vit-large-augmented-ph2-patch-32

This model is a fine-tuned version of google/vit-large-patch32-224-in21k on the ahishamm/Augmented_PH2_db_sharpened dataset. It achieves the following results on the evaluation set:

• Loss: 0.5737
• Accuracy: 0.8701
• Recall: 0.8701
• F1: 0.8701
• Precision: 0.8701

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: 0.0002
• train_batch_size: 16
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Recall	F1	Precision
0.0405	0.36	50	0.6853	0.8342	0.8342	0.8342	0.8342
0.0107	0.72	100	0.8199	0.8256	0.8256	0.8256	0.8256
0.0338	1.09	150	0.5737	0.8701	0.8701	0.8701	0.8701
0.0026	1.45	200	0.6008	0.8684	0.8684	0.8684	0.8684
0.0019	1.81	250	0.6275	0.8735	0.8735	0.8735	0.8735
0.0016	2.17	300	0.6488	0.8735	0.8735	0.8735	0.8735
0.0013	2.54	350	0.6639	0.8752	0.8752	0.8752	0.8752
0.0012	2.9	400	0.6757	0.8752	0.8752	0.8752	0.8752
0.0011	3.26	450	0.6844	0.8735	0.8735	0.8735	0.8735
0.001	3.62	500	0.6895	0.8735	0.8735	0.8735	0.8735
0.001	3.99	550	0.6913	0.8735	0.8735	0.8735	0.8735

Framework versions

• Transformers 4.30.2
• Pytorch 2.0.1+cu118
• Datasets 2.13.1
• Tokenizers 0.13.3