custom-object-masking_v4-windows

sungile/custom-object-masking_v4-windows

custom-object-masking_v4-windows is a image segmentation model from sungile. Use it for the image segmentation task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as other.

should probably proofread and complete it, then remove this comment. --

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29.8 MB on disk

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At a glance

Task: Image Segmentation
Library: transformers
License: other
Model type: segformer
Access: Public
Created: Jan 17, 2025
Updated: Jan 17, 2025
SHA: 5f78ce60

Base models

nvidia/mit-b0

Model card

From the Hugging Face model README

custom-object-masking_v4-windows

This model is a fine-tuned version of nvidia/mit-b0 on the sungile/custom-object-masking_v4_windows dataset. It achieves the following results on the evaluation set:

Loss: 0.0683
Mean Iou: 0.8920
Mean Accuracy: 0.9387
Overall Accuracy: 0.9781
Accuracy Unknown: nan
Accuracy Background: 0.9894
Accuracy Windows: 0.9326
Accuracy Doors: 0.8941
Iou Unknown: nan
Iou Background: 0.9766
Iou Windows: 0.8664
Iou Doors: 0.8330

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: 6e-05
train_batch_size: 2
eval_batch_size: 2
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 13

Training results

Training Loss	Epoch	Step	Validation Loss	Mean Iou	Mean Accuracy	Overall Accuracy	Accuracy Unknown	Accuracy Background	Accuracy Windows	Accuracy Doors	Iou Unknown	Iou Background	Iou Windows	Iou Doors
1.1123	0.0889	20	1.2340	0.3693	0.7755	0.7972	nan	0.8019	0.7161	0.8085	0.0	0.7971	0.3814	0.2986
0.8576	0.1778	40	0.8315	0.4604	0.7890	0.8964	nan	0.9248	0.6823	0.7599	0.0	0.9086	0.5196	0.4135
0.6731	0.2667	60	0.6788	0.4918	0.8207	0.9163	nan	0.9450	0.8512	0.6659	0.0	0.9246	0.5809	0.4618
0.6596	0.3556	80	0.5392	0.6508	0.8229	0.9103	nan	0.9352	0.7984	0.7351	nan	0.9185	0.5802	0.4539
0.6217	0.4444	100	0.4434	0.6832	0.8085	0.9291	nan	0.9635	0.7790	0.6831	nan	0.9383	0.6202	0.4909
0.4555	0.5333	120	0.3915	0.6932	0.8107	0.9327	nan	0.9688	0.8269	0.6364	nan	0.9405	0.6506	0.4885
0.4429	0.6222	140	0.3746	0.6948	0.8375	0.9266	nan	0.9516	0.8020	0.7591	nan	0.9344	0.6549	0.4951
0.3978	0.7111	160	0.3440	0.6987	0.8443	0.9318	nan	0.9585	0.8851	0.6895	nan	0.9398	0.6426	0.5138
0.5	0.8	180	0.3016	0.7152	0.8231	0.9397	nan	0.9738	0.8225	0.6731	nan	0.9468	0.6642	0.5345
0.2722	0.8889	200	0.3163	0.7193	0.8670	0.9353	nan	0.9553	0.8699	0.7760	nan	0.9423	0.6688	0.5467
0.327	0.9778	220	0.2595	0.7225	0.8337	0.9399	nan	0.9701	0.8042	0.7270	nan	0.9464	0.6715	0.5498
0.3964	1.0667	240	0.2516	0.7305	0.8162	0.9458	nan	0.9834	0.8069	0.6582	nan	0.9516	0.6757	0.5643
0.2407	1.1556	260	0.2199	0.7422	0.8589	0.9458	nan	0.9715	0.8708	0.7343	nan	0.9526	0.6906	0.5833
0.3972	1.2444	280	0.2210	0.7424	0.8679	0.9442	nan	0.9667	0.8737	0.7634	nan	0.9511	0.6975	0.5786
0.1568	1.3333	300	0.2047	0.7442	0.8495	0.9465	nan	0.9747	0.8460	0.7277	nan	0.9525	0.6979	0.5822
0.2474	1.4222	320	0.2032	0.7476	0.8592	0.9458	nan	0.9699	0.8170	0.7908	nan	0.9522	0.7013	0.5895
0.183	1.5111	340	0.2112	0.7454	0.8717	0.9423	nan	0.9618	0.8341	0.8193	nan	0.9480	0.7119	0.5762
0.2524	1.6	360	0.1827	0.7435	0.8450	0.9477	nan	0.9779	0.8526	0.7045	nan	0.9546	0.6965	0.5792
0.1665	1.6889	380	0.1746	0.7608	0.8626	0.9514	nan	0.9767	0.8368	0.7743	nan	0.9582	0.7052	0.6191
0.618	1.7778	400	0.1765	0.7565	0.8753	0.9486	nan	0.9696	0.8609	0.7955	nan	0.9556	0.7051	0.6088
0.3693	1.8667	420	0.1629	0.7653	0.8720	0.9505	nan	0.9727	0.8434	0.7999	nan	0.9563	0.7243	0.6152
0.2788	1.9556	440	0.1523	0.7681	0.8712	0.9526	nan	0.9757	0.8483	0.7897	nan	0.9591	0.7216	0.6235
0.09	2.0444	460	0.1746	0.7438	0.8712	0.9422	nan	0.9605	0.7828	0.8704	nan	0.9494	0.6970	0.5850
0.1173	2.1333	480	0.1417	0.7871	0.8677	0.9580	nan	0.9834	0.8333	0.7864	nan	0.9623	0.7330	0.6659
0.1552	2.2222	500	0.1581	0.7588	0.8610	0.9546	nan	0.9835	0.9186	0.6810	nan	0.9639	0.6937	0.6186
0.2021	2.3111	520	0.1400	0.7786	0.8658	0.9581	nan	0.9860	0.9008	0.7105	nan	0.9646	0.7254	0.6459
0.2156	2.4	540	0.1332	0.7945	0.8729	0.9596	nan	0.9849	0.8701	0.7638	nan	0.9638	0.7560	0.6636
0.3223	2.4889	560	0.1371	0.7754	0.8454	0.9579	nan	0.9919	0.8833	0.6609	nan	0.9636	0.7414	0.6213
0.1204	2.5778	580	0.1370	0.8055	0.9040	0.9582	nan	0.9733	0.8797	0.8589	nan	0.9602	0.7812	0.6750
0.1454	2.6667	600	0.1290	0.8106	0.8990	0.9602	nan	0.9775	0.8800	0.8395	nan	0.9621	0.7856	0.6842
0.2149	2.7556	620	0.1375	0.7664	0.8532	0.9559	nan	0.9869	0.8897	0.6830	nan	0.9639	0.7244	0.6110
0.0912	2.8444	640	0.1251	0.7898	0.8694	0.9594	nan	0.9854	0.8598	0.7631	nan	0.9648	0.7437	0.6609
0.0827	2.9333	660	0.1242	0.7959	0.8868	0.9584	nan	0.9789	0.8726	0.8088	nan	0.9625	0.7624	0.6628
0.1986	3.0222	680	0.1324	0.7794	0.8818	0.9568	nan	0.9800	0.9269	0.7387	nan	0.9633	0.7294	0.6456
0.0993	3.1111	700	0.1158	0.8141	0.8824	0.9643	nan	0.9875	0.8582	0.8014	nan	0.9677	0.7681	0.7065
0.1709	3.2	720	0.1128	0.8159	0.9045	0.9629	nan	0.9800	0.9043	0.8293	nan	0.9657	0.7750	0.7070
0.1923	3.2889	740	0.1125	0.8201	0.8913	0.9651	nan	0.9865	0.8874	0.7998	nan	0.9680	0.7802	0.7120
0.0559	3.3778	760	0.1138	0.8247	0.9117	0.9635	nan	0.9780	0.8874	0.8696	nan	0.9652	0.7963	0.7127
0.2231	3.4667	780	0.1084	0.8270	0.9147	0.9642	nan	0.9782	0.9006	0.8654	nan	0.9659	0.7969	0.7184
0.0587	3.5556	800	0.1042	0.8296	0.9132	0.9662	nan	0.9817	0.9159	0.8419	nan	0.9687	0.7893	0.7309
0.0754	3.6444	820	0.1063	0.8324	0.8984	0.9669	nan	0.9858	0.8566	0.8530	nan	0.9689	0.7947	0.7336
0.2001	3.7333	840	0.1188	0.8069	0.9188	0.9595	nan	0.9716	0.9253	0.8594	nan	0.9635	0.7752	0.6820
0.0732	3.8222	860	0.1036	0.8321	0.8903	0.9669	nan	0.9894	0.8944	0.7872	nan	0.9681	0.8110	0.7172
0.1668	3.9111	880	0.1343	0.7993	0.9242	0.9515	nan	0.9588	0.9001	0.9138	nan	0.9518	0.8042	0.6419
0.1307	4.0	900	0.1041	0.8276	0.8938	0.9658	nan	0.9870	0.8990	0.7954	nan	0.9676	0.8055	0.7099
0.0929	4.0889	920	0.1091	0.8127	0.8989	0.9643	nan	0.9843	0.9304	0.7819	nan	0.9690	0.7628	0.7062
0.0936	4.1778	940	0.0985	0.8428	0.9230	0.9680	nan	0.9808	0.9077	0.8804	nan	0.9695	0.8142	0.7448
0.0645	4.2667	960	0.1019	0.8312	0.9123	0.9665	nan	0.9824	0.9162	0.8382	nan	0.9691	0.7985	0.7259
0.1122	4.3556	980	0.1075	0.8140	0.9010	0.9643	nan	0.9836	0.9308	0.7886	nan	0.9687	0.7659	0.7073
0.3607	4.4444	1000	0.1186	0.7965	0.8587	0.9619	nan	0.9932	0.8998	0.6830	nan	0.9658	0.7641	0.6595
0.0704	4.5333	1020	0.0950	0.8454	0.9081	0.9694	nan	0.9873	0.9105	0.8265	nan	0.9700	0.8137	0.7524
0.0472	4.6222	1040	0.1128	0.8245	0.9303	0.9609	nan	0.9697	0.9247	0.8965	nan	0.9610	0.8096	0.7029
0.1245	4.7111	1060	0.0963	0.8363	0.8919	0.9684	nan	0.9911	0.9038	0.7808	nan	0.9700	0.8114	0.7275
0.0474	4.8	1080	0.0948	0.8379	0.9114	0.9686	nan	0.9861	0.9408	0.8074	nan	0.9711	0.8092	0.7335
0.0584	4.8889	1100	0.0835	0.8650	0.9217	0.9734	nan	0.9887	0.9271	0.8494	nan	0.9736	0.8367	0.7847
0.0584	4.9778	1120	0.0965	0.8343	0.9248	0.9669	nan	0.9796	0.9366	0.8583	nan	0.9693	0.7901	0.7436
0.3062	5.0667	1140	0.0948	0.8471	0.8990	0.9698	nan	0.9912	0.9240	0.7819	nan	0.9698	0.8270	0.7445
0.0905	5.1556	1160	0.0866	0.8609	0.9318	0.9719	nan	0.9839	0.9407	0.8709	nan	0.9721	0.8302	0.7804
0.0655	5.2444	1180	0.0855	0.8616	0.9268	0.9730	nan	0.9870	0.9435	0.8500	nan	0.9740	0.8257	0.7852
0.0897	5.3333	1200	0.0820	0.8718	0.9249	0.9741	nan	0.9886	0.9286	0.8576	nan	0.9731	0.8442	0.7981
0.1252	5.4222	1220	0.0859	0.8590	0.9322	0.9714	nan	0.9830	0.9375	0.8759	nan	0.9716	0.8288	0.7767
0.0787	5.5111	1240	0.0942	0.8528	0.9303	0.9687	nan	0.9796	0.9162	0.8952	nan	0.9687	0.8424	0.7472
0.1752	5.6	1260	0.0880	0.8530	0.9197	0.9710	nan	0.9861	0.9240	0.8490	nan	0.9718	0.8143	0.7728
0.12	5.6889	1280	0.0856	0.8568	0.9222	0.9705	nan	0.9837	0.8913	0.8914	nan	0.9700	0.8290	0.7715
0.0789	5.7778	1300	0.0836	0.8612	0.9284	0.9716	nan	0.9837	0.9101	0.8913	nan	0.9713	0.8310	0.7814
0.1557	5.8667	1320	0.0829	0.8664	0.9300	0.9722	nan	0.9841	0.9136	0.8925	nan	0.9708	0.8366	0.7918
0.1868	5.9556	1340	0.0839	0.8640	0.9222	0.9722	nan	0.9870	0.9259	0.8537	nan	0.9711	0.8349	0.7859
0.1028	6.0444	1360	0.0835	0.8647	0.9297	0.9725	nan	0.9851	0.9320	0.8720	nan	0.9719	0.8302	0.7919
0.1021	6.1333	1380	0.0860	0.8572	0.9267	0.9717	nan	0.9847	0.9233	0.8722	nan	0.9724	0.8194	0.7796
0.116	6.2222	1400	0.0883	0.8487	0.9263	0.9704	nan	0.9838	0.9442	0.8508	nan	0.9720	0.8029	0.7712
0.0726	6.3111	1420	0.0856	0.8669	0.9392	0.9718	nan	0.9809	0.9245	0.9122	nan	0.9705	0.8425	0.7878
0.0746	6.4	1440	0.0902	0.8406	0.9123	0.9699	nan	0.9873	0.9347	0.8149	nan	0.9726	0.7909	0.7584
0.0596	6.4889	1460	0.0823	0.8620	0.9262	0.9724	nan	0.9860	0.9285	0.8641	nan	0.9725	0.8303	0.7832
0.127	6.5778	1480	0.0830	0.8667	0.9384	0.9722	nan	0.9821	0.9397	0.8933	nan	0.9711	0.8394	0.7896
0.0511	6.6667	1500	0.0800	0.8746	0.9345	0.9744	nan	0.9862	0.9391	0.8783	nan	0.9733	0.8470	0.8037
0.1304	6.7556	1520	0.0829	0.8658	0.9339	0.9723	nan	0.9834	0.9275	0.8907	nan	0.9717	0.8382	0.7875
0.0768	6.8444	1540	0.0850	0.8595	0.9074	0.9724	nan	0.9915	0.9135	0.8173	nan	0.9722	0.8349	0.7714
0.2556	6.9333	1560	0.0792	0.8681	0.9243	0.9738	nan	0.9883	0.9252	0.8594	nan	0.9737	0.8408	0.7899
0.0446	7.0222	1580	0.0819	0.8497	0.9251	0.9712	nan	0.9853	0.9505	0.8394	nan	0.9732	0.7965	0.7795
0.0593	7.1111	1600	0.0791	0.8774	0.9290	0.9747	nan	0.9881	0.9297	0.8691	nan	0.9726	0.8486	0.8110
0.0997	7.2	1620	0.0786	0.8763	0.9426	0.9743	nan	0.9837	0.9473	0.8969	nan	0.9727	0.8386	0.8176
0.2284	7.2889	1640	0.0815	0.8654	0.9390	0.9724	nan	0.9819	0.9316	0.9034	nan	0.9719	0.8306	0.7937
0.0501	7.3778	1660	0.0833	0.8658	0.9416	0.9726	nan	0.9820	0.9518	0.8912	nan	0.9723	0.8280	0.7972
0.0553	7.4667	1680	0.0754	0.8819	0.9420	0.9755	nan	0.9849	0.9251	0.9160	nan	0.9741	0.8524	0.8191
0.1392	7.5556	1700	0.0739	0.8882	0.9416	0.9772	nan	0.9879	0.9538	0.8831	nan	0.9756	0.8611	0.8278
0.0422	7.6444	1720	0.0753	0.8764	0.9408	0.9749	nan	0.9850	0.9460	0.8915	nan	0.9739	0.8377	0.8176
0.0591	7.7333	1740	0.0766	0.8744	0.9346	0.9744	nan	0.9863	0.9436	0.8741	nan	0.9731	0.8402	0.8100
0.0515	7.8222	1760	0.0766	0.8725	0.9392	0.9738	nan	0.9836	0.9255	0.9084	nan	0.9730	0.8395	0.8051
0.025	7.9111	1780	0.0750	0.8770	0.9358	0.9751	nan	0.9861	0.9211	0.9003	nan	0.9742	0.8442	0.8126
0.2387	8.0	1800	0.0771	0.8714	0.9332	0.9737	nan	0.9850	0.9144	0.9003	nan	0.9731	0.8443	0.7969
0.1592	8.0889	1820	0.0772	0.8734	0.9327	0.9744	nan	0.9859	0.9113	0.9008	nan	0.9741	0.8491	0.7969
0.0835	8.1778	1840	0.0764	0.8705	0.9377	0.9742	nan	0.9850	0.9435	0.8846	nan	0.9745	0.8396	0.7972
0.0639	8.2667	1860	0.0743	0.8828	0.9303	0.9765	nan	0.9898	0.9249	0.8762	nan	0.9758	0.8624	0.8103
0.0841	8.3556	1880	0.0735	0.8812	0.9328	0.9762	nan	0.9883	0.9149	0.8952	nan	0.9754	0.8522	0.8159
0.0946	8.4444	1900	0.0784	0.8643	0.9344	0.9737	nan	0.9856	0.9495	0.8682	nan	0.9749	0.8236	0.7946
0.3774	8.5333	1920	0.0726	0.8799	0.9349	0.9761	nan	0.9875	0.9119	0.9054	nan	0.9757	0.8478	0.8162
0.0636	8.6222	1940	0.0745	0.8739	0.9375	0.9747	nan	0.9856	0.9378	0.8892	nan	0.9744	0.8392	0.8081
0.0278	8.7111	1960	0.0804	0.8627	0.9189	0.9736	nan	0.9898	0.9295	0.8373	nan	0.9744	0.8272	0.7864
0.147	8.8	1980	0.0780	0.8670	0.9356	0.9735	nan	0.9848	0.9443	0.8778	nan	0.9736	0.8280	0.7996
0.0254	8.8889	2000	0.0734	0.8792	0.9338	0.9756	nan	0.9876	0.9245	0.8894	nan	0.9747	0.8488	0.8140
0.0302	8.9778	2020	0.0750	0.8792	0.9436	0.9753	nan	0.9849	0.9549	0.8910	nan	0.9740	0.8433	0.8204
0.0245	9.0667	2040	0.0744	0.8834	0.9357	0.9764	nan	0.9886	0.9488	0.8698	nan	0.9750	0.8559	0.8193
0.1541	9.1556	2060	0.0733	0.8835	0.9418	0.9759	nan	0.9858	0.9406	0.8988	nan	0.9743	0.8581	0.8181
0.0589	9.2444	2080	0.0740	0.8764	0.9425	0.9745	nan	0.9835	0.9304	0.9137	nan	0.9733	0.8434	0.8123
0.0289	9.3333	2100	0.0750	0.8771	0.9321	0.9754	nan	0.9884	0.9408	0.8671	nan	0.9747	0.8456	0.8111
0.1783	9.4222	2120	0.0756	0.8711	0.9326	0.9746	nan	0.9872	0.9455	0.8652	nan	0.9746	0.8368	0.8018
0.0317	9.5111	2140	0.0733	0.8812	0.9345	0.9761	nan	0.9884	0.9375	0.8775	nan	0.9753	0.8561	0.8122
0.0838	9.6	2160	0.0720	0.8839	0.9408	0.9764	nan	0.9867	0.9380	0.8978	nan	0.9754	0.8576	0.8187
0.0384	9.6889	2180	0.0710	0.8858	0.9383	0.9770	nan	0.9879	0.9249	0.9021	nan	0.9763	0.8626	0.8186
0.0713	9.7778	2200	0.0705	0.8875	0.9338	0.9776	nan	0.9901	0.9261	0.8853	nan	0.9768	0.8640	0.8216
0.033	9.8667	2220	0.0695	0.8869	0.9405	0.9772	nan	0.9875	0.9279	0.9061	nan	0.9762	0.8586	0.8260
0.0204	9.9556	2240	0.0705	0.8894	0.9422	0.9775	nan	0.9878	0.9414	0.8972	nan	0.9762	0.8632	0.8288
0.3245	10.0444	2260	0.0690	0.8900	0.9355	0.9780	nan	0.9901	0.9254	0.8910	nan	0.9770	0.8653	0.8275
0.0184	10.1333	2280	0.0679	0.8922	0.9441	0.9781	nan	0.9878	0.9395	0.9049	nan	0.9767	0.8646	0.8353
0.0205	10.2222	2300	0.0710	0.8867	0.9450	0.9768	nan	0.9861	0.9444	0.9044	nan	0.9753	0.8526	0.8322
0.0526	10.3111	2320	0.0726	0.8875	0.9395	0.9770	nan	0.9881	0.9461	0.8841	nan	0.9753	0.8605	0.8266
0.0489	10.4	2340	0.0709	0.8892	0.9355	0.9774	nan	0.9896	0.9321	0.8847	nan	0.9758	0.8616	0.8303
0.0243	10.4889	2360	0.0693	0.8908	0.9393	0.9777	nan	0.9887	0.9326	0.8965	nan	0.9761	0.8640	0.8324
0.0283	10.5778	2380	0.0704	0.8927	0.9382	0.9781	nan	0.9898	0.9399	0.8849	nan	0.9764	0.8723	0.8294
0.0422	10.6667	2400	0.0698	0.8904	0.9416	0.9775	nan	0.9878	0.9351	0.9020	nan	0.9759	0.8636	0.8316
0.0571	10.7556	2420	0.0706	0.8883	0.9488	0.9768	nan	0.9848	0.9423	0.9194	nan	0.9753	0.8606	0.8290
0.0175	10.8444	2440	0.0687	0.8933	0.9401	0.9782	nan	0.9892	0.9322	0.8989	nan	0.9766	0.8678	0.8355
0.0684	10.9333	2460	0.0681	0.8930	0.9464	0.9780	nan	0.9873	0.9478	0.9040	nan	0.9764	0.8660	0.8365
0.0248	11.0222	2480	0.0693	0.8920	0.9473	0.9778	nan	0.9868	0.9527	0.9024	nan	0.9761	0.8638	0.8362
0.0499	11.1111	2500	0.0725	0.8840	0.9326	0.9769	nan	0.9902	0.9451	0.8625	nan	0.9760	0.8568	0.8193
0.072	11.2	2520	0.0706	0.8901	0.9404	0.9775	nan	0.9884	0.9432	0.8895	nan	0.9758	0.8625	0.8318
0.0304	11.2889	2540	0.0696	0.8899	0.9450	0.9773	nan	0.9866	0.9415	0.9069	nan	0.9755	0.8602	0.8340
0.0397	11.3778	2560	0.0695	0.8902	0.9425	0.9774	nan	0.9876	0.9400	0.8999	nan	0.9757	0.8606	0.8343
0.1503	11.4667	2580	0.0709	0.8892	0.9462	0.9771	nan	0.9863	0.9492	0.9031	nan	0.9753	0.8584	0.8339
0.0692	11.5556	2600	0.0708	0.8899	0.9454	0.9772	nan	0.9866	0.9456	0.9040	nan	0.9755	0.8624	0.8319
0.0771	11.6444	2620	0.0710	0.8864	0.9399	0.9771	nan	0.9881	0.9458	0.8857	nan	0.9759	0.8555	0.8277
0.0751	11.7333	2640	0.0692	0.8897	0.9395	0.9776	nan	0.9884	0.9280	0.9020	nan	0.9762	0.8608	0.8320
0.0356	11.8222	2660	0.0716	0.8855	0.9430	0.9767	nan	0.9867	0.9485	0.8939	nan	0.9755	0.8545	0.8266
0.0707	11.9111	2680	0.0705	0.8908	0.9405	0.9777	nan	0.9886	0.9422	0.8909	nan	0.9761	0.8669	0.8293
0.015	12.0	2700	0.0687	0.8915	0.9390	0.9780	nan	0.9891	0.9297	0.8981	nan	0.9766	0.8657	0.8321
0.0334	12.0889	2720	0.0691	0.8862	0.9417	0.9769	nan	0.9868	0.9258	0.9124	nan	0.9759	0.8552	0.8274
0.0161	12.1778	2740	0.0690	0.8897	0.9456	0.9774	nan	0.9866	0.9415	0.9089	nan	0.9759	0.8593	0.8340
0.0728	12.2667	2760	0.0686	0.8917	0.9406	0.9780	nan	0.9888	0.9357	0.8974	nan	0.9765	0.8646	0.8339
0.0517	12.3556	2780	0.0696	0.8918	0.9398	0.9780	nan	0.9892	0.9419	0.8884	nan	0.9764	0.8661	0.8328
0.0445	12.4444	2800	0.0689	0.8916	0.9444	0.9778	nan	0.9874	0.9403	0.9055	nan	0.9762	0.8641	0.8344
0.0376	12.5333	2820	0.0696	0.8907	0.9454	0.9775	nan	0.9869	0.9438	0.9055	nan	0.9759	0.8621	0.8341
0.0233	12.6222	2840	0.0688	0.8911	0.9436	0.9777	nan	0.9875	0.9380	0.9054	nan	0.9762	0.8632	0.8338
0.2039	12.7111	2860	0.0684	0.8919	0.9383	0.9781	nan	0.9895	0.9317	0.8937	nan	0.9766	0.8659	0.8332
0.1103	12.8	2880	0.0679	0.8921	0.9386	0.9781	nan	0.9894	0.9283	0.8980	nan	0.9767	0.8659	0.8336
0.0528	12.8889	2900	0.0686	0.8918	0.9409	0.9780	nan	0.9887	0.9380	0.8959	nan	0.9765	0.8652	0.8337
0.0323	12.9778	2920	0.0683	0.8920	0.9387	0.9781	nan	0.9894	0.9326	0.8941	nan	0.9766	0.8664	0.8330

Framework versions

Transformers 4.47.1
Pytorch 2.5.1+cu124
Datasets 3.2.0
Tokenizers 0.21.0

Task: Image Segmentation
Library: transformers
Type: segformer
License: other
Created: Jan 17, 2025
Updated: Jan 17, 2025