This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.5837
Accuracy: 0.8142

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: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.9273	0.99	41	1.9166	0.2281
1.8096	2.0	83	1.7653	0.3716
1.6373	2.99	124	1.5785	0.4486
1.4996	4.0	166	1.4273	0.5060
1.3441	4.99	207	1.2730	0.5891
1.1677	6.0	249	1.1615	0.6254
0.9809	6.99	290	1.1033	0.6254
0.8292	8.0	332	0.9928	0.6873
0.8035	8.99	373	0.8762	0.7402
0.6982	10.0	415	0.8117	0.7341
0.6992	10.99	456	0.7667	0.7749
0.5601	12.0	498	0.7563	0.7568
0.5358	12.99	539	0.7178	0.7749
0.569	14.0	581	0.7356	0.7553
0.4503	14.99	622	0.6535	0.8051
0.4509	16.0	664	0.6755	0.7855
0.5127	16.99	705	0.6431	0.7976
0.425	18.0	747	0.6362	0.8006
0.3968	18.99	788	0.5821	0.8157
0.398	20.0	830	0.6355	0.7900
0.4468	20.99	871	0.5103	0.8323
0.429	22.0	913	0.6056	0.8051
0.3332	22.99	954	0.5681	0.8233
0.3431	24.0	996	0.5186	0.8263
0.3052	24.99	1037	0.5993	0.8036
0.3495	26.0	1079	0.5837	0.8142

Framework versions

Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2

vishnu027/dental_classification_model_010424_2

dental_classification_model_010424_2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

vishnu027/
dental_classification_model_010424_2