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

jkrperson/Beit-for-rice-disease

Beit-for-rice-disease

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

jkrperson/
Beit-for-rice-disease