yolo_finetuned_fruits

MarioGL/yolo_finetuned_fruits

yolo_finetuned_fruits is a object detection model from MarioGL. 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: Apr 23, 2025
Updated: Apr 23, 2025
SHA: 5fc94828

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: 0.8341
Map: 0.572
Map 50: 0.8556
Map 75: 0.6387
Map Small: -1.0
Map Medium: 0.5995
Map Large: 0.5779
Mar 1: 0.4112
Mar 10: 0.7057
Mar 100: 0.7578
Mar Small: -1.0
Mar Medium: 0.7325
Mar Large: 0.7609
Map Banana: 0.4363
Mar 100 Banana: 0.7325
Map Orange: 0.6275
Mar 100 Orange: 0.781
Map Apple: 0.6522
Mar 100 Apple: 0.76

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 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	1.5440	0.0387	0.0859	0.0348	-1.0	0.1394	0.0336	0.149	0.2869	0.5454	-1.0	0.485	0.5483	0.0331	0.5975	0.0514	0.4929	0.0315	0.5457
No log	2.0	120	1.5123	0.0855	0.2047	0.0596	-1.0	0.2024	0.0905	0.176	0.366	0.5231	-1.0	0.43	0.5303	0.0686	0.575	0.0483	0.3143	0.1395	0.68
No log	3.0	180	1.4236	0.0718	0.1411	0.0629	-1.0	0.1677	0.0714	0.2189	0.4188	0.5707	-1.0	0.6325	0.5636	0.0422	0.5925	0.0798	0.5738	0.0934	0.5457
No log	4.0	240	1.2437	0.1361	0.2456	0.1491	-1.0	0.3305	0.1522	0.2948	0.5091	0.6615	-1.0	0.625	0.6675	0.0816	0.6175	0.1462	0.6786	0.1805	0.6886
No log	5.0	300	1.1642	0.1941	0.3089	0.2199	-1.0	0.3199	0.2035	0.3128	0.5666	0.6821	-1.0	0.705	0.6824	0.0805	0.635	0.1943	0.6429	0.3076	0.7686
No log	6.0	360	1.1856	0.3147	0.5352	0.3616	-1.0	0.3609	0.3281	0.3224	0.5628	0.66	-1.0	0.57	0.6692	0.1343	0.63	0.3586	0.6214	0.4513	0.7286
No log	7.0	420	0.9729	0.3946	0.6053	0.4763	-1.0	0.3824	0.4076	0.3595	0.6093	0.7112	-1.0	0.6675	0.7153	0.2312	0.705	0.4634	0.7286	0.4894	0.7
No log	8.0	480	1.0144	0.4255	0.7172	0.4726	-1.0	0.4703	0.4381	0.362	0.6152	0.6965	-1.0	0.6825	0.7014	0.2774	0.6475	0.4481	0.6905	0.5511	0.7514
1.1634	9.0	540	0.9774	0.48	0.7801	0.5204	-1.0	0.515	0.5061	0.3615	0.641	0.7079	-1.0	0.6325	0.7183	0.32	0.67	0.5217	0.731	0.5984	0.7229
1.1634	10.0	600	1.0095	0.4681	0.7863	0.4974	-1.0	0.5686	0.4764	0.3608	0.6471	0.7063	-1.0	0.645	0.7137	0.3044	0.665	0.5478	0.731	0.5521	0.7229
1.1634	11.0	660	0.9365	0.4856	0.785	0.5537	-1.0	0.5393	0.4932	0.3753	0.6683	0.7209	-1.0	0.71	0.7258	0.3324	0.6675	0.5215	0.7667	0.603	0.7286
1.1634	12.0	720	0.9318	0.5065	0.7759	0.5698	-1.0	0.4812	0.5166	0.3932	0.6754	0.7317	-1.0	0.7025	0.7373	0.3646	0.685	0.4942	0.7357	0.6606	0.7743
1.1634	13.0	780	0.8694	0.5439	0.8237	0.6188	-1.0	0.5939	0.5536	0.3957	0.6971	0.7484	-1.0	0.755	0.7513	0.4012	0.7075	0.5879	0.7833	0.6427	0.7543
1.1634	14.0	840	0.8888	0.537	0.8231	0.5881	-1.0	0.471	0.5495	0.3965	0.6842	0.7273	-1.0	0.7275	0.7298	0.4131	0.6875	0.557	0.7571	0.6408	0.7371
1.1634	15.0	900	0.8759	0.5486	0.8215	0.6192	-1.0	0.4901	0.5642	0.4162	0.6849	0.7504	-1.0	0.7175	0.7571	0.4077	0.6975	0.5634	0.7738	0.6749	0.78
1.1634	16.0	960	0.8709	0.5503	0.856	0.6079	-1.0	0.6038	0.5588	0.3988	0.6788	0.7389	-1.0	0.6925	0.7459	0.4131	0.6925	0.5928	0.7643	0.645	0.76
0.739	17.0	1020	0.9051	0.5407	0.8343	0.6075	-1.0	0.6395	0.544	0.3903	0.6884	0.7336	-1.0	0.7475	0.7349	0.3945	0.685	0.5774	0.7643	0.6501	0.7514
0.739	18.0	1080	0.8992	0.5441	0.84	0.5738	-1.0	0.6025	0.5492	0.4014	0.684	0.7301	-1.0	0.705	0.7349	0.4046	0.685	0.5938	0.7738	0.6341	0.7314
0.739	19.0	1140	0.8874	0.5597	0.8492	0.6127	-1.0	0.637	0.5648	0.4083	0.6959	0.7476	-1.0	0.7375	0.7512	0.4149	0.7	0.6086	0.7857	0.6555	0.7571
0.739	20.0	1200	0.8511	0.5739	0.8539	0.6164	-1.0	0.6501	0.5792	0.4119	0.7027	0.7512	-1.0	0.765	0.7526	0.4278	0.685	0.598	0.7857	0.6958	0.7829
0.739	21.0	1260	0.8410	0.5585	0.8335	0.602	-1.0	0.617	0.562	0.4049	0.6914	0.7379	-1.0	0.7225	0.7408	0.4426	0.695	0.598	0.7786	0.635	0.74
0.739	22.0	1320	0.8601	0.5661	0.8578	0.6273	-1.0	0.59	0.5698	0.402	0.6915	0.7349	-1.0	0.69	0.7399	0.4617	0.7075	0.5998	0.7714	0.6367	0.7257
0.739	23.0	1380	0.8342	0.5768	0.8697	0.6525	-1.0	0.5742	0.5857	0.4092	0.6926	0.7453	-1.0	0.7125	0.7495	0.4508	0.715	0.6183	0.781	0.6612	0.74
0.739	24.0	1440	0.8332	0.5754	0.8542	0.6483	-1.0	0.5912	0.5811	0.4106	0.6929	0.7493	-1.0	0.735	0.7519	0.4558	0.7175	0.6252	0.7905	0.6453	0.74
0.5743	25.0	1500	0.8418	0.5749	0.8527	0.6509	-1.0	0.589	0.5814	0.4114	0.6978	0.7517	-1.0	0.725	0.7552	0.4595	0.7275	0.6192	0.7905	0.6461	0.7371
0.5743	26.0	1560	0.8364	0.573	0.854	0.6416	-1.0	0.6126	0.5773	0.4096	0.6985	0.7505	-1.0	0.745	0.752	0.4485	0.7225	0.6224	0.7833	0.6482	0.7457
0.5743	27.0	1620	0.8337	0.574	0.8561	0.6405	-1.0	0.6115	0.579	0.4104	0.6971	0.7515	-1.0	0.7325	0.754	0.4423	0.7225	0.6291	0.7833	0.6504	0.7486
0.5743	28.0	1680	0.8323	0.5702	0.8556	0.6335	-1.0	0.6109	0.5749	0.4104	0.704	0.7544	-1.0	0.7225	0.7583	0.4356	0.7275	0.6258	0.7786	0.6491	0.7571
0.5743	29.0	1740	0.8336	0.5719	0.8555	0.6387	-1.0	0.5994	0.5779	0.4112	0.7057	0.7578	-1.0	0.7325	0.7609	0.4356	0.7325	0.6275	0.781	0.6526	0.76
0.5743	30.0	1800	0.8341	0.572	0.8556	0.6387	-1.0	0.5995	0.5779	0.4112	0.7057	0.7578	-1.0	0.7325	0.7609	0.4363	0.7325	0.6275	0.781	0.6522	0.76

Framework versions

Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1

Task: Object Detection
Library: transformers
Type: yolos
License: apache-2.0
Created: Apr 23, 2025
Updated: Apr 23, 2025