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: 4.1726
Accuracy: 0.4222

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	1.4791	0.3333
2.0372	2.0	12	1.3991	0.2444
2.0372	3.0	18	1.9327	0.2444
1.2524	4.0	24	1.4584	0.3556
1.1547	5.0	30	1.3317	0.3556
1.1547	6.0	36	1.9319	0.3333
0.8748	7.0	42	1.3603	0.4222
0.8748	8.0	48	1.0979	0.5333
0.8902	9.0	54	1.9103	0.4222
0.6653	10.0	60	2.0004	0.3778
0.6653	11.0	66	2.0962	0.4
0.5253	12.0	72	1.2246	0.5111
0.5253	13.0	78	1.6731	0.4889
0.5223	14.0	84	2.1516	0.4
0.2968	15.0	90	2.5065	0.4
0.2968	16.0	96	2.0657	0.4444
0.4394	17.0	102	1.5876	0.4667
0.4394	18.0	108	2.1433	0.4
0.2725	19.0	114	1.4220	0.5556
0.1718	20.0	120	1.7558	0.4667
0.1718	21.0	126	2.3734	0.4667
0.0642	22.0	132	2.9683	0.4667
0.0642	23.0	138	2.9217	0.4889
0.0435	24.0	144	3.4732	0.4667
0.0409	25.0	150	3.8797	0.4667
0.0409	26.0	156	4.3387	0.4444
0.0418	27.0	162	3.9839	0.4444
0.0418	28.0	168	4.5122	0.4444
0.0035	29.0	174	4.2517	0.4444
0.0006	30.0	180	3.9958	0.4444
0.0006	31.0	186	3.9647	0.4444
0.0004	32.0	192	3.9928	0.4444
0.0004	33.0	198	4.0376	0.4222
0.0003	34.0	204	4.0736	0.4222
0.0002	35.0	210	4.1046	0.4222
0.0002	36.0	216	4.1284	0.4222
0.0002	37.0	222	4.1466	0.4222
0.0002	38.0	228	4.1585	0.4222
0.0002	39.0	234	4.1664	0.4222
0.0002	40.0	240	4.1704	0.4222
0.0002	41.0	246	4.1721	0.4222
0.0002	42.0	252	4.1726	0.4222
0.0002	43.0	258	4.1726	0.4222
0.0002	44.0	264	4.1726	0.4222
0.0002	45.0	270	4.1726	0.4222
0.0002	46.0	276	4.1726	0.4222
0.0002	47.0	282	4.1726	0.4222
0.0002	48.0	288	4.1726	0.4222
0.0002	49.0	294	4.1726	0.4222
0.0002	50.0	300	4.1726	0.4222

Framework versions

Transformers 4.35.0
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1

hkivancoral/hushem_conflu_deneme_f1

hushem_conflu_deneme_f1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

hkivancoral/
hushem_conflu_deneme_f1