ryan_model314

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

• Loss: 0.2532
• Na Accuracy: 0.947
• Ordinal Accuracy: 0.5952

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
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Na Accuracy	Ordinal Accuracy
0.3042	0.16	100	0.3673	0.928	0.4671
0.2904	0.32	200	0.2977	0.933	0.5790
0.2648	0.48	300	0.2831	0.944	0.5940
0.3036	0.64	400	0.2776	0.949	0.5871
0.2656	0.8	500	0.2846	0.931	0.6101
0.2954	0.96	600	0.2532	0.947	0.5952
0.1991	1.12	700	0.2603	0.942	0.6078
0.1678	1.28	800	0.2905	0.942	0.6332
0.2514	1.44	900	0.2566	0.94	0.6090
0.2328	1.6	1000	0.2884	0.94	0.5617
0.1826	1.76	1100	0.2870	0.943	0.6044
0.2013	1.92	1200	0.2937	0.941	0.5905
0.0663	2.08	1300	0.2954	0.938	0.6251
0.1503	2.24	1400	0.3188	0.937	0.5986
0.0611	2.4	1500	0.3393	0.945	0.5998
0.0743	2.56	1600	0.3182	0.942	0.6482
0.0908	2.72	1700	0.3332	0.942	0.6482
0.1108	2.88	1800	0.3256	0.943	0.6459
0.0786	3.04	1900	0.3222	0.944	0.6540
0.043	3.2	2000	0.3501	0.941	0.6482
0.0472	3.36	2100	0.3455	0.943	0.6609
0.032	3.52	2200	0.3562	0.94	0.6517
0.0434	3.68	2300	0.3499	0.94	0.6597
0.0341	3.84	2400	0.3611	0.94	0.6482
0.0305	4.0	2500	0.3635	0.939	0.6609

Framework versions

• Transformers 4.39.1
• Pytorch 2.2.1+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2