3810
1.3541	10.0	60	1.3456	0.3810
1.3541	11.0	66	1.3370	0.3810
1.3363	12.0	72	1.3284	0.3810
1.3363	13.0	78	1.3193	0.3571
1.3168	14.0	84	1.3103	0.4048
1.2875	15.0	90	1.3032	0.4048
1.2875	16.0	96	1.2966	0.4048
1.2638	17.0	102	1.2902	0.4048
1.2638	18.0	108	1.2846	0.4048
1.2758	19.0	114	1.2805	0.4048
1.2611	20.0	120	1.2763	0.4048
1.2611	21.0	126	1.2724	0.4048
1.2411	22.0	132	1.2693	0.4048
1.2411	23.0	138	1.2666	0.4048
1.2357	24.0	144	1.2628	0.4048
1.231	25.0	150	1.2590	0.4048
1.231	26.0	156	1.2555	0.4048
1.2026	27.0	162	1.2531	0.4048
1.2026	28.0	168	1.2508	0.4048
1.2253	29.0	174	1.2482	0.4048
1.1949	30.0	180	1.2457	0.4048
1.1949	31.0	186	1.2436	0.4286
1.2025	32.0	192	1.2420	0.4286
1.2025	33.0	198	1.2406	0.4524
1.1709	34.0	204	1.2390	0.4524
1.1908	35.0	210	1.2376	0.4524
1.1908	36.0	216	1.2365	0.4524
1.1663	37.0	222	1.2358	0.4524
1.1663	38.0	228	1.2349	0.4524
1.1875	39.0	234	1.2342	0.4524
1.1799	40.0	240	1.2338	0.4524
1.1799	41.0	246	1.2336	0.4524
1.1658	42.0	252	1.2335	0.4524
1.1658	43.0	258	1.2335	0.4524
1.1875	44.0	264	1.2335	0.4524
1.1627	45.0	270	1.2335	0.4524
1.1627	46.0	276	1.2335	0.4524
1.1689	47.0	282	1.2335	0.4524
1.1689	48.0	288	1.2335	0.4524
1.1911	49.0	294	1.2335	0.4524
1.1557	50.0	300	1.2335	0.4524

Framework versions

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