detr_domain_shift

toukapy/detr_domain_shift

detr_domain_shift is a object detection model from toukapy. 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: conditional_detr
Access: Public
Created: Mar 8, 2025
Updated: Mar 9, 2025
SHA: f1d0d3e1

Base models

microsoft/conditional-detr-resnet-50

Model card

From the Hugging Face model README

detr_domain_shift

This model is a fine-tuned version of microsoft/conditional-detr-resnet-50 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.4246
Map: 0.8353
Map 50: 0.9529
Map 75: 0.9029
Map Small: 0.0159
Map Medium: 0.6742
Map Large: 0.8707
Mar 1: 0.7106
Mar 10: 0.8977
Mar 100: 0.9152
Mar Small: 0.2984
Mar Medium: 0.8276
Mar Large: 0.9365
Map Garbage bag: 0.8185
Mar 100 Garbage bag: 0.9059
Map Paper bag: 0.8446
Mar 100 Paper bag: 0.9239
Map Plastic bag: 0.8429
Mar 100 Plastic bag: 0.9159

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: 0.0001
train_batch_size: 8
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: 50

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 Garbage bag	Mar 100 Garbage bag	Map Paper bag	Mar 100 Paper bag	Map Plastic bag	Mar 100 Plastic bag
0.9775	1.0	1557	0.8739	0.2419	0.3276	0.2719	0.0003	0.1808	0.2566	0.4246	0.773	0.8186	0.0271	0.6849	0.8501	0.1999	0.808	0.3045	0.8292	0.2213	0.8187
0.919	2.0	3114	0.8527	0.4465	0.6037	0.5018	0.0043	0.2877	0.4787	0.5098	0.7627	0.8137	0.0123	0.6656	0.8474	0.5496	0.8075	0.4518	0.8235	0.3382	0.8101
0.85	3.0	4671	0.7649	0.5508	0.7268	0.6183	0.0013	0.3684	0.5898	0.5619	0.7944	0.8335	0.0652	0.7147	0.8613	0.5635	0.8206	0.5877	0.8471	0.5012	0.8327
0.844	4.0	6228	0.7562	0.605	0.7924	0.6857	0.0023	0.4402	0.6405	0.5732	0.7901	0.8296	0.0579	0.7174	0.856	0.6113	0.8213	0.6125	0.8364	0.5912	0.8313
0.8332	5.0	7785	0.7811	0.5982	0.8004	0.6799	0.007	0.4141	0.6365	0.5683	0.7801	0.8214	0.0194	0.6914	0.852	0.5785	0.8091	0.6326	0.8361	0.5834	0.8188
0.9303	6.0	9342	0.9325	0.5179	0.7395	0.5906	0.0001	0.3665	0.5506	0.5192	0.7288	0.7756	0.0097	0.6358	0.8074	0.52	0.7664	0.5744	0.7825	0.4593	0.7778
0.8773	7.0	10899	0.8869	0.5561	0.7748	0.626	0.0	0.374	0.5948	0.547	0.748	0.7895	0.0	0.6483	0.8223	0.5435	0.7752	0.5909	0.8132	0.5339	0.7801
1.011	8.0	12456	0.8729	0.5604	0.7945	0.6437	0.0013	0.3991	0.5954	0.538	0.7475	0.7971	0.0218	0.6489	0.831	0.5251	0.7729	0.6152	0.8222	0.541	0.7962
1.0019	9.0	14013	1.2187	0.313	0.5258	0.3396	0.0	0.2026	0.337	0.3859	0.6118	0.6892	0.0	0.5141	0.7282	0.4395	0.7076	0.2496	0.6916	0.25	0.6685
0.9286	10.0	15570	0.8059	0.5848	0.7852	0.6584	0.0	0.3874	0.6257	0.5595	0.7725	0.8196	0.0179	0.6689	0.8539	0.5762	0.8015	0.6239	0.8429	0.5544	0.8143
0.8782	11.0	17127	0.8458	0.5587	0.7551	0.627	0.01	0.377	0.596	0.5551	0.7678	0.812	0.0516	0.6635	0.8453	0.5726	0.7966	0.6164	0.8355	0.4872	0.804
0.8493	12.0	18684	0.7872	0.5899	0.7787	0.6622	0.0012	0.3803	0.6329	0.57	0.7832	0.8287	0.019	0.6719	0.8643	0.5813	0.8215	0.6336	0.8412	0.5548	0.8235
0.793	13.0	20241	0.7784	0.6112	0.8128	0.6924	0.0023	0.4275	0.6502	0.5785	0.7783	0.8249	0.0434	0.6872	0.8566	0.6157	0.8253	0.6326	0.8344	0.5852	0.8151
0.7712	14.0	21798	0.7881	0.6089	0.8162	0.688	0.0001	0.4211	0.6497	0.5772	0.7785	0.8184	0.039	0.6874	0.8491	0.5984	0.803	0.6429	0.84	0.5853	0.8123
0.7892	15.0	23355	0.7204	0.6548	0.8515	0.742	0.0007	0.486	0.6916	0.6018	0.7991	0.8376	0.0359	0.7139	0.8668	0.653	0.8377	0.6716	0.8447	0.6399	0.8302
0.7735	16.0	24912	0.7768	0.604	0.7908	0.6807	0.0152	0.4142	0.6445	0.5803	0.7794	0.8258	0.043	0.7167	0.8522	0.5854	0.8359	0.6421	0.8307	0.5844	0.8106
0.8052	17.0	26469	0.7466	0.6389	0.8417	0.7325	0.0001	0.4658	0.6767	0.5883	0.7847	0.8231	0.0245	0.7291	0.8469	0.6493	0.8262	0.6572	0.8329	0.6101	0.8101
0.7366	18.0	28026	0.7490	0.6372	0.8435	0.7198	0.0069	0.4492	0.6783	0.5883	0.7881	0.8287	0.0271	0.7084	0.8572	0.6427	0.8307	0.6486	0.8376	0.6202	0.8178
0.7316	19.0	29583	0.6964	0.6697	0.869	0.7578	0.0028	0.5095	0.704	0.6068	0.8029	0.839	0.0705	0.7283	0.8651	0.6529	0.8277	0.6915	0.8538	0.6646	0.8353
0.7243	20.0	31140	0.7165	0.6616	0.8605	0.753	0.0033	0.4782	0.7003	0.6046	0.7972	0.8299	0.0581	0.7148	0.8574	0.6366	0.8126	0.6791	0.8452	0.6692	0.832
0.7189	21.0	32697	0.6921	0.6748	0.8694	0.7621	0.001	0.5019	0.7121	0.6105	0.8042	0.8382	0.0788	0.7253	0.8649	0.6422	0.8241	0.7087	0.8581	0.6735	0.8324
0.6802	22.0	34254	0.6381	0.7091	0.886	0.7875	0.0007	0.5366	0.7465	0.6318	0.8291	0.8618	0.0716	0.752	0.8883	0.6953	0.8572	0.7253	0.8718	0.7067	0.8565
0.6676	23.0	35811	0.6252	0.7186	0.8865	0.7994	0.0034	0.5423	0.7573	0.6391	0.8373	0.8649	0.0665	0.7597	0.8908	0.7021	0.8567	0.7358	0.8752	0.7181	0.8628
0.6624	24.0	37368	0.6432	0.7117	0.8986	0.8041	0.0019	0.5384	0.7488	0.63	0.8205	0.8535	0.0974	0.7492	0.8786	0.6871	0.8394	0.7287	0.8639	0.7194	0.8572
0.6356	25.0	38925	0.6101	0.7284	0.905	0.8178	0.004	0.5444	0.7676	0.6448	0.8322	0.863	0.1108	0.7616	0.8874	0.7125	0.8556	0.7417	0.8709	0.7311	0.8626
0.6319	26.0	40482	0.6330	0.7191	0.9005	0.8113	0.0085	0.557	0.754	0.6392	0.8262	0.8513	0.106	0.7566	0.8745	0.702	0.849	0.7371	0.8558	0.7182	0.8489
0.6069	27.0	42039	0.5855	0.7461	0.9072	0.824	0.0082	0.5615	0.7852	0.6512	0.845	0.8742	0.2484	0.7625	0.9003	0.7159	0.8596	0.7615	0.884	0.7609	0.8791
0.5898	28.0	43596	0.5582	0.7581	0.9158	0.8405	0.0091	0.5844	0.7957	0.6649	0.8552	0.878	0.2474	0.785	0.9008	0.7384	0.8677	0.7742	0.8882	0.7616	0.8782
0.5777	29.0	45153	0.5412	0.7706	0.9226	0.8492	0.0029	0.6117	0.8054	0.6718	0.8591	0.8878	0.2147	0.7882	0.9118	0.7542	0.8826	0.7799	0.8953	0.7777	0.8854
0.5461	30.0	46710	0.5424	0.7714	0.9259	0.8563	0.0024	0.6033	0.8081	0.6708	0.8571	0.8829	0.206	0.7823	0.9069	0.7602	0.8784	0.7814	0.8906	0.7726	0.8798
0.5392	31.0	48267	0.5274	0.7773	0.9219	0.8591	0.0026	0.5986	0.8159	0.6752	0.8648	0.8888	0.2832	0.795	0.9111	0.7549	0.8835	0.7902	0.894	0.7867	0.8889
0.5367	32.0	49824	0.5181	0.7863	0.9312	0.8654	0.0038	0.6234	0.8216	0.678	0.8663	0.8882	0.2332	0.7956	0.9109	0.7689	0.8805	0.7985	0.8962	0.7915	0.8879
0.5187	33.0	51381	0.5079	0.7853	0.934	0.8672	0.0187	0.6245	0.8206	0.6814	0.8681	0.8917	0.2412	0.7984	0.9143	0.7692	0.89	0.7937	0.8966	0.7931	0.8884
0.5102	34.0	52938	0.4861	0.8049	0.9381	0.8761	0.0318	0.6481	0.8388	0.6912	0.8811	0.9047	0.2659	0.818	0.9262	0.7893	0.8991	0.8191	0.914	0.8062	0.901
0.4868	35.0	54495	0.4753	0.8046	0.9392	0.8827	0.0084	0.6389	0.8413	0.6933	0.8796	0.9015	0.2495	0.8056	0.9249	0.7884	0.8981	0.811	0.9036	0.8143	0.903
0.4821	36.0	56052	0.4714	0.8096	0.9427	0.8861	0.0225	0.6485	0.8448	0.6955	0.8828	0.9042	0.278	0.8159	0.9258	0.7923	0.8981	0.8221	0.9121	0.8143	0.9024
0.4714	37.0	57609	0.4447	0.8232	0.9433	0.8911	0.0219	0.6619	0.8599	0.7032	0.8935	0.9126	0.269	0.8235	0.9344	0.8072	0.9051	0.8295	0.9173	0.8329	0.9154
0.4653	38.0	59166	0.4554	0.819	0.946	0.8912	0.0178	0.6567	0.8548	0.7021	0.8873	0.9059	0.3004	0.8138	0.9281	0.8025	0.899	0.8281	0.9122	0.8264	0.9065
0.4494	39.0	60723	0.4310	0.8308	0.9451	0.8939	0.0243	0.6685	0.8663	0.7091	0.8985	0.918	0.3242	0.8358	0.9381	0.8127	0.9114	0.8401	0.9237	0.8397	0.919
0.4389	40.0	62280	0.4289	0.8336	0.9489	0.8967	0.0177	0.6757	0.8684	0.7102	0.8976	0.9165	0.2958	0.8329	0.9369	0.8167	0.9102	0.8425	0.9219	0.8416	0.9174
0.4376	41.0	63837	0.4245	0.8365	0.9498	0.9011	0.0179	0.6795	0.8709	0.7122	0.8985	0.9182	0.3335	0.8382	0.9377	0.8167	0.9067	0.8477	0.9272	0.845	0.9205
0.4252	42.0	65394	0.4244	0.8368	0.9511	0.8998	0.0175	0.6802	0.8713	0.7106	0.8988	0.9166	0.3604	0.8331	0.9369	0.8183	0.9089	0.8467	0.9229	0.8456	0.9179
0.4215	43.0	66951	0.4281	0.8342	0.9517	0.8987	0.0297	0.6731	0.8696	0.7088	0.8985	0.9159	0.3176	0.83	0.9369	0.8177	0.9092	0.8431	0.9217	0.8418	0.9169
0.4279	44.0	68508	0.4235	0.8375	0.9527	0.9012	0.0191	0.6777	0.873	0.7116	0.8984	0.9164	0.32	0.8288	0.9376	0.8191	0.9094	0.8479	0.9226	0.8453	0.9172
0.4133	45.0	70065	0.4220	0.837	0.9525	0.9014	0.0168	0.6764	0.8719	0.7117	0.9	0.9175	0.3059	0.8353	0.9377	0.8168	0.9081	0.8488	0.9244	0.8455	0.9199
0.4085	46.0	71622	0.4231	0.837	0.9538	0.9026	0.0158	0.679	0.8721	0.7118	0.8986	0.9157	0.2905	0.8276	0.9371	0.8196	0.908	0.8463	0.9227	0.8451	0.9165
0.4138	47.0	73179	0.4269	0.8335	0.9529	0.9019	0.014	0.6735	0.8689	0.7097	0.8965	0.9141	0.2954	0.8246	0.9358	0.8145	0.9048	0.8436	0.9226	0.8424	0.9149
0.4147	48.0	74736	0.4246	0.8353	0.9529	0.9023	0.0158	0.6736	0.8709	0.7108	0.8979	0.9155	0.2982	0.8266	0.937	0.8182	0.9062	0.8447	0.9242	0.843	0.916
0.4145	49.0	76293	0.4237	0.8362	0.9531	0.9027	0.0159	0.6751	0.8715	0.7108	0.8984	0.916	0.2984	0.8286	0.9373	0.8192	0.9067	0.8454	0.9248	0.8439	0.9167
0.406	50.0	77850	0.4246	0.8353	0.9529	0.9029	0.0159	0.6742	0.8707	0.7106	0.8977	0.9152	0.2984	0.8276	0.9365	0.8185	0.9059	0.8446	0.9239	0.8429	0.9159

Framework versions

Transformers 4.49.0
Pytorch 2.5.1+cu118
Datasets 3.3.2
Tokenizers 0.21.0

Task: Object Detection
Library: transformers
Type: conditional_detr
License: apache-2.0
Created: Mar 8, 2025
Updated: Mar 9, 2025