This model is a fine-tuned version of facebook/deit-base-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 0.4898
Accuracy: 0.8748

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: 5e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.3398	1.0	375	0.4288	0.8164
0.2944	2.0	750	0.4228	0.8297
0.1957	3.0	1125	0.4014	0.8497
0.176	4.0	1501	0.4565	0.8514
0.1333	5.0	1876	0.3698	0.8731
0.1322	6.0	2251	0.5002	0.8481
0.0952	7.0	2626	0.4711	0.8648
0.0941	8.0	3002	0.4872	0.8698
0.0946	9.0	3377	0.5003	0.8564
0.0911	9.99	3750	0.4898	0.8748

Framework versions

Transformers 4.32.1
Pytorch 2.1.0+cu121
Datasets 2.12.0
Tokenizers 0.13.2

alperenoguz/smids_deit_base_f1

smids_deit_base_f1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

alperenoguz/
smids_deit_base_f1