dental_classification_model_010424

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: 0.5797
• Accuracy: 0.8354

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: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.8845	0.99	40	1.8553	0.3106
1.6458	1.99	80	1.6211	0.4363
1.4423	2.98	120	1.4076	0.5202
1.2767	4.0	161	1.2806	0.5714
1.0687	4.99	201	1.0996	0.6537
0.9687	5.99	241	1.0288	0.6677
0.8714	6.98	281	0.9370	0.7252
0.7841	8.0	322	0.8287	0.7484
0.6814	8.99	362	0.8141	0.7376
0.5964	9.99	402	0.7433	0.7919
0.5995	10.98	442	0.7075	0.7904
0.5222	12.0	483	0.6613	0.8043
0.5173	12.99	523	0.6485	0.8090
0.4776	13.99	563	0.6196	0.8230
0.4679	14.98	603	0.5795	0.8416
0.4123	16.0	644	0.6202	0.8168
0.4179	16.99	684	0.6037	0.8230
0.4139	17.99	724	0.5797	0.8354

Framework versions

• Transformers 4.38.2
• Pytorch 2.2.1+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2