hushem_1x_deit_tiny_sgd_lr00001_fold5

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: 1.6421
• Accuracy: 0.1220

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: 1e-05
• 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	1.6490	0.1220
1.6062	2.0	12	1.6487	0.1220
1.6062	3.0	18	1.6483	0.1220
1.6229	4.0	24	1.6480	0.1220
1.5995	5.0	30	1.6477	0.1220
1.5995	6.0	36	1.6474	0.1220
1.5906	7.0	42	1.6470	0.1220
1.5906	8.0	48	1.6468	0.1220
1.609	9.0	54	1.6465	0.1220
1.6018	10.0	60	1.6462	0.1220
1.6018	11.0	66	1.6459	0.1220
1.5944	12.0	72	1.6457	0.1220
1.5944	13.0	78	1.6454	0.1220
1.6013	14.0	84	1.6452	0.1220
1.5987	15.0	90	1.6449	0.1220
1.5987	16.0	96	1.6447	0.1220
1.5899	17.0	102	1.6445	0.1220
1.5899	18.0	108	1.6443	0.1220
1.626	19.0	114	1.6441	0.1220
1.5972	20.0	120	1.6439	0.1220
1.5972	21.0	126	1.6437	0.1220
1.5649	22.0	132	1.6436	0.1220
1.5649	23.0	138	1.6434	0.1220
1.6699	24.0	144	1.6433	0.1220
1.5696	25.0	150	1.6431	0.1220
1.5696	26.0	156	1.6430	0.1220
1.5743	27.0	162	1.6429	0.1220
1.5743	28.0	168	1.6427	0.1220
1.6236	29.0	174	1.6426	0.1220
1.5936	30.0	180	1.6426	0.1220
1.5936	31.0	186	1.6425	0.1220
1.5875	32.0	192	1.6424	0.1220
1.5875	33.0	198	1.6423	0.1220
1.6171	34.0	204	1.6423	0.1220
1.5897	35.0	210	1.6422	0.1220
1.5897	36.0	216	1.6422	0.1220
1.5725	37.0	222	1.6421	0.1220
1.5725	38.0	228	1.6421	0.1220
1.6227	39.0	234	1.6421	0.1220
1.5924	40.0	240	1.6421	0.1220
1.5924	41.0	246	1.6421	0.1220
1.5811	42.0	252	1.6421	0.1220
1.5811	43.0	258	1.6421	0.1220
1.6072	44.0	264	1.6421	0.1220
1.5938	45.0	270	1.6421	0.1220
1.5938	46.0	276	1.6421	0.1220
1.6243	47.0	282	1.6421	0.1220
1.6243	48.0	288	1.6421	0.1220
1.5633	49.0	294	1.6421	0.1220
1.6091	50.0	300	1.6421	0.1220

Framework versions

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