Beit-for-rice-disease

jkrperson/Beit-for-rice-disease

Beit-for-rice-disease is a image classification model from jkrperson. Use it when you need a label for an image. It is set up for transformers. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Image Classification
Library: transformers
License: apache-2.0
Model type: beit
Access: Public
Created: Jun 4, 2023
Updated: Jun 4, 2023
SHA: cd6dde1b

Datasets

image_folder

Spaces

rohanmiriyala/jkrperson-Beit-for-rice-disease

Model card

From the Hugging Face model README

Beit-for-rice-disease

This model is a fine-tuned version of microsoft/beit-base-patch16-224-pt22k-ft22k on the image_folder dataset. It achieves the following results on the evaluation set:

Loss: 0.1687
Accuracy: 0.95

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: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
2.4305	0.16	10	2.0142	0.5
1.804	0.32	20	1.5097	0.5446
1.2088	0.48	30	1.0185	0.6786
0.9168	0.63	40	0.8841	0.7768
0.7893	0.79	50	0.7512	0.7768
0.6253	0.95	60	0.9253	0.7411
0.4949	1.11	70	0.5854	0.8214
0.3272	1.27	80	0.5379	0.8393
0.3753	1.43	90	0.5194	0.8571
0.3378	1.59	100	0.3831	0.8661
0.3643	1.75	110	0.4066	0.8661
0.3413	1.9	120	0.4268	0.875
0.3278	2.06	130	0.4754	0.8482
0.1784	2.22	140	0.4979	0.8839
0.2002	2.38	150	0.3606	0.8929
0.1224	2.54	160	0.3852	0.8839
0.2458	2.7	170	0.3492	0.9107
0.1816	2.86	180	0.3506	0.8839
0.2194	3.02	190	0.3255	0.9018
0.1582	3.17	200	0.4486	0.875
0.2072	3.33	210	0.3760	0.8929
0.1317	3.49	220	0.3021	0.9286
0.1223	3.65	230	0.3867	0.9018
0.1543	3.81	240	0.2640	0.9286
0.1256	3.97	250	0.2925	0.9196
0.095	4.13	260	0.2909	0.9107
0.0578	4.29	270	0.2825	0.9196
0.0428	4.44	280	0.2826	0.9196
0.1743	4.6	290	0.2746	0.9196
0.0659	4.76	300	0.3457	0.8929
0.0871	4.92	310	0.2902	0.9196
0.0726	5.08	320	0.2810	0.9196
0.0556	5.24	330	0.3244	0.9107
0.0629	5.4	340	0.2812	0.9286
0.0517	5.56	350	0.2638	0.9464
0.078	5.71	360	0.2580	0.9554
0.0376	5.87	370	0.2375	0.9464
0.0262	6.03	380	0.2274	0.9464
0.0582	6.19	390	0.2254	0.9643
0.0215	6.35	400	0.2545	0.9375
0.0379	6.51	410	0.2925	0.9286
0.0664	6.67	420	0.2842	0.9196
0.0375	6.83	430	0.2643	0.9375
0.0088	6.98	440	0.2401	0.9375
0.0299	7.14	450	0.2634	0.9286
0.0199	7.3	460	0.2800	0.9286
0.0182	7.46	470	0.2996	0.9107
0.0199	7.62	480	0.2813	0.9286
0.0189	7.78	490	0.2571	0.9286
0.053	7.94	500	0.2260	0.9196
0.0448	8.1	510	0.2112	0.9464
0.0072	8.25	520	0.2133	0.9286
0.0112	8.41	530	0.2149	0.9464
0.021	8.57	540	0.2189	0.9286
0.0073	8.73	550	0.2397	0.9375
0.0128	8.89	560	0.2578	0.9375
0.005	9.05	570	0.2578	0.9375
0.0246	9.21	580	0.2485	0.9286
0.0073	9.37	590	0.2460	0.9286
0.005	9.52	600	0.2429	0.9286
0.0083	9.68	610	0.2362	0.9286
0.0114	9.84	620	0.2338	0.9286
0.0031	10.0	630	0.2327	0.9286

Framework versions

Transformers 4.28.0
Pytorch 2.0.0
Datasets 2.1.0
Tokenizers 0.13.3

Task: Image Classification
Library: transformers
Type: beit
License: apache-2.0
Created: Jun 4, 2023
Updated: Jun 4, 2023