fb_detr_finetuned_diana

LLyq/fb_detr_finetuned_diana

fb_detr_finetuned_diana is a object detection model from LLyq. 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: detr
Access: Public
Created: Jun 11, 2024
Updated: Jul 30, 2024
SHA: 875c4ccc

Base models

facebook/detr-resnet-50

Datasets

imagefolder

Model card

From the Hugging Face model README

fb_detr_finetuned_diana

This model is a fine-tuned version of facebook/detr-resnet-50 on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 0.3238
Map: 0.7325
Map 50: 0.8805
Map 75: 0.8535
Map Small: -1.0
Map Medium: 0.7891
Map Large: 0.7273
Mar 1: 0.0881
Mar 10: 0.7675
Mar 100: 0.8712
Mar Small: -1.0
Mar Medium: 0.8348
Mar Large: 0.886
Map Per Class: -1.0
Mar 100 Per Class: -1.0
Classes: 0

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
num_epochs: 100

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 Per Class	Mar 100 Per Class
2.0159	1.0	10	1.9364	0.0	0.0	0.0	-1.0	0.0	0.0	0.0	0.0	0.0	-1.0	0.0	0.0	-1.0	-1.0
1.731	2.0	20	1.6869	0.0	0.0	0.0	-1.0	0.0	0.0	0.0	0.0	0.0	-1.0	0.0	0.0	-1.0	-1.0
1.5773	3.0	30	1.6082	0.0	0.0	0.0	-1.0	0.0	0.0	0.0	0.0	0.0	-1.0	0.0	0.0	-1.0	-1.0
1.7825	4.0	40	1.4512	0.0042	0.0099	0.0	-1.0	0.0119	0.0025	0.0025	0.0056	0.0056	-1.0	0.0087	0.0044	-1.0	-1.0
1.4306	5.0	50	1.2470	0.0424	0.075	0.0531	-1.0	0.0473	0.0424	0.0431	0.0688	0.0688	-1.0	0.0652	0.0702	-1.0	-1.0
1.2657	6.0	60	1.1537	0.0327	0.0521	0.0363	-1.0	0.0436	0.0286	0.0281	0.0344	0.0344	-1.0	0.0478	0.0289	-1.0	-1.0
1.3114	7.0	70	1.0515	0.0933	0.148	0.114	-1.0	0.072	0.1029	0.0556	0.1156	0.1156	-1.0	0.0739	0.1325	-1.0	-1.0
1.0453	8.0	80	0.9494	0.1865	0.2552	0.2174	-1.0	0.1565	0.1983	0.0737	0.2219	0.2219	-1.0	0.1674	0.2439	-1.0	-1.0
0.8954	9.0	90	0.8976	0.2919	0.4271	0.3403	-1.0	0.2369	0.3188	0.0756	0.3906	0.4038	-1.0	0.3522	0.4246	-1.0	-1.0
0.9844	10.0	100	0.9485	0.3314	0.5102	0.4147	-1.0	0.3038	0.351	0.0688	0.4244	0.4412	-1.0	0.3543	0.4763	-1.0	-1.0
0.8282	11.0	110	0.8403	0.4211	0.6222	0.5098	-1.0	0.3505	0.4606	0.0819	0.5256	0.5694	-1.0	0.413	0.6325	-1.0	-1.0
0.7106	12.0	120	0.7935	0.431	0.6385	0.5331	-1.0	0.3495	0.4761	0.0794	0.5612	0.6281	-1.0	0.5609	0.6553	-1.0	-1.0
0.6526	13.0	130	0.7319	0.5166	0.7537	0.6577	-1.0	0.4806	0.5376	0.075	0.6	0.6762	-1.0	0.6152	0.7009	-1.0	-1.0
0.7241	14.0	140	0.7162	0.5073	0.715	0.6429	-1.0	0.4718	0.5377	0.0806	0.5688	0.6594	-1.0	0.5696	0.6956	-1.0	-1.0
0.771	15.0	150	0.6368	0.5778	0.7847	0.716	-1.0	0.5218	0.6118	0.0812	0.6325	0.7219	-1.0	0.6261	0.7605	-1.0	-1.0
0.6217	16.0	160	0.6107	0.5797	0.8084	0.7379	-1.0	0.5941	0.586	0.085	0.6313	0.7319	-1.0	0.6913	0.7482	-1.0	-1.0
0.6656	17.0	170	0.6412	0.5931	0.8074	0.7118	-1.0	0.5751	0.6115	0.0938	0.6562	0.7344	-1.0	0.6391	0.7728	-1.0	-1.0
0.4162	18.0	180	0.6373	0.5991	0.8189	0.7538	-1.0	0.6026	0.6037	0.0913	0.6438	0.7487	-1.0	0.7	0.7684	-1.0	-1.0
0.538	19.0	190	0.5741	0.6192	0.8493	0.7732	-1.0	0.6516	0.6082	0.0844	0.6363	0.7644	-1.0	0.7587	0.7667	-1.0	-1.0
0.3672	20.0	200	0.5242	0.6256	0.8228	0.7781	-1.0	0.6944	0.6089	0.0794	0.6694	0.7906	-1.0	0.7957	0.7886	-1.0	-1.0
0.3685	21.0	210	0.4954	0.6548	0.8544	0.8291	-1.0	0.6707	0.6608	0.0875	0.6856	0.7862	-1.0	0.7217	0.8123	-1.0	-1.0
0.5199	22.0	220	0.4870	0.665	0.8679	0.8399	-1.0	0.681	0.6694	0.09	0.7006	0.805	-1.0	0.7565	0.8246	-1.0	-1.0
0.545	23.0	230	0.4580	0.6669	0.8667	0.8309	-1.0	0.6986	0.6642	0.0913	0.7013	0.8025	-1.0	0.787	0.8088	-1.0	-1.0
0.3932	24.0	240	0.4901	0.6494	0.8679	0.7951	-1.0	0.6509	0.6644	0.0831	0.6775	0.7887	-1.0	0.713	0.8193	-1.0	-1.0
0.5348	25.0	250	0.4542	0.6652	0.8623	0.8064	-1.0	0.6761	0.6794	0.0962	0.7	0.805	-1.0	0.7478	0.8281	-1.0	-1.0
0.4903	26.0	260	0.4622	0.6599	0.855	0.8212	-1.0	0.6611	0.6745	0.0956	0.69	0.7981	-1.0	0.7261	0.8272	-1.0	-1.0
0.586	27.0	270	0.4812	0.6611	0.8652	0.8148	-1.0	0.6619	0.6732	0.0962	0.68	0.795	-1.0	0.7413	0.8167	-1.0	-1.0
0.3898	28.0	280	0.4864	0.6606	0.8411	0.8023	-1.0	0.6398	0.678	0.1037	0.69	0.8012	-1.0	0.7522	0.8211	-1.0	-1.0
0.3738	29.0	290	0.5301	0.6366	0.8379	0.7826	-1.0	0.6521	0.6493	0.0862	0.6737	0.7725	-1.0	0.7196	0.7939	-1.0	-1.0
0.5067	30.0	300	0.4871	0.6597	0.8465	0.8017	-1.0	0.65	0.6705	0.0956	0.7006	0.8031	-1.0	0.7696	0.8167	-1.0	-1.0
0.4212	31.0	310	0.4221	0.7033	0.8798	0.8324	-1.0	0.7001	0.7165	0.0887	0.7237	0.8338	-1.0	0.7826	0.8544	-1.0	-1.0
0.4625	32.0	320	0.4304	0.7179	0.8835	0.8514	-1.0	0.7284	0.721	0.1006	0.7275	0.8338	-1.0	0.7848	0.8535	-1.0	-1.0
0.4318	33.0	330	0.4246	0.6794	0.8574	0.8077	-1.0	0.6674	0.6904	0.0938	0.715	0.8206	-1.0	0.7761	0.8386	-1.0	-1.0
0.5166	34.0	340	0.4357	0.6692	0.8476	0.8146	-1.0	0.6649	0.6812	0.0862	0.71	0.8169	-1.0	0.7543	0.8421	-1.0	-1.0
0.4435	35.0	350	0.4045	0.6748	0.8531	0.8211	-1.0	0.662	0.6862	0.0938	0.7113	0.8163	-1.0	0.7587	0.8395	-1.0	-1.0
0.3236	36.0	360	0.4110	0.6776	0.8527	0.8265	-1.0	0.6929	0.6858	0.0831	0.7163	0.8256	-1.0	0.7413	0.8596	-1.0	-1.0
0.4923	37.0	370	0.4340	0.6749	0.8531	0.8088	-1.0	0.7001	0.6776	0.0938	0.7081	0.8144	-1.0	0.7543	0.8386	-1.0	-1.0
0.4057	38.0	380	0.4256	0.69	0.8742	0.8284	-1.0	0.7185	0.6876	0.0925	0.7119	0.8194	-1.0	0.7739	0.8377	-1.0	-1.0
0.3833	39.0	390	0.4131	0.7058	0.8661	0.8408	-1.0	0.703	0.7183	0.0981	0.7244	0.8238	-1.0	0.7522	0.8526	-1.0	-1.0
0.3845	40.0	400	0.4475	0.6838	0.8654	0.8107	-1.0	0.7109	0.6807	0.0975	0.7188	0.8188	-1.0	0.787	0.8316	-1.0	-1.0
0.3881	41.0	410	0.4030	0.7142	0.8812	0.8569	-1.0	0.7143	0.727	0.095	0.7362	0.8338	-1.0	0.7826	0.8544	-1.0	-1.0
0.3441	42.0	420	0.3964	0.7087	0.8683	0.841	-1.0	0.7332	0.7113	0.0938	0.7356	0.8406	-1.0	0.8043	0.8553	-1.0	-1.0
0.3544	43.0	430	0.4157	0.6905	0.8643	0.8324	-1.0	0.6984	0.6989	0.0938	0.7312	0.8231	-1.0	0.7783	0.8412	-1.0	-1.0
0.3639	44.0	440	0.3973	0.6977	0.8656	0.8399	-1.0	0.7067	0.7048	0.0931	0.7394	0.8369	-1.0	0.7783	0.8605	-1.0	-1.0
0.2883	45.0	450	0.3685	0.7138	0.8743	0.8473	-1.0	0.7572	0.7094	0.0931	0.7456	0.85	-1.0	0.8	0.8702	-1.0	-1.0
0.3492	46.0	460	0.3839	0.7069	0.88	0.8323	-1.0	0.7024	0.7238	0.0938	0.7469	0.8356	-1.0	0.7413	0.8737	-1.0	-1.0
0.2949	47.0	470	0.3781	0.7074	0.8604	0.8427	-1.0	0.7014	0.7273	0.1	0.7431	0.8388	-1.0	0.7565	0.8719	-1.0	-1.0
0.4604	48.0	480	0.3945	0.7123	0.8803	0.8474	-1.0	0.7103	0.722	0.1	0.73	0.84	-1.0	0.7957	0.8579	-1.0	-1.0
0.321	49.0	490	0.4030	0.7034	0.8772	0.8431	-1.0	0.7357	0.7052	0.0944	0.7425	0.8394	-1.0	0.8	0.8553	-1.0	-1.0
0.3609	50.0	500	0.3718	0.7088	0.8648	0.839	-1.0	0.751	0.7042	0.095	0.7462	0.8438	-1.0	0.8065	0.8588	-1.0	-1.0
0.3086	51.0	510	0.3798	0.7087	0.8698	0.8387	-1.0	0.7261	0.7106	0.0869	0.7469	0.8419	-1.0	0.7957	0.8605	-1.0	-1.0
0.3784	52.0	520	0.3669	0.7224	0.8709	0.847	-1.0	0.7484	0.7224	0.0913	0.7481	0.8506	-1.0	0.8109	0.8667	-1.0	-1.0
0.3195	53.0	530	0.3884	0.719	0.8717	0.8384	-1.0	0.72	0.7274	0.0887	0.7519	0.8494	-1.0	0.7826	0.8763	-1.0	-1.0
0.3255	54.0	540	0.3421	0.7255	0.8763	0.8435	-1.0	0.7377	0.7317	0.0956	0.7581	0.8544	-1.0	0.8022	0.8754	-1.0	-1.0
0.4141	55.0	550	0.3541	0.7143	0.8728	0.8388	-1.0	0.7587	0.7078	0.0887	0.7556	0.8537	-1.0	0.8217	0.8667	-1.0	-1.0
0.2409	56.0	560	0.3493	0.7317	0.8747	0.8485	-1.0	0.7642	0.7298	0.0975	0.7606	0.8644	-1.0	0.8196	0.8825	-1.0	-1.0
0.2739	57.0	570	0.3364	0.7324	0.8825	0.8489	-1.0	0.7642	0.7313	0.1	0.7619	0.8644	-1.0	0.8283	0.8789	-1.0	-1.0
0.2322	58.0	580	0.3423	0.7279	0.8817	0.849	-1.0	0.7463	0.7321	0.0994	0.7606	0.86	-1.0	0.8283	0.8728	-1.0	-1.0
0.3043	59.0	590	0.3376	0.7285	0.8812	0.8455	-1.0	0.7519	0.7362	0.0988	0.7644	0.8669	-1.0	0.8043	0.8921	-1.0	-1.0
0.2806	60.0	600	0.3639	0.714	0.8667	0.8374	-1.0	0.7335	0.7263	0.0969	0.7506	0.8481	-1.0	0.7739	0.8781	-1.0	-1.0
0.318	61.0	610	0.3444	0.7169	0.8734	0.8391	-1.0	0.7709	0.7108	0.0894	0.755	0.8531	-1.0	0.8283	0.8632	-1.0	-1.0
0.3217	62.0	620	0.3392	0.7223	0.8816	0.8381	-1.0	0.7649	0.7182	0.0913	0.7594	0.8525	-1.0	0.8217	0.8649	-1.0	-1.0
0.2648	63.0	630	0.3447	0.7304	0.8981	0.8486	-1.0	0.7663	0.7293	0.0913	0.7588	0.8562	-1.0	0.8174	0.8719	-1.0	-1.0
0.3217	64.0	640	0.3501	0.7195	0.8944	0.8453	-1.0	0.762	0.7178	0.0906	0.7538	0.8512	-1.0	0.8196	0.864	-1.0	-1.0
0.2912	65.0	650	0.3418	0.7329	0.8944	0.8616	-1.0	0.7591	0.7373	0.0925	0.7625	0.8625	-1.0	0.813	0.8825	-1.0	-1.0
0.2591	66.0	660	0.3400	0.7314	0.8877	0.8562	-1.0	0.7498	0.736	0.0913	0.7619	0.8637	-1.0	0.8174	0.8825	-1.0	-1.0
0.2844	67.0	670	0.3459	0.7237	0.8786	0.8412	-1.0	0.7613	0.7255	0.0925	0.7506	0.8587	-1.0	0.8217	0.8737	-1.0	-1.0
0.3221	68.0	680	0.3366	0.7345	0.8877	0.8484	-1.0	0.7735	0.7333	0.0913	0.7581	0.8669	-1.0	0.8326	0.8807	-1.0	-1.0
0.2491	69.0	690	0.3325	0.7344	0.8858	0.8472	-1.0	0.7777	0.7336	0.09	0.765	0.8675	-1.0	0.8326	0.8816	-1.0	-1.0
0.2743	70.0	700	0.3317	0.7345	0.885	0.8475	-1.0	0.7754	0.7333	0.0913	0.7638	0.8681	-1.0	0.8304	0.8833	-1.0	-1.0
0.249	71.0	710	0.3184	0.7371	0.8827	0.8521	-1.0	0.7685	0.7391	0.09	0.7669	0.8737	-1.0	0.8283	0.8921	-1.0	-1.0
0.2721	72.0	720	0.3230	0.7393	0.8939	0.8545	-1.0	0.7696	0.7442	0.0969	0.7588	0.8625	-1.0	0.8109	0.8833	-1.0	-1.0
0.2454	73.0	730	0.3237	0.7362	0.8887	0.8515	-1.0	0.7709	0.7396	0.0887	0.7688	0.8662	-1.0	0.8174	0.886	-1.0	-1.0
0.2494	74.0	740	0.3218	0.7319	0.8865	0.8486	-1.0	0.7672	0.735	0.0894	0.7719	0.8669	-1.0	0.8152	0.8877	-1.0	-1.0
0.2481	75.0	750	0.3195	0.7349	0.8834	0.8549	-1.0	0.782	0.7315	0.09	0.7781	0.8712	-1.0	0.837	0.8851	-1.0	-1.0
0.2278	76.0	760	0.3284	0.7275	0.8751	0.8398	-1.0	0.7878	0.7173	0.0894	0.7581	0.8625	-1.0	0.837	0.8728	-1.0	-1.0
0.2639	77.0	770	0.3241	0.7257	0.8745	0.8468	-1.0	0.7836	0.719	0.09	0.7613	0.865	-1.0	0.8283	0.8798	-1.0	-1.0
0.2158	78.0	780	0.3249	0.7287	0.8809	0.8523	-1.0	0.7779	0.7241	0.0906	0.7581	0.8619	-1.0	0.8239	0.8772	-1.0	-1.0
0.2259	79.0	790	0.3289	0.7277	0.8803	0.8534	-1.0	0.7718	0.7247	0.09	0.7544	0.8581	-1.0	0.8174	0.8746	-1.0	-1.0
0.2361	80.0	800	0.3318	0.73	0.8758	0.8598	-1.0	0.7768	0.7308	0.0906	0.7575	0.8612	-1.0	0.813	0.8807	-1.0	-1.0
0.2708	81.0	810	0.3279	0.7327	0.8865	0.8588	-1.0	0.7773	0.7344	0.0906	0.7638	0.8656	-1.0	0.8152	0.886	-1.0	-1.0
0.2111	82.0	820	0.3223	0.7336	0.8849	0.859	-1.0	0.7817	0.731	0.09	0.7681	0.8681	-1.0	0.8261	0.8851	-1.0	-1.0
0.2663	83.0	830	0.3269	0.7337	0.885	0.8573	-1.0	0.7893	0.727	0.0913	0.7644	0.8681	-1.0	0.837	0.8807	-1.0	-1.0
0.2105	84.0	840	0.3259	0.7339	0.8851	0.859	-1.0	0.7812	0.7296	0.0906	0.7625	0.8669	-1.0	0.8326	0.8807	-1.0	-1.0
0.2211	85.0	850	0.3169	0.7355	0.8863	0.8611	-1.0	0.7978	0.7258	0.0962	0.7606	0.8675	-1.0	0.8457	0.8763	-1.0	-1.0
0.2243	86.0	860	0.3155	0.7369	0.8836	0.8592	-1.0	0.7924	0.7307	0.0956	0.765	0.8712	-1.0	0.8391	0.8842	-1.0	-1.0
0.1953	87.0	870	0.3225	0.7318	0.8818	0.8561	-1.0	0.7817	0.7283	0.0906	0.7644	0.8681	-1.0	0.8304	0.8833	-1.0	-1.0
0.2024	88.0	880	0.3245	0.7308	0.8832	0.8571	-1.0	0.7827	0.7272	0.0906	0.7625	0.865	-1.0	0.8261	0.8807	-1.0	-1.0
0.2507	89.0	890	0.3273	0.7262	0.8815	0.8459	-1.0	0.7833	0.7205	0.0881	0.76	0.8631	-1.0	0.8283	0.8772	-1.0	-1.0
0.2073	90.0	900	0.3236	0.7302	0.8798	0.8521	-1.0	0.7872	0.7254	0.0887	0.7644	0.8687	-1.0	0.8348	0.8825	-1.0	-1.0
0.1975	91.0	910	0.3268	0.7269	0.8788	0.8512	-1.0	0.7827	0.7236	0.0881	0.7631	0.8669	-1.0	0.8326	0.8807	-1.0	-1.0
0.2445	92.0	920	0.3260	0.7285	0.8797	0.8519	-1.0	0.7872	0.724	0.0881	0.7638	0.8681	-1.0	0.8348	0.8816	-1.0	-1.0
0.1991	93.0	930	0.3266	0.7296	0.8797	0.8522	-1.0	0.7874	0.7251	0.0881	0.7644	0.8687	-1.0	0.8348	0.8825	-1.0	-1.0
0.2979	94.0	940	0.3252	0.7318	0.8806	0.853	-1.0	0.7925	0.7267	0.0881	0.7669	0.8712	-1.0	0.837	0.8851	-1.0	-1.0
0.2172	95.0	950	0.3243	0.7317	0.8813	0.8542	-1.0	0.7901	0.7267	0.0881	0.7663	0.87	-1.0	0.8348	0.8842	-1.0	-1.0
0.2317	96.0	960	0.3236	0.733	0.8808	0.8539	-1.0	0.7935	0.7269	0.0881	0.7681	0.8719	-1.0	0.837	0.886	-1.0	-1.0
0.2501	97.0	970	0.3237	0.733	0.8805	0.8536	-1.0	0.7927	0.7273	0.0881	0.7681	0.8719	-1.0	0.837	0.886	-1.0	-1.0
0.204	98.0	980	0.3238	0.7325	0.8805	0.8535	-1.0	0.7891	0.7273	0.0881	0.7675	0.8712	-1.0	0.8348	0.886	-1.0	-1.0
0.3266	99.0	990	0.3238	0.7325	0.8805	0.8535	-1.0	0.7891	0.7273	0.0881	0.7675	0.8712	-1.0	0.8348	0.886	-1.0	-1.0
0.1921	100.0	1000	0.3238	0.7325	0.8805	0.8535	-1.0	0.7891	0.7273	0.0881	0.7675	0.8712	-1.0	0.8348	0.886	-1.0	-1.0

Framework versions

Transformers 4.41.1
Pytorch 2.2.1+cu121
Datasets 2.19.1
Tokenizers 0.19.1

Task: Object Detection
Library: transformers
Type: detr
License: apache-2.0
Created: Jun 11, 2024
Updated: Jul 30, 2024