vit-tiny-patch16-224_rice-leaf-disease-augmented-v4_fft

This model is a fine-tuned version of WinKawaks/vit-tiny-patch16-224 on an unknown dataset. It achieves the following results on the evaluation set:

Model description

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The following hyperparameters were used during training:

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 Loss	Epoch	Step	Accuracy	Validation Loss
2.0564	0.5	64	0.4899	1.4541
1.0767	1.0	128	0.7651	0.6909
0.4917	1.5	192	0.8322	0.4307
0.285	2.0	256	0.9027	0.2932
0.0902	2.5	320	0.8993	0.3134
0.0588	3.0	384	0.9161	0.3076
0.0155	3.5	448	0.9396	0.2627
0.0066	4.0	512	0.9295	0.2992
0.0017	4.5	576	0.9228	0.2936
0.0009	5.0	640	0.9228	0.2961
0.0006	5.5	704	0.9228	0.3005
0.0005	6.0	768	0.9228	0.3004
0.0005	6.5	832	0.9262	0.2867
0.0004	7.0	896	0.9295	0.2977
0.0003	7.5	960	0.9295	0.2944
0.0002	8.0	1024	0.9295	0.3074
0.0002	8.5	1088	0.9329	0.3053
0.0002	9.0	1152	0.9295	0.3098
0.0001	9.5	1216	0.9295	0.3102
0.0001	10.0	1280	0.9262	0.3105
0.0001	10.5	1344	0.9262	0.3105
0.0001	11.0	1408	0.9262	0.3202
0.0001	11.5	1472	0.9295	0.3183
0.0001	12.0	1536	0.9329	0.3131
0.0001	12.5	1600	0.9295	0.3157
0.0001	13.0	1664	0.9228	0.3238
0.0001	13.5	1728	0.9228	0.3220
0.0001	14.0	1792	0.9228	0.3266
0.0001	14.5	1856	0.9228	0.3274
0.0001	15.0	1920	0.9228	0.3269
0.0001	15.5	1984	0.3267	0.9262
0.0001	16.0	2048	0.3298	0.9228
0.0001	16.5	2112	0.3330	0.9228
0.0001	17.0	2176	0.3337	0.9228
0.0001	17.5	2240	0.3337	0.9228
0.0001	18.0	2304	0.3355	0.9228
0.0	18.5	2368	0.3346	0.9228
0.0	19.0	2432	0.3360	0.9228
0.0	19.5	2496	0.3368	0.9228
0.0	20.0	2560	0.3365	0.9228
0.0	20.5	2624	0.3364	0.9228
0.0	21.0	2688	0.3412	0.9228
0.0	21.5	2752	0.3414	0.9228
0.0	22.0	2816	0.3435	0.9262
0.0	22.5	2880	0.3557	0.9228
0.0	23.0	2944	0.3490	0.9295
0.0	23.5	3008	0.3564	0.9262
0.0	24.0	3072	0.3545	0.9295
0.0	24.5	3136	0.3577	0.9262
0.0	25.0	3200	0.3597	0.9262
0.0	25.5	3264	0.3632	0.9262
0.0	26.0	3328	0.3627	0.9262
0.0	26.5	3392	0.3650	0.9262
0.0	27.0	3456	0.3664	0.9262
0.0	27.5	3520	0.3664	0.9262
0.0	28.0	3584	0.3666	0.9262
0.0	28.5	3648	0.3666	0.9262
0.0	29.0	3712	0.3670	0.9262
0.0	29.5	3776	0.3673	0.9262
0.0	30.0	3840	0.3674	0.9262