yolo_finetuned_fruits

magarcd/yolo_finetuned_fruits

yolo_finetuned_fruits is a object detection model from magarcd. Use it when you need objects located in 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: Object Detection
Library: transformers
License: apache-2.0
Model type: yolos
Access: Public
Created: Jan 9, 2026
Updated: Feb 9, 2026
SHA: 1379f662

Base models

hustvl/yolos-tiny

Model card

From the Hugging Face model README

yolo_finetuned_fruits

This model is a fine-tuned version of hustvl/yolos-tiny on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.7954
Map: 0.5892
Map 50: 0.8328
Map 75: 0.6674
Map Small: -1.0
Map Medium: 0.5663
Map Large: 0.6169
Mar 1: 0.4141
Mar 10: 0.7265
Mar 100: 0.7756
Mar Small: -1.0
Mar Medium: 0.6571
Mar Large: 0.7955
Map Banana: 0.4429
Mar 100 Banana: 0.75
Map Orange: 0.659
Mar 100 Orange: 0.8024
Map Apple: 0.6657
Mar 100 Apple: 0.7743

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: 4
eval_batch_size: 8
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
num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Map	Map 50	Map 75	Map Small	Map Medium	Map Large	Mar 1	Mar 10	Mar 100	Mar Small	Mar Medium	Mar Large	Map Banana	Mar 100 Banana	Map Orange	Mar 100 Orange	Map Apple	Mar 100 Apple
No log	1.0	60	1.3990	0.0391	0.0719	0.0403	-1.0	0.0684	0.0401	0.1199	0.2527	0.385	-1.0	0.1714	0.3965	0.0247	0.6475	0.092	0.4762	0.0006	0.0314
No log	2.0	120	1.1686	0.1096	0.204	0.1038	-1.0	0.1725	0.1044	0.2342	0.4783	0.5948	-1.0	0.4643	0.6074	0.0809	0.69	0.225	0.6714	0.023	0.4229
No log	3.0	180	1.3431	0.1249	0.2509	0.1144	-1.0	0.1462	0.1347	0.2579	0.4407	0.5518	-1.0	0.4143	0.5687	0.0942	0.6225	0.1709	0.3643	0.1096	0.6686
No log	4.0	240	1.1267	0.1845	0.3439	0.1842	-1.0	0.1392	0.2039	0.3012	0.529	0.6278	-1.0	0.4071	0.6563	0.2237	0.7025	0.1888	0.4238	0.1411	0.7571
No log	5.0	300	1.0912	0.2475	0.4219	0.2236	-1.0	0.2148	0.2749	0.2966	0.5299	0.5811	-1.0	0.3643	0.6057	0.2455	0.7	0.2101	0.3119	0.2871	0.7314
No log	6.0	360	1.1260	0.235	0.4756	0.2187	-1.0	0.2442	0.2449	0.2846	0.5881	0.677	-1.0	0.45	0.7094	0.2412	0.7025	0.2525	0.6143	0.2112	0.7143
No log	7.0	420	1.0101	0.3586	0.5987	0.385	-1.0	0.3398	0.3796	0.3431	0.6107	0.6646	-1.0	0.4429	0.6963	0.2966	0.6925	0.373	0.5214	0.4062	0.78
No log	8.0	480	0.9863	0.3786	0.6147	0.4192	-1.0	0.3567	0.4123	0.336	0.641	0.7049	-1.0	0.5571	0.7277	0.3085	0.7175	0.4108	0.6571	0.4164	0.74
1.132	9.0	540	0.9648	0.4371	0.6906	0.5079	-1.0	0.4881	0.4603	0.3692	0.6546	0.7301	-1.0	0.6143	0.7496	0.3509	0.7075	0.4736	0.7429	0.4869	0.74
1.132	10.0	600	0.8788	0.4717	0.726	0.5483	-1.0	0.4967	0.4947	0.3771	0.6851	0.7631	-1.0	0.6571	0.7823	0.3582	0.7275	0.5304	0.8048	0.5265	0.7571
1.132	11.0	660	0.9204	0.4947	0.7668	0.5812	-1.0	0.4896	0.5148	0.3867	0.6721	0.7424	-1.0	0.6143	0.7658	0.3929	0.7125	0.5248	0.7405	0.5663	0.7743
1.132	12.0	720	0.8795	0.5097	0.7562	0.5828	-1.0	0.4958	0.5336	0.3852	0.67	0.7348	-1.0	0.6429	0.7514	0.427	0.71	0.4924	0.7143	0.6097	0.78
1.132	13.0	780	0.8721	0.5118	0.7716	0.5685	-1.0	0.5372	0.527	0.385	0.703	0.7557	-1.0	0.6857	0.7688	0.3992	0.72	0.5161	0.7929	0.6202	0.7543
1.132	14.0	840	0.8932	0.4965	0.7674	0.548	-1.0	0.5124	0.5212	0.3857	0.7051	0.7569	-1.0	0.6714	0.7727	0.3965	0.7275	0.535	0.769	0.5579	0.7743
1.132	15.0	900	0.9053	0.5106	0.8022	0.6087	-1.0	0.5431	0.5282	0.383	0.6686	0.7318	-1.0	0.6571	0.7462	0.4034	0.705	0.5408	0.719	0.5875	0.7714
1.132	16.0	960	0.8319	0.5518	0.7953	0.6198	-1.0	0.5083	0.5816	0.4026	0.7194	0.7738	-1.0	0.6143	0.8029	0.4373	0.72	0.5925	0.7929	0.6254	0.8086
0.7216	17.0	1020	0.8561	0.5435	0.8079	0.6491	-1.0	0.5569	0.5657	0.4005	0.7085	0.7467	-1.0	0.6214	0.7683	0.4095	0.715	0.6005	0.7595	0.6206	0.7657
0.7216	18.0	1080	0.8085	0.5698	0.8277	0.6445	-1.0	0.6027	0.5835	0.4165	0.7286	0.7826	-1.0	0.7286	0.7948	0.4496	0.745	0.6174	0.8143	0.6423	0.7886
0.7216	19.0	1140	0.7614	0.572	0.8128	0.6327	-1.0	0.5691	0.596	0.4105	0.7371	0.7795	-1.0	0.6857	0.7958	0.4407	0.7575	0.6224	0.8095	0.6528	0.7714
0.7216	20.0	1200	0.8146	0.5741	0.8193	0.6743	-1.0	0.5661	0.5945	0.4043	0.7217	0.7694	-1.0	0.7071	0.7806	0.4402	0.7525	0.623	0.7929	0.659	0.7629
0.7216	21.0	1260	0.8018	0.5737	0.8077	0.6593	-1.0	0.5429	0.6006	0.4021	0.7263	0.7698	-1.0	0.6714	0.7867	0.4384	0.75	0.6301	0.8024	0.6527	0.7571
0.7216	22.0	1320	0.8288	0.5605	0.81	0.647	-1.0	0.472	0.5924	0.4049	0.7087	0.7646	-1.0	0.6357	0.7856	0.4384	0.7475	0.6124	0.7976	0.6305	0.7486
0.7216	23.0	1380	0.8224	0.5768	0.8378	0.651	-1.0	0.517	0.6071	0.4137	0.709	0.7643	-1.0	0.6571	0.7818	0.463	0.7525	0.6179	0.7976	0.6494	0.7429
0.7216	24.0	1440	0.8023	0.5733	0.8227	0.6485	-1.0	0.5448	0.6014	0.4114	0.7226	0.7642	-1.0	0.6429	0.7846	0.4365	0.7375	0.633	0.8095	0.6503	0.7457
0.5482	25.0	1500	0.7952	0.5852	0.8328	0.6578	-1.0	0.5474	0.6147	0.4136	0.7294	0.7743	-1.0	0.6571	0.794	0.4432	0.75	0.6573	0.8071	0.6551	0.7657
0.5482	26.0	1560	0.7987	0.5873	0.8373	0.6686	-1.0	0.5588	0.6155	0.4128	0.7279	0.7792	-1.0	0.6571	0.7994	0.4457	0.7575	0.6598	0.8143	0.6565	0.7657
0.5482	27.0	1620	0.7974	0.5893	0.8299	0.6691	-1.0	0.566	0.6184	0.4177	0.7317	0.7781	-1.0	0.6571	0.7987	0.4381	0.7525	0.6575	0.8048	0.6723	0.7771
0.5482	28.0	1680	0.7946	0.5896	0.8328	0.6673	-1.0	0.5592	0.618	0.4149	0.7298	0.7756	-1.0	0.6571	0.7954	0.4466	0.7525	0.6591	0.8	0.663	0.7743
0.5482	29.0	1740	0.7968	0.5897	0.8322	0.6671	-1.0	0.5663	0.6173	0.4141	0.7274	0.7772	-1.0	0.6571	0.7971	0.4445	0.755	0.6588	0.8024	0.6657	0.7743
0.5482	30.0	1800	0.7954	0.5892	0.8328	0.6674	-1.0	0.5663	0.6169	0.4141	0.7265	0.7756	-1.0	0.6571	0.7955	0.4429	0.75	0.659	0.8024	0.6657	0.7743

Framework versions

Transformers 4.57.6
Pytorch 2.9.0+cu126
Datasets 4.0.0
Tokenizers 0.22.2

Task: Object Detection
Library: transformers
Type: yolos
License: apache-2.0
Created: Jan 9, 2026
Updated: Feb 9, 2026