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: 2.8961
Accuracy: 0.5111

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: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	6	1.4190	0.2444
1.9213	2.0	12	1.3227	0.3111
1.9213	3.0	18	2.3526	0.2444
1.2734	4.0	24	1.7104	0.3778
1.0407	5.0	30	1.6039	0.3556
1.0407	6.0	36	1.2459	0.4667
0.733	7.0	42	1.3344	0.4667
0.733	8.0	48	1.5744	0.5556
0.448	9.0	54	1.2479	0.5556
0.3254	10.0	60	2.2545	0.5333
0.3254	11.0	66	1.7472	0.5333
0.2088	12.0	72	2.0350	0.5778
0.2088	13.0	78	3.0002	0.4889
0.1216	14.0	84	2.1774	0.5556
0.0746	15.0	90	2.5953	0.5333
0.0746	16.0	96	2.8934	0.5111
0.0176	17.0	102	2.8961	0.5111
0.0176	18.0	108	2.8961	0.5111
0.0201	19.0	114	2.8961	0.5111
0.0136	20.0	120	2.8961	0.5111

Framework versions

Transformers 4.35.0
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1

hkivancoral/hushem_conflu_deneme_fold1

hushem_conflu_deneme_fold1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

hkivancoral/
hushem_conflu_deneme_fold1