yolo_finetuned_fruits

MapacheFantasma/yolo_finetuned_fruits

yolo_finetuned_fruits is a object detection model from MapacheFantasma. 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 26, 2025
Updated: Apr 26, 2025
SHA: 66800bc1

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: 0.7503
Map: 0.6085
Map 50: 0.8475
Map 75: 0.7364
Map Small: -1.0
Map Medium: 0.6015
Map Large: 0.6265
Mar 1: 0.4268
Mar 10: 0.751
Mar 100: 0.7961
Mar Small: -1.0
Mar Medium: 0.7229
Mar Large: 0.8051
Map Banana: 0.5094
Mar 100 Banana: 0.785
Map Orange: 0.618
Mar 100 Orange: 0.769
Map Apple: 0.698
Mar 100 Apple: 0.8343

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	1.8687	0.0129	0.038	0.0049	-1.0	0.0067	0.0157	0.0572	0.1949	0.3652	-1.0	0.2814	0.3769	0.0129	0.415	0.0218	0.469	0.0039	0.2114
No log	2.0	120	1.9912	0.0217	0.0645	0.0096	-1.0	0.0976	0.0177	0.0771	0.1793	0.3634	-1.0	0.31	0.3634	0.0221	0.5125	0.0223	0.3262	0.0207	0.2514
No log	3.0	180	1.3626	0.0825	0.1743	0.0701	-1.0	0.2573	0.0705	0.2254	0.4597	0.6161	-1.0	0.5471	0.6235	0.0727	0.6225	0.1038	0.5714	0.071	0.6543
No log	4.0	240	1.1473	0.2756	0.4616	0.3013	-1.0	0.2822	0.2894	0.3357	0.5695	0.6993	-1.0	0.5957	0.7144	0.219	0.6575	0.2073	0.669	0.4004	0.7714
No log	5.0	300	1.1179	0.2757	0.4919	0.2891	-1.0	0.3702	0.2764	0.2987	0.5971	0.6843	-1.0	0.6257	0.6906	0.2151	0.69	0.2161	0.6571	0.3957	0.7057
No log	6.0	360	0.9856	0.3562	0.5528	0.405	-1.0	0.468	0.3741	0.3483	0.6138	0.7382	-1.0	0.7286	0.7449	0.2702	0.6775	0.2062	0.7	0.5923	0.8371
No log	7.0	420	0.9100	0.4767	0.7183	0.5312	-1.0	0.4923	0.4962	0.3951	0.6727	0.7679	-1.0	0.69	0.7806	0.3461	0.7375	0.4555	0.7548	0.6285	0.8114
No log	8.0	480	0.8879	0.5102	0.7946	0.5966	-1.0	0.5537	0.5229	0.3958	0.6899	0.7675	-1.0	0.67	0.7813	0.3708	0.735	0.52	0.7762	0.64	0.7914
1.2703	9.0	540	0.8767	0.4935	0.7566	0.5666	-1.0	0.5038	0.5153	0.3947	0.6888	0.7654	-1.0	0.6971	0.7758	0.3741	0.74	0.5181	0.7619	0.5882	0.7943
1.2703	10.0	600	0.9414	0.4938	0.7676	0.5823	-1.0	0.4991	0.5147	0.4014	0.685	0.7503	-1.0	0.6771	0.761	0.3564	0.73	0.5156	0.7238	0.6094	0.7971
1.2703	11.0	660	0.8135	0.5144	0.7897	0.5938	-1.0	0.508	0.5392	0.4156	0.7196	0.7767	-1.0	0.7343	0.7836	0.4231	0.7625	0.5653	0.7762	0.5547	0.7914
1.2703	12.0	720	0.8786	0.4876	0.7543	0.5569	-1.0	0.5132	0.4986	0.3891	0.6706	0.739	-1.0	0.6914	0.7435	0.3739	0.74	0.5269	0.7286	0.5621	0.7486
1.2703	13.0	780	0.8729	0.5293	0.8224	0.5918	-1.0	0.5589	0.5392	0.3945	0.679	0.7554	-1.0	0.7114	0.7616	0.3989	0.7325	0.5524	0.7595	0.6366	0.7743
1.2703	14.0	840	0.9073	0.5443	0.813	0.6243	-1.0	0.5372	0.563	0.4065	0.698	0.7671	-1.0	0.6843	0.7808	0.3877	0.715	0.5517	0.7548	0.6934	0.8314
1.2703	15.0	900	0.7988	0.5792	0.8313	0.6911	-1.0	0.5979	0.5993	0.4382	0.7344	0.7752	-1.0	0.7243	0.7852	0.4579	0.74	0.6013	0.7571	0.6785	0.8286
1.2703	16.0	960	0.7813	0.5791	0.8403	0.6903	-1.0	0.5997	0.5964	0.4227	0.7348	0.7898	-1.0	0.71	0.8023	0.4825	0.775	0.574	0.7714	0.6808	0.8229
0.7137	17.0	1020	0.8336	0.5661	0.8326	0.687	-1.0	0.5509	0.5899	0.4199	0.7257	0.7735	-1.0	0.6871	0.7848	0.4837	0.7625	0.5681	0.7667	0.6465	0.7914
0.7137	18.0	1080	0.7945	0.5896	0.8523	0.6792	-1.0	0.6043	0.6038	0.428	0.7363	0.789	-1.0	0.7057	0.7996	0.4522	0.765	0.6042	0.7762	0.7124	0.8257
0.7137	19.0	1140	0.8319	0.5886	0.867	0.6988	-1.0	0.6039	0.6003	0.4302	0.7234	0.7826	-1.0	0.6929	0.792	0.4803	0.7825	0.591	0.7452	0.6946	0.82
0.7137	20.0	1200	0.7760	0.6031	0.8523	0.7223	-1.0	0.6261	0.6134	0.429	0.7447	0.7875	-1.0	0.7129	0.7964	0.4878	0.775	0.5966	0.7619	0.725	0.8257
0.7137	21.0	1260	0.7789	0.6091	0.8682	0.7337	-1.0	0.5898	0.6269	0.4252	0.7343	0.7887	-1.0	0.6771	0.8031	0.4982	0.78	0.6219	0.769	0.7071	0.8171
0.7137	22.0	1320	0.7605	0.6027	0.8448	0.6999	-1.0	0.6072	0.6237	0.4281	0.7459	0.7911	-1.0	0.7114	0.8011	0.4851	0.79	0.6207	0.769	0.7024	0.8143
0.7137	23.0	1380	0.7435	0.6084	0.8491	0.731	-1.0	0.6307	0.6253	0.432	0.7536	0.8052	-1.0	0.7429	0.8131	0.4922	0.7975	0.6328	0.781	0.7001	0.8371
0.7137	24.0	1440	0.7429	0.6063	0.8352	0.7323	-1.0	0.6293	0.6206	0.4342	0.7492	0.7987	-1.0	0.7257	0.8077	0.4852	0.7975	0.6289	0.7643	0.7048	0.8343
0.5485	25.0	1500	0.7587	0.6018	0.8351	0.7314	-1.0	0.602	0.6199	0.4369	0.7473	0.7954	-1.0	0.7157	0.8052	0.5002	0.79	0.6166	0.7619	0.6887	0.8343
0.5485	26.0	1560	0.7494	0.6089	0.8385	0.7347	-1.0	0.6205	0.6252	0.4377	0.7566	0.8028	-1.0	0.7257	0.8126	0.5078	0.795	0.6166	0.7762	0.7024	0.8371
0.5485	27.0	1620	0.7562	0.6066	0.8428	0.7343	-1.0	0.5974	0.6242	0.4321	0.7513	0.7963	-1.0	0.7129	0.8061	0.5057	0.79	0.6067	0.7619	0.7072	0.8371
0.5485	28.0	1680	0.7555	0.6034	0.845	0.7342	-1.0	0.5912	0.6222	0.426	0.7502	0.7937	-1.0	0.7129	0.8033	0.5072	0.7825	0.6061	0.7643	0.6969	0.8343
0.5485	29.0	1740	0.7505	0.6085	0.8472	0.7371	-1.0	0.6015	0.6266	0.4268	0.7519	0.7969	-1.0	0.7229	0.8059	0.5097	0.7875	0.6178	0.769	0.698	0.8343
0.5485	30.0	1800	0.7503	0.6085	0.8475	0.7364	-1.0	0.6015	0.6265	0.4268	0.751	0.7961	-1.0	0.7229	0.8051	0.5094	0.785	0.618	0.769	0.698	0.8343

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 26, 2025
Updated: Apr 26, 2025