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Nevico/
dfine-small-remia-cartons-v2

Name: dfine-small-remia-cartons-v2
Availability: InStock

generated_from_trainer

ustc-community/dfine-small-coco

finetune

apache-2.0

endpoints_compatible

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dfine-small-remia-cartons-v2

This model is a fine-tuned version of ustc-community/dfine-small-coco on the Nevico/remia-ned1-cam1-cartons-v2 dataset. It achieves the following results on the evaluation set:

Loss: 0.7504
Map: 0.9282
Map 50: 0.9711
Map 75: 0.9584
Map Small: 0.8068
Map Medium: 0.9538
Map Large: 0.9723
Mar 1: 0.0633
Mar 10: 0.5612
Mar 100: 0.9577
Mar Small: 0.8851
Mar Medium: 0.9739
Mar Large: 0.9873
Map Carton: 0.9282
Mar 100 Carton: 0.9577

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: 8
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: linear
num_epochs: 45.0

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 Carton	Mar 100 Carton
No log	1.0	135	2.0223	0.8046	0.9236	0.8464	0.5073	0.8677	0.8998	0.0619	0.5306	0.8686	0.667	0.9166	0.9402	0.8046	0.8686
No log	2.0	270	1.3310	0.8648	0.9541	0.9074	0.6741	0.9047	0.9201	0.0628	0.5474	0.9121	0.8003	0.9376	0.9564	0.8648	0.9121
No log	3.0	405	1.1531	0.8789	0.9594	0.9179	0.7072	0.9173	0.9286	0.0625	0.5495	0.9236	0.8124	0.9505	0.9612	0.8789	0.9236
13.1981	4.0	540	1.0580	0.8946	0.9648	0.9361	0.737	0.9279	0.9421	0.0633	0.5517	0.9375	0.8436	0.9595	0.9722	0.8946	0.9375
13.1981	5.0	675	1.0006	0.8998	0.9641	0.939	0.7433	0.9294	0.9537	0.0633	0.5533	0.941	0.8477	0.9612	0.9818	0.8998	0.941
13.1981	6.0	810	0.9521	0.905	0.9669	0.944	0.7495	0.9349	0.9564	0.0633	0.5524	0.945	0.8595	0.9632	0.9838	0.905	0.945
13.1981	7.0	945	0.9574	0.9033	0.9647	0.9409	0.7536	0.9334	0.9528	0.0633	0.5546	0.9428	0.857	0.9612	0.9811	0.9033	0.9428
9.3213	8.0	1080	0.9206	0.9083	0.9653	0.9466	0.7621	0.9365	0.9558	0.0633	0.5553	0.9463	0.8624	0.965	0.9808	0.9083	0.9463
9.3213	9.0	1215	0.8858	0.9121	0.9676	0.95	0.7703	0.9386	0.9595	0.0633	0.5555	0.9488	0.8693	0.9655	0.9856	0.9121	0.9488
9.3213	10.0	1350	0.8926	0.9132	0.9684	0.9475	0.764	0.9413	0.9603	0.0633	0.5583	0.9495	0.8686	0.9672	0.9842	0.9132	0.9495
9.3213	11.0	1485	0.8866	0.9137	0.9675	0.9504	0.7721	0.9419	0.9639	0.0633	0.5568	0.949	0.8608	0.9679	0.9887	0.9137	0.949
8.9070	12.0	1620	0.8633	0.9158	0.9677	0.9511	0.7748	0.9428	0.9677	0.0633	0.5592	0.9525	0.8711	0.9702	0.988	0.9158	0.9525
8.9070	13.0	1755	0.8623	0.9144	0.9672	0.9489	0.7782	0.9416	0.9582	0.0632	0.5587	0.9502	0.866	0.9689	0.9849	0.9144	0.9502
8.9070	14.0	1890	0.8490	0.9178	0.9693	0.9529	0.7822	0.9447	0.9657	0.0633	0.5582	0.9531	0.875	0.9698	0.9887	0.9178	0.9531
8.7030	15.0	2025	0.8435	0.9196	0.9687	0.9549	0.7841	0.9469	0.9646	0.0633	0.5578	0.9545	0.8714	0.9738	0.9856	0.9196	0.9545
8.7030	16.0	2160	0.8290	0.9203	0.969	0.954	0.7851	0.9466	0.9674	0.0633	0.559	0.9537	0.8706	0.9721	0.9883	0.9203	0.9537
8.7030	17.0	2295	0.8215	0.9213	0.9703	0.954	0.7897	0.946	0.9705	0.0633	0.5591	0.9538	0.8714	0.9721	0.988	0.9213	0.9538
8.7030	18.0	2430	0.8190	0.9227	0.9712	0.9551	0.7906	0.9469	0.9726	0.0633	0.5609	0.9547	0.876	0.9716	0.99	0.9227	0.9547
8.5033	19.0	2565	0.8186	0.9226	0.9706	0.9549	0.7907	0.948	0.9728	0.0633	0.5599	0.9551	0.8735	0.9728	0.9911	0.9226	0.9551
8.5033	20.0	2700	0.8003	0.9246	0.9714	0.9569	0.7919	0.9486	0.976	0.0633	0.5603	0.9546	0.8719	0.9729	0.9897	0.9246	0.9546
8.5033	21.0	2835	0.7979	0.924	0.9712	0.9573	0.7919	0.9495	0.9728	0.0633	0.5601	0.9552	0.8724	0.9736	0.9897	0.924	0.9552
8.5033	22.0	2970	0.8135	0.922	0.9696	0.9553	0.7911	0.9497	0.9633	0.0633	0.5595	0.9548	0.8714	0.9749	0.9835	0.922	0.9548
8.4478	23.0	3105	0.7922	0.9243	0.9708	0.9581	0.7966	0.9484	0.967	0.0633	0.5616	0.9563	0.883	0.9729	0.9852	0.9243	0.9563
8.4478	24.0	3240	0.7901	0.9248	0.9704	0.9559	0.7953	0.9489	0.9722	0.0633	0.5619	0.9563	0.8784	0.9737	0.9887	0.9248	0.9563
8.4478	25.0	3375	0.7910	0.9241	0.9712	0.9563	0.791	0.9486	0.9763	0.0633	0.5614	0.9543	0.8729	0.9721	0.989	0.9241	0.9543
8.3512	26.0	3510	0.7776	0.9252	0.9717	0.9563	0.7979	0.9491	0.9724	0.0633	0.5616	0.9544	0.8758	0.9714	0.989	0.9252	0.9544
8.3512	27.0	3645	0.7722	0.9263	0.9725	0.9584	0.8011	0.9498	0.9718	0.0633	0.5618	0.9555	0.8802	0.9722	0.9873	0.9263	0.9555
8.3512	28.0	3780	0.7880	0.9247	0.9728	0.9563	0.7968	0.9506	0.9668	0.0633	0.5609	0.9546	0.8722	0.9734	0.9869	0.9247	0.9546
8.3512	29.0	3915	0.7773	0.9259	0.9716	0.9572	0.799	0.9507	0.9651	0.0633	0.5597	0.9554	0.8786	0.973	0.9849	0.9259	0.9554
8.2997	30.0	4050	0.7818	0.9239	0.9714	0.9547	0.797	0.9493	0.9637	0.0633	0.5599	0.9537	0.8753	0.9724	0.9811	0.9239	0.9537
8.2997	31.0	4185	0.7682	0.9276	0.9719	0.9581	0.8031	0.9526	0.9744	0.0633	0.5614	0.9574	0.8807	0.9744	0.9897	0.9276	0.9574
8.2997	32.0	4320	0.7634	0.9273	0.9713	0.959	0.8029	0.9511	0.9765	0.0633	0.5612	0.9574	0.884	0.9731	0.9904	0.9273	0.9574
8.2997	33.0	4455	0.7793	0.9256	0.9713	0.9551	0.8017	0.9495	0.9707	0.0633	0.5609	0.956	0.8802	0.973	0.9869	0.9256	0.956
8.2935	34.0	4590	0.7625	0.9263	0.9721	0.9577	0.8003	0.95	0.9698	0.0633	0.5599	0.9556	0.8796	0.9729	0.9856	0.9263	0.9556
8.2935	35.0	4725	0.7581	0.9265	0.972	0.9589	0.8056	0.9495	0.9702	0.0633	0.5601	0.9557	0.8812	0.9719	0.988	0.9265	0.9557
8.2935	36.0	4860	0.7610	0.9267	0.9717	0.9582	0.8065	0.951	0.972	0.0633	0.5611	0.9563	0.8848	0.9716	0.9887	0.9267	0.9563
8.2935	37.0	4995	0.7533	0.9276	0.9718	0.9589	0.807	0.95	0.9712	0.0633	0.5609	0.9562	0.8825	0.9725	0.9869	0.9276	0.9562
8.2062	38.0	5130	0.7569	0.9277	0.972	0.9577	0.8062	0.9502	0.9695	0.0633	0.5615	0.9565	0.8848	0.9726	0.9859	0.9277	0.9565
8.2062	39.0	5265	0.7547	0.9267	0.972	0.9588	0.8038	0.9503	0.9702	0.0633	0.5613	0.9553	0.8814	0.9717	0.9863	0.9267	0.9553
8.2062	40.0	5400	0.7581	0.9273	0.9716	0.9588	0.8034	0.9519	0.9734	0.0633	0.5602	0.9563	0.8809	0.9733	0.9869	0.9273	0.9563
8.2161	41.0	5535	0.7529	0.9267	0.9707	0.9585	0.8044	0.951	0.9715	0.0633	0.5602	0.9563	0.8827	0.9727	0.9869	0.9267	0.9563
8.2161	42.0	5670	0.7590	0.9264	0.9705	0.957	0.8025	0.9506	0.9676	0.0633	0.5614	0.9557	0.8807	0.9727	0.9859	0.9264	0.9557
8.2161	43.0	5805	0.7541	0.9271	0.9716	0.9582	0.803	0.9519	0.9704	0.0633	0.5614	0.9566	0.8807	0.9739	0.9866	0.9271	0.9566
8.2161	44.0	5940	0.7507	0.9282	0.9711	0.9585	0.8069	0.9532	0.9724	0.0633	0.5612	0.9577	0.8853	0.9739	0.9876	0.9282	0.9577
8.1444	45.0	6075	0.7518	0.9272	0.9706	0.9579	0.8046	0.9529	0.9714	0.0633	0.5609	0.9569	0.8814	0.9738	0.9876	0.9272	0.9569

Framework versions

Transformers 5.13.1
Pytorch 2.13.0+cu130
Datasets 5.0.0
Tokenizers 0.22.2

Nevico/dfine-small-remia-cartons-v2

dfine-small-remia-cartons-v2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Nevico/
dfine-small-remia-cartons-v2