deit_fold_1

nqvii/deit_fold_1

deit_fold_1 is a image classification model from nqvii. 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: vit
Access: Public
Created: Aug 8, 2026
Updated: Aug 8, 2026
SHA: b7ee6dda

Base models

facebook/deit-small-patch16-224

Datasets

imagefolder

Model card

From the Hugging Face model README

deit_fold_1

This model is a fine-tuned version of facebook/deit-small-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 1.1170
Accuracy: 0.9655
F1 Score: 0.9681
Recall: 0.9681

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: 1e-05
train_batch_size: 64
eval_batch_size: 64
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 150
num_epochs: 100
label_smoothing_factor: 0.15

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1 Score	Recall
2.7052	1.0	19	2.6182	0.3897	0.2859	0.3210
2.6037	2.0	38	2.4936	0.4345	0.3591	0.3697
2.4310	3.0	57	2.2883	0.5552	0.5442	0.5290
2.1283	4.0	76	1.9885	0.7172	0.7322	0.7214
1.7269	5.0	95	1.6339	0.8172	0.8313	0.8241
1.4880	6.0	114	1.3974	0.8655	0.8730	0.8676
1.2856	7.0	133	1.2969	0.9	0.9069	0.9031
1.2589	8.0	152	1.2535	0.9069	0.9112	0.9057
1.1813	9.0	171	1.1953	0.9241	0.9300	0.9304
1.1441	10.0	190	1.1895	0.9379	0.9417	0.9389
1.1279	11.0	209	1.1635	0.9552	0.9589	0.9584
1.0956	12.0	228	1.1425	0.9483	0.9524	0.9511
1.0689	13.0	247	1.1503	0.9483	0.9511	0.9521
1.0613	14.0	266	1.1557	0.9552	0.9574	0.9571
1.0226	15.0	285	1.1592	0.9448	0.9478	0.9449
1.0242	16.0	304	1.1320	0.9483	0.9511	0.9510
1.0160	17.0	323	1.1371	0.9552	0.9584	0.9571
0.9991	18.0	342	1.1267	0.9621	0.9650	0.9657
1.0108	19.0	361	1.1350	0.9517	0.9551	0.9534
1.0175	20.0	380	1.1404	0.9586	0.9617	0.9608
0.9991	21.0	399	1.1422	0.9586	0.9614	0.9596
0.9951	22.0	418	1.1277	0.9552	0.9590	0.9608
0.9753	23.0	437	1.1113	0.9586	0.9620	0.9632
0.9748	24.0	456	1.1117	0.9552	0.9590	0.9608
0.9748	25.0	475	1.1086	0.9621	0.9648	0.9645
0.9704	26.0	494	1.1182	0.9586	0.9619	0.9620
0.9748	27.0	513	1.1061	0.9586	0.9620	0.9632
0.9637	28.0	532	1.0796	0.9621	0.9652	0.9669
0.9696	29.0	551	1.1170	0.9655	0.9681	0.9681
0.9656	30.0	570	1.0977	0.9621	0.9652	0.9669
0.9679	31.0	589	1.1275	0.9586	0.9621	0.9632
0.9699	32.0	608	1.0992	0.9586	0.9622	0.9645
0.9760	33.0	627	1.1147	0.9621	0.9647	0.9632
0.9595	34.0	646	1.0978	0.9621	0.9653	0.9681
0.9619	35.0	665	1.1000	0.9621	0.9648	0.9645
0.9634	36.0	684	1.1140	0.9655	0.9679	0.9669
0.9554	37.0	703	1.1082	0.9655	0.9679	0.9669
0.9644	38.0	722	1.1166	0.9655	0.9681	0.9681

Framework versions

Transformers 5.0.0
Pytorch 2.10.0+cu128
Datasets 5.0.0
Tokenizers 0.22.2

Task: Image Classification
Library: transformers
Type: vit
License: apache-2.0
Created: Aug 8, 2026
Updated: Aug 8, 2026