hushem_1x_deit_tiny_rms_lr001_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: 1.6888
• Accuracy: 0.3778

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	5.6136	0.2667
3.3911	2.0	12	1.9975	0.2444
3.3911	3.0	18	1.6108	0.2444
1.8768	4.0	24	1.5122	0.2667
1.5956	5.0	30	1.5150	0.2444
1.5956	6.0	36	1.8016	0.2444
1.4916	7.0	42	1.5690	0.4444
1.4916	8.0	48	1.4991	0.2667
1.4756	9.0	54	1.4574	0.2444
1.4478	10.0	60	1.4022	0.2444
1.4478	11.0	66	1.4406	0.2667
1.421	12.0	72	1.3666	0.2444
1.421	13.0	78	1.3200	0.2667
1.4101	14.0	84	1.4311	0.2444
1.366	15.0	90	1.5240	0.4
1.366	16.0	96	1.1533	0.5333
1.3311	17.0	102	1.1480	0.4667
1.3311	18.0	108	1.5207	0.2444
1.1912	19.0	114	1.6588	0.2889
1.1923	20.0	120	1.4947	0.4667
1.1923	21.0	126	1.3281	0.2444
1.1796	22.0	132	1.3569	0.3333
1.1796	23.0	138	1.7298	0.2444
1.1031	24.0	144	1.6401	0.3556
1.2056	25.0	150	1.3732	0.2889
1.2056	26.0	156	1.8651	0.3333
1.1039	27.0	162	1.2494	0.4667
1.1039	28.0	168	1.4459	0.2889
1.0659	29.0	174	1.4875	0.3333
1.0534	30.0	180	1.4599	0.3556
1.0534	31.0	186	1.3781	0.3556
1.0466	32.0	192	1.7266	0.4
1.0466	33.0	198	1.5340	0.4222
0.973	34.0	204	1.5429	0.3111
1.0226	35.0	210	1.6233	0.3111
1.0226	36.0	216	1.7204	0.3111
0.9676	37.0	222	1.7918	0.4
0.9676	38.0	228	1.6933	0.3333
0.8379	39.0	234	1.6708	0.4222
0.8938	40.0	240	1.6748	0.4
0.8938	41.0	246	1.6963	0.3778
0.8462	42.0	252	1.6888	0.3778
0.8462	43.0	258	1.6888	0.3778
0.8764	44.0	264	1.6888	0.3778
0.8676	45.0	270	1.6888	0.3778
0.8676	46.0	276	1.6888	0.3778
0.8418	47.0	282	1.6888	0.3778
0.8418	48.0	288	1.6888	0.3778
0.8647	49.0	294	1.6888	0.3778
0.872	50.0	300	1.6888	0.3778

Framework versions

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