learning_rate: 5e-05
train_batch_size: 64
eval_batch_size: 64
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine_with_restarts
lr_scheduler_warmup_steps: 256
num_epochs: 30
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.9877	0.5	64	1.6839	0.4530
1.1728	1.0	128	0.7806	0.7517
0.4995	1.5	192	0.4855	0.8389
0.2433	2.0	256	0.2821	0.9161
0.0745	2.5	320	0.3466	0.9060
0.0506	3.0	384	0.3206	0.9195
0.0163	3.5	448	0.2656	0.9195
0.0061	4.0	512	0.2853	0.9295
0.002	4.5	576	0.2004	0.9430
0.0009	5.0	640	0.2256	0.9396
0.0006	5.5	704	0.2412	0.9362
0.0006	6.0	768	0.2381	0.9362
0.0005	6.5	832	0.2384	0.9362
0.0005	7.0	896	0.2366	0.9430
0.0004	7.5	960	0.2608	0.9329
0.0003	8.0	1024	0.2530	0.9430
0.0002	8.5	1088	0.2587	0.9396
0.0002	9.0	1152	0.2602	0.9430
0.0002	9.5	1216	0.2671	0.9396
0.0002	10.0	1280	0.2640	0.9396
0.0002	10.5	1344	0.2637	0.9396
0.0002	11.0	1408	0.2644	0.9396
0.0002	11.5	1472	0.2677	0.9396
0.0001	12.0	1536	0.2767	0.9362
0.0001	12.5	1600	0.2761	0.9396
0.0001	13.0	1664	0.2833	0.9396
0.0001	13.5	1728	0.2810	0.9396
0.0001	14.0	1792	0.2839	0.9396
0.0001	14.5	1856	0.2860	0.9396
0.0001	15.0	1920	0.2846	0.9396
0.0001	15.5	1984	0.2850	0.9396
0.0001	16.0	2048	0.2850	0.9396
0.0001	16.5	2112	0.2854	0.9396
0.0001	17.0	2176	0.2950	0.9396
0.0001	17.5	2240	0.2976	0.9396
0.0001	18.0	2304	0.2972	0.9396
0.0001	18.5	2368	0.2984	0.9396
0.0001	19.0	2432	0.2980	0.9396
0.0001	19.5	2496	0.3003	0.9396
0.0001	20.0	2560	0.3002	0.9396
0.0001	20.5	2624	0.3001	0.9396
0.0001	21.0	2688	0.3030	0.9396
0.0	21.5	2752	0.3009	0.9396
0.0	22.0	2816	0.3065	0.9396
0.0	22.5	2880	0.3093	0.9396
0.0	23.0	2944	0.3082	0.9396
0.0	23.5	3008	0.3105	0.9396
0.0	24.0	3072	0.3112	0.9396
0.0	24.5	3136	0.3115	0.9396
0.0	25.0	3200	0.3117	0.9396
0.0	25.5	3264	0.3091	0.9396
0.0	26.0	3328	0.3159	0.9430
0.0	26.5	3392	0.3166	0.9430
0.0	27.0	3456	0.3231	0.9396
0.0	27.5	3520	0.3229	0.9396
0.0	28.0	3584	0.3223	0.9430
0.0	28.5	3648	0.3246	0.9396
0.0	29.0	3712	0.3229	0.9430
0.0	29.5	3776	0.3234	0.9430
0.0	30.0	3840	0.3237	0.9430

Framework versions

Transformers 4.48.3
Pytorch 2.5.1+cu124
Datasets 3.3.2
Tokenizers 0.21.1

SodaXII/deit-small-patch16-224_rice-leaf-disease-augmented-v4_v5_fft

deit-small-patch16-224_rice-leaf-disease-augmented-v4_v5_fft

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

SodaXII/
deit-small-patch16-224_rice-leaf-disease-augmented-v4_v5_fft