This model is a fine-tuned version of nvidia/mit-b0 on the dskong07/chargers-full-v0.1 dataset. It achieves the following results on the evaluation set:

Loss: 0.3510
Mean Iou: 0.7481
Mean Accuracy: 0.8280
Overall Accuracy: 0.9093
Accuracy Unlabeled: nan
Accuracy Screen: 0.7207
Accuracy Body: 0.8779
Accuracy Cable: 0.6796
Accuracy Plug: 0.9087
Accuracy Void-background: 0.9530
Iou Unlabeled: nan
Iou Screen: 0.6781
Iou Body: 0.7424
Iou Cable: 0.5453
Iou Plug: 0.8738
Iou Void-background: 0.9009

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 OptimizerNames.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: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Mean Iou	Mean Accuracy	Overall Accuracy	Accuracy Unlabeled	Accuracy Screen	Accuracy Body	Accuracy Cable	Accuracy Plug	Accuracy Void-background	Iou Unlabeled	Iou Screen	Iou Body	Iou Cable	Iou Plug	Iou Void-background
1.3959	0.2985	20	1.6451	0.2149	0.4251	0.5844	nan	0.2836	0.8921	0.2978	0.0481	0.6039	0.0	0.1468	0.3945	0.1098	0.0453	0.5929
1.1295	0.5970	40	1.1431	0.3602	0.5469	0.7683	nan	0.2951	0.7976	0.2907	0.4706	0.8806	0.0	0.2479	0.5120	0.1799	0.4300	0.7914
1.0457	0.8955	60	0.9529	0.3982	0.5893	0.7974	nan	0.1740	0.8798	0.2241	0.8104	0.8585	0.0	0.1686	0.5536	0.1788	0.6904	0.7981
1.0391	1.1940	80	0.8307	0.4267	0.6336	0.8131	nan	0.1892	0.8940	0.3723	0.8493	0.8629	0.0	0.1852	0.5927	0.2561	0.7169	0.8093
0.729	1.4925	100	0.7868	0.5246	0.6347	0.8184	nan	0.2819	0.9228	0.2473	0.8642	0.8574	nan	0.2677	0.5923	0.1971	0.7525	0.8135
0.8083	1.7910	120	0.6311	0.5766	0.6715	0.8488	nan	0.5087	0.8173	0.2381	0.8664	0.9271	nan	0.4398	0.6266	0.1934	0.7761	0.8472
0.7409	2.0896	140	0.6098	0.5587	0.6506	0.8391	nan	0.4065	0.8446	0.2365	0.8528	0.9124	nan	0.3657	0.6063	0.1973	0.7861	0.8379
0.6813	2.3881	160	0.6285	0.5473	0.6578	0.8350	nan	0.2686	0.8308	0.5015	0.7660	0.9221	nan	0.2581	0.6172	0.2807	0.7356	0.8448
0.7327	2.6866	180	0.6285	0.5529	0.6812	0.8248	nan	0.7147	0.7609	0.3242	0.6949	0.9111	nan	0.4776	0.5766	0.2051	0.6681	0.8372
0.5943	2.9851	200	0.5870	0.5678	0.6801	0.8369	nan	0.3296	0.9147	0.3810	0.9022	0.8729	nan	0.3214	0.6196	0.2815	0.7850	0.8317
0.7262	3.2836	220	0.5076	0.6021	0.7128	0.8449	nan	0.5441	0.8872	0.3393	0.9169	0.8765	nan	0.5152	0.6357	0.2766	0.7567	0.8264
0.9053	3.5821	240	0.4928	0.6306	0.7432	0.8566	nan	0.6822	0.8404	0.4218	0.8675	0.9039	nan	0.5562	0.6344	0.3053	0.8081	0.8490
0.5192	3.8806	260	0.4863	0.6330	0.7440	0.8604	nan	0.5954	0.8649	0.4892	0.8647	0.9057	nan	0.5407	0.6580	0.3233	0.7909	0.8522
0.9235	4.1791	280	0.4369	0.6290	0.7128	0.8659	nan	0.5969	0.8345	0.3405	0.8554	0.9368	nan	0.5448	0.6557	0.2858	0.8021	0.8566
0.3542	4.4776	300	0.5060	0.6175	0.7684	0.8364	nan	0.7935	0.7959	0.5086	0.8745	0.8693	nan	0.5238	0.5822	0.3420	0.8100	0.8293
0.6167	4.7761	320	0.4596	0.6429	0.7504	0.8615	nan	0.6708	0.8624	0.4183	0.9008	0.8997	nan	0.5739	0.6443	0.3414	0.8055	0.8496
0.6788	5.0746	340	0.4298	0.6535	0.7660	0.8663	nan	0.6556	0.8719	0.4889	0.9147	0.8991	nan	0.5810	0.6662	0.3765	0.7917	0.8522
0.4773	5.3731	360	0.4225	0.6477	0.7492	0.8685	nan	0.5286	0.8797	0.5281	0.8968	0.9127	nan	0.5034	0.6662	0.4019	0.8062	0.8606
0.4333	5.6716	380	0.3937	0.6625	0.7463	0.8804	nan	0.6664	0.8328	0.4130	0.8707	0.9486	nan	0.5867	0.6852	0.3648	0.8032	0.8725
0.2509	5.9701	400	0.4125	0.6635	0.7887	0.8675	nan	0.7264	0.7845	0.6535	0.8514	0.9276	nan	0.5892	0.6445	0.4217	0.8014	0.8609
0.454	6.2687	420	0.4145	0.6603	0.7557	0.8717	nan	0.5785	0.7910	0.5657	0.8997	0.9438	nan	0.5412	0.6551	0.4345	0.8101	0.8606
0.3448	6.5672	440	0.3982	0.6577	0.7560	0.8736	nan	0.4938	0.8411	0.6223	0.8882	0.9348	nan	0.4840	0.6694	0.4508	0.8178	0.8665
0.5959	6.8657	460	0.4177	0.6580	0.7452	0.8687	nan	0.6642	0.7121	0.5706	0.8034	0.9756	nan	0.6031	0.6357	0.4165	0.7790	0.8556
0.5151	7.1642	480	0.4120	0.6209	0.7095	0.8703	nan	0.3412	0.8909	0.5066	0.8742	0.9343	nan	0.3410	0.6686	0.4023	0.8178	0.8748
0.3364	7.4627	500	0.3630	0.6858	0.7925	0.8805	nan	0.7609	0.8687	0.5155	0.9027	0.9148	nan	0.6400	0.6846	0.4191	0.8163	0.8691
0.3042	7.7612	520	0.3496	0.6926	0.7792	0.8878	nan	0.7152	0.8403	0.5164	0.8778	0.9462	nan	0.6416	0.6969	0.4192	0.8278	0.8775
0.2251	8.0597	540	0.3641	0.6856	0.7761	0.8860	nan	0.6173	0.8721	0.5571	0.8998	0.9344	nan	0.5875	0.6991	0.4413	0.8223	0.8779
0.2735	8.3582	560	0.3717	0.6885	0.7795	0.8838	nan	0.6515	0.8773	0.5883	0.8482	0.9321	nan	0.5983	0.6911	0.4570	0.8207	0.8754
0.2617	8.6567	580	0.3784	0.6790	0.7681	0.8790	nan	0.6191	0.8792	0.5428	0.8743	0.9248	nan	0.5843	0.6789	0.4415	0.8216	0.8688
0.2461	8.9552	600	0.3530	0.6935	0.8163	0.8859	nan	0.7448	0.7860	0.6821	0.9264	0.9424	nan	0.6098	0.6840	0.4829	0.8076	0.8830
0.2172	9.2537	620	0.3958	0.6737	0.7720	0.8753	nan	0.5520	0.9130	0.5980	0.8910	0.9062	nan	0.5389	0.6767	0.4576	0.8304	0.8651
0.3699	9.5522	640	0.3647	0.6949	0.8025	0.8820	nan	0.7068	0.8459	0.6498	0.8838	0.9260	nan	0.6152	0.6797	0.4684	0.8391	0.8720
0.601	9.8507	660	0.3733	0.6920	0.7962	0.8755	nan	0.7026	0.8599	0.6140	0.8941	0.9105	nan	0.6289	0.6650	0.4743	0.8328	0.8588
0.3308	10.1493	680	0.3447	0.7052	0.7860	0.8947	nan	0.6886	0.8192	0.6065	0.8478	0.9679	nan	0.6362	0.7125	0.4704	0.8200	0.8868
0.1745	10.4478	700	0.3382	0.6967	0.7898	0.8874	nan	0.6219	0.9052	0.5976	0.9035	0.9209	nan	0.5981	0.7032	0.4761	0.8279	0.8779
0.2469	10.7463	720	0.3389	0.6990	0.7983	0.8877	nan	0.7653	0.8186	0.5818	0.8805	0.9451	nan	0.6164	0.6912	0.4861	0.8217	0.8795
0.233	11.0448	740	0.3643	0.6941	0.7998	0.8828	nan	0.6902	0.8671	0.6112	0.9119	0.9186	nan	0.6004	0.6836	0.4823	0.8306	0.8735
0.7088	11.3433	760	0.3651	0.6968	0.8047	0.8837	nan	0.6909	0.8801	0.6465	0.8891	0.9169	nan	0.6268	0.6920	0.4589	0.8326	0.8735
0.1924	11.6418	780	0.3697	0.6890	0.7770	0.8822	nan	0.6157	0.8859	0.5758	0.8830	0.9246	nan	0.5844	0.6829	0.4663	0.8393	0.8720
0.1873	11.9403	800	0.3436	0.7016	0.7937	0.8888	nan	0.6824	0.8210	0.6051	0.9127	0.9471	nan	0.6265	0.6989	0.4912	0.8151	0.8764
0.1641	12.2388	820	0.3624	0.6960	0.7885	0.8839	nan	0.6579	0.8851	0.6024	0.8731	0.9238	nan	0.6156	0.6878	0.4697	0.8334	0.8732
0.2781	12.5373	840	0.3360	0.7051	0.7923	0.8922	nan	0.6615	0.8851	0.5932	0.8857	0.9361	nan	0.6192	0.7046	0.4742	0.8411	0.8862
0.1532	12.8358	860	0.3566	0.6906	0.7840	0.8848	nan	0.7283	0.8188	0.5124	0.9189	0.9415	nan	0.6266	0.6871	0.4437	0.8235	0.8721
0.3139	13.1343	880	0.3424	0.7093	0.8035	0.8958	nan	0.6391	0.8593	0.6512	0.9235	0.9442	nan	0.6152	0.7207	0.4971	0.8248	0.8888
1.4139	13.4328	900	0.3632	0.7038	0.7838	0.8914	nan	0.6587	0.8352	0.6035	0.8650	0.9565	nan	0.6184	0.6996	0.4858	0.8333	0.8821
0.2153	13.7313	920	0.3262	0.7139	0.8113	0.8966	nan	0.7117	0.8414	0.6435	0.9122	0.9476	nan	0.6232	0.7126	0.5055	0.8363	0.8919
0.1624	14.0299	940	0.3574	0.7066	0.7916	0.8926	nan	0.6483	0.9021	0.5800	0.8969	0.9306	nan	0.6175	0.7114	0.4800	0.8403	0.8835
0.1489	14.3284	960	0.3444	0.7122	0.8085	0.8910	nan	0.6998	0.8007	0.6693	0.9210	0.9514	nan	0.6364	0.6918	0.5209	0.8321	0.8798
0.2614	14.6269	980	0.3488	0.7048	0.8088	0.8870	nan	0.7298	0.8728	0.6108	0.9104	0.9202	nan	0.6170	0.6894	0.4902	0.8491	0.8782
0.1637	14.9254	1000	0.3316	0.7212	0.8060	0.9008	nan	0.6580	0.8217	0.6820	0.9016	0.9666	nan	0.6265	0.7197	0.5192	0.8459	0.8946
0.2536	15.2239	1020	0.3377	0.7159	0.8014	0.8989	nan	0.6778	0.8494	0.6063	0.9206	0.9526	nan	0.6315	0.7246	0.4956	0.8376	0.8903
0.2094	15.5224	1040	0.3390	0.7120	0.7967	0.8968	nan	0.6810	0.8489	0.6513	0.8432	0.9590	nan	0.6316	0.7212	0.5022	0.8149	0.8900
0.1201	15.8209	1060	0.3164	0.7237	0.8065	0.9018	nan	0.6839	0.8706	0.6122	0.9163	0.9495	nan	0.6470	0.7273	0.4930	0.8564	0.8949
0.2082	16.1194	1080	0.3379	0.7188	0.8177	0.8973	nan	0.6962	0.8692	0.6681	0.9173	0.9375	nan	0.6358	0.7159	0.4956	0.8558	0.8912
0.1298	16.4179	1100	0.3332	0.7213	0.8144	0.8993	nan	0.6781	0.8719	0.6567	0.9238	0.9412	nan	0.6329	0.7211	0.5006	0.8592	0.8928
0.201	16.7164	1120	0.3353	0.7131	0.8025	0.8963	nan	0.6558	0.8692	0.6251	0.9206	0.9418	nan	0.6254	0.7248	0.5082	0.8206	0.8865
0.1457	17.0149	1140	0.3407	0.7167	0.8212	0.8956	nan	0.7162	0.8594	0.6688	0.9267	0.9349	nan	0.6500	0.7171	0.4932	0.8355	0.8876
0.2474	17.3134	1160	0.3434	0.7212	0.8108	0.9004	nan	0.7325	0.8143	0.6513	0.8904	0.9654	nan	0.6299	0.7129	0.5175	0.8488	0.8969
0.1211	17.6119	1180	0.3516	0.7106	0.8047	0.8979	nan	0.6133	0.8766	0.6635	0.9278	0.9422	nan	0.5902	0.7261	0.5130	0.8304	0.8935
0.1135	17.9104	1200	0.3331	0.7229	0.8202	0.8985	nan	0.6951	0.8560	0.6899	0.9165	0.9434	nan	0.6389	0.7206	0.5248	0.8391	0.8909
0.107	18.2090	1220	0.3554	0.7110	0.7815	0.8979	nan	0.7022	0.8322	0.5147	0.8931	0.9653	nan	0.6458	0.7190	0.4609	0.8429	0.8864
0.2058	18.5075	1240	0.3337	0.7243	0.8294	0.9009	nan	0.7325	0.8348	0.7262	0.9012	0.9522	nan	0.6495	0.7239	0.4966	0.8542	0.8973
0.2117	18.8060	1260	0.3449	0.7204	0.8095	0.8982	nan	0.6761	0.8609	0.6609	0.9022	0.9470	nan	0.6356	0.7182	0.5088	0.8491	0.8904
0.2975	19.1045	1280	0.3342	0.7252	0.8172	0.9006	nan	0.6768	0.8875	0.6618	0.9223	0.9377	nan	0.6324	0.7279	0.5204	0.8516	0.8934
0.1542	19.4030	1300	0.3245	0.7306	0.8149	0.9046	nan	0.6870	0.8661	0.6576	0.9098	0.9539	nan	0.6429	0.7366	0.5250	0.8506	0.8978
0.1417	19.7015	1320	0.3507	0.7217	0.8184	0.8964	nan	0.6995	0.9091	0.6607	0.8984	0.9243	nan	0.6469	0.7189	0.5051	0.8491	0.8883
0.1359	20.0	1340	0.3346	0.7275	0.8109	0.9023	nan	0.6821	0.8760	0.6451	0.9027	0.9486	nan	0.6376	0.7273	0.5270	0.8496	0.8961
0.1662	20.2985	1360	0.3349	0.7248	0.8150	0.8993	nan	0.7285	0.8694	0.6402	0.8934	0.9434	nan	0.6556	0.7226	0.5154	0.8392	0.8911
0.1662	20.5970	1380	0.3448	0.7257	0.8144	0.9012	nan	0.7193	0.8485	0.6309	0.9225	0.9510	nan	0.6468	0.7229	0.5192	0.8454	0.8940
0.0921	20.8955	1400	0.3306	0.7329	0.8260	0.9030	nan	0.6949	0.8537	0.7215	0.9084	0.9513	nan	0.6514	0.7273	0.5389	0.8505	0.8964
0.1773	21.1940	1420	0.3357	0.7282	0.8246	0.8980	nan	0.7261	0.8576	0.6900	0.9089	0.9403	nan	0.6531	0.7128	0.5345	0.8510	0.8894
0.1477	21.4925	1440	0.3445	0.7259	0.8132	0.9027	nan	0.6474	0.8725	0.6636	0.9351	0.9474	nan	0.6207	0.7333	0.5390	0.8403	0.8962
0.1214	21.7910	1460	0.3235	0.7346	0.8169	0.9059	nan	0.6949	0.8858	0.6324	0.9243	0.9471	nan	0.6539	0.7377	0.5218	0.8606	0.8993
0.1165	22.0896	1480	0.3264	0.7324	0.8171	0.9045	nan	0.7079	0.8623	0.6394	0.9240	0.9519	nan	0.6533	0.7305	0.5213	0.8586	0.8981
0.0872	22.3881	1500	0.3404	0.7298	0.8120	0.9037	nan	0.6788	0.8663	0.6545	0.9067	0.9538	nan	0.6519	0.7344	0.5168	0.8504	0.8957
0.1461	22.6866	1520	0.3371	0.7280	0.8285	0.8968	nan	0.7293	0.8792	0.6968	0.9072	0.9298	nan	0.6656	0.7170	0.5221	0.8495	0.8859
0.1415	22.9851	1540	0.3299	0.7331	0.8112	0.9056	nan	0.7038	0.8586	0.6132	0.9233	0.9572	nan	0.6540	0.7343	0.5172	0.8628	0.8974
0.2888	23.2836	1560	0.3418	0.7332	0.8135	0.9060	nan	0.6904	0.8383	0.6783	0.8928	0.9678	nan	0.6461	0.7331	0.5259	0.8611	0.9000
0.1135	23.5821	1580	0.3408	0.7353	0.8209	0.9037	nan	0.7111	0.8504	0.6877	0.8997	0.9557	nan	0.6603	0.7273	0.5353	0.8582	0.8954
0.1058	23.8806	1600	0.3290	0.7335	0.8156	0.9032	nan	0.7209	0.8625	0.6444	0.8979	0.9524	nan	0.6644	0.7288	0.5274	0.8526	0.8943
0.1641	24.1791	1620	0.3224	0.7344	0.8304	0.9033	nan	0.7509	0.8763	0.6825	0.9006	0.9418	nan	0.6678	0.7319	0.5251	0.8506	0.8968
0.0945	24.4776	1640	0.3357	0.7378	0.8234	0.9064	nan	0.7200	0.8355	0.6849	0.9140	0.9628	nan	0.6638	0.7325	0.5331	0.8598	0.8995
0.1204	24.7761	1660	0.3388	0.7304	0.8223	0.9035	nan	0.6941	0.8709	0.6697	0.9316	0.9451	nan	0.6527	0.7406	0.5304	0.8333	0.8948
0.1033	25.0746	1680	0.3225	0.7398	0.8238	0.9070	nan	0.7335	0.8444	0.6681	0.9122	0.9606	nan	0.6706	0.7364	0.5322	0.8606	0.8991
0.1098	25.3731	1700	0.3348	0.7308	0.8073	0.9075	nan	0.6866	0.8773	0.6025	0.9127	0.9574	nan	0.6442	0.7390	0.5073	0.8596	0.9042
0.0611	25.6716	1720	0.3229	0.7384	0.8304	0.9091	nan	0.6754	0.8591	0.7288	0.9313	0.9572	nan	0.6420	0.7459	0.5377	0.8610	0.9054
0.1827	25.9701	1740	0.3287	0.7343	0.8192	0.9062	nan	0.7268	0.8512	0.6194	0.9435	0.9550	nan	0.6630	0.7412	0.5277	0.8421	0.8977
0.0946	26.2687	1760	0.3205	0.7437	0.8272	0.9090	nan	0.7301	0.8802	0.6653	0.9089	0.9516	nan	0.6745	0.7452	0.5346	0.8624	0.9020
0.1211	26.5672	1780	0.3243	0.7399	0.8259	0.9071	nan	0.7100	0.9083	0.6436	0.9298	0.9376	nan	0.6650	0.7453	0.5268	0.8634	0.8989
0.1551	26.8657	1800	0.3405	0.7297	0.8419	0.8982	nan	0.7089	0.8894	0.7488	0.9410	0.9214	nan	0.6603	0.7287	0.5325	0.8400	0.8873
0.0636	27.1642	1820	0.3370	0.7384	0.8209	0.9047	nan	0.7343	0.8370	0.6681	0.9043	0.9607	nan	0.6732	0.7279	0.5357	0.8604	0.8951
0.0926	27.4627	1840	0.3300	0.7404	0.8267	0.9067	nan	0.7415	0.8610	0.6560	0.9229	0.9520	nan	0.6632	0.7339	0.5404	0.8647	0.8998
0.0895	27.7612	1860	0.3446	0.7396	0.8239	0.9064	nan	0.7084	0.8809	0.6634	0.9194	0.9475	nan	0.6575	0.7355	0.5386	0.8669	0.8996
0.1398	28.0597	1880	0.3368	0.7379	0.8190	0.9053	nan	0.6982	0.8762	0.6673	0.9026	0.9508	nan	0.6616	0.7365	0.5393	0.8560	0.8963
0.1192	28.3582	1900	0.3235	0.7413	0.8317	0.9072	nan	0.7537	0.8615	0.6638	0.9293	0.9501	nan	0.6663	0.7380	0.5384	0.8634	0.9003
0.1265	28.6567	1920	0.3482	0.7326	0.8304	0.9015	nan	0.7228	0.8707	0.6774	0.9444	0.9365	nan	0.6600	0.7271	0.5379	0.8453	0.8929
0.1188	28.9552	1940	0.3482	0.7369	0.8261	0.9054	nan	0.6956	0.8821	0.6902	0.9174	0.9451	nan	0.6569	0.7315	0.5166	0.8792	0.9000
1.3833	29.2537	1960	0.3375	0.7429	0.8171	0.9101	nan	0.7240	0.8518	0.6207	0.9240	0.9648	nan	0.6727	0.7414	0.5243	0.8732	0.9028
0.0947	29.5522	1980	0.3357	0.7371	0.8267	0.9051	nan	0.7277	0.8788	0.6598	0.9234	0.9437	nan	0.6641	0.7316	0.5246	0.8667	0.8987
0.1055	29.8507	2000	0.3282	0.7471	0.8300	0.9114	nan	0.7251	0.8617	0.6815	0.9219	0.9599	nan	0.6687	0.7482	0.5468	0.8660	0.9058
0.1461	30.1493	2020	0.3499	0.7359	0.8170	0.9044	nan	0.7025	0.8768	0.6440	0.9133	0.9483	nan	0.6570	0.7299	0.5310	0.8654	0.8963
0.0773	30.4478	2040	0.3489	0.7349	0.8185	0.9045	nan	0.6925	0.8785	0.6551	0.9196	0.9470	nan	0.6545	0.7317	0.5308	0.8609	0.8969
0.1575	30.7463	2060	0.3418	0.7356	0.8124	0.9067	nan	0.7055	0.8683	0.6273	0.9030	0.9577	nan	0.6594	0.7366	0.5219	0.8603	0.9000
0.0737	31.0448	2080	0.3405	0.7401	0.8200	0.9074	nan	0.7117	0.8691	0.6487	0.9157	0.9548	nan	0.6646	0.7384	0.5336	0.8641	0.8999
0.0909	31.3433	2100	0.3403	0.7439	0.8254	0.9075	nan	0.7338	0.8597	0.6555	0.9232	0.9545	nan	0.6682	0.7331	0.5437	0.8749	0.8994
0.0858	31.6418	2120	0.3338	0.7442	0.8323	0.9086	nan	0.7161	0.8931	0.6737	0.9365	0.9424	nan	0.6764	0.7476	0.5366	0.8597	0.9008
0.1927	31.9403	2140	0.3277	0.7474	0.8232	0.9106	nan	0.7080	0.8699	0.6745	0.9027	0.9607	nan	0.6724	0.7464	0.5426	0.8730	0.9028
0.0937	32.2388	2160	0.3320	0.7437	0.8287	0.9088	nan	0.7044	0.8716	0.6767	0.9397	0.9511	nan	0.6646	0.7464	0.5424	0.8652	0.9000
0.1045	32.5373	2180	0.3538	0.7438	0.8250	0.9097	nan	0.7079	0.8446	0.6955	0.9110	0.9660	nan	0.6621	0.7417	0.5407	0.8717	0.9030
0.0842	32.8358	2200	0.3509	0.7379	0.8207	0.9066	nan	0.7316	0.8959	0.6347	0.8960	0.9455	nan	0.6644	0.7401	0.5243	0.8604	0.9001
0.1174	33.1343	2220	0.3442	0.7398	0.8259	0.9084	nan	0.6756	0.8797	0.7023	0.9204	0.9518	nan	0.6476	0.7467	0.5437	0.8591	0.9022
0.0447	33.4328	2240	0.3403	0.7433	0.8279	0.9077	nan	0.7453	0.8510	0.6639	0.9225	0.9567	nan	0.6692	0.7352	0.5463	0.8656	0.9002
0.0504	33.7313	2260	0.3304	0.7460	0.8259	0.9111	nan	0.7023	0.8935	0.6571	0.9260	0.9506	nan	0.6653	0.7523	0.5397	0.8678	0.9046
0.1154	34.0299	2280	0.3391	0.7419	0.8281	0.9057	nan	0.7408	0.8688	0.6684	0.9139	0.9483	nan	0.6675	0.7318	0.5434	0.8692	0.8973
0.11	34.3284	2300	0.3415	0.7426	0.8238	0.9068	nan	0.7180	0.8761	0.6519	0.9238	0.9490	nan	0.6724	0.7389	0.5397	0.8651	0.8968
0.0706	34.6269	2320	0.3575	0.7377	0.8230	0.9035	nan	0.7369	0.8856	0.6375	0.9148	0.9404	nan	0.6796	0.7345	0.5306	0.8518	0.8922
0.0921	34.9254	2340	0.3547	0.7380	0.8249	0.9040	nan	0.7413	0.8817	0.6474	0.9119	0.9421	nan	0.6812	0.7296	0.5200	0.8642	0.8952
0.1541	35.2239	2360	0.3574	0.7429	0.8232	0.9077	nan	0.7033	0.8654	0.6792	0.9120	0.9561	nan	0.6718	0.7405	0.5404	0.8633	0.8986
0.1086	35.5224	2380	0.3393	0.7453	0.8218	0.9097	nan	0.7267	0.8774	0.6335	0.9165	0.9549	nan	0.6808	0.7466	0.5346	0.8632	0.9012
0.1061	35.8209	2400	0.3444	0.7479	0.8329	0.9097	nan	0.7322	0.8684	0.6916	0.9181	0.9540	nan	0.6756	0.7437	0.5482	0.8698	0.9024
0.1069	36.1194	2420	0.3389	0.7478	0.8320	0.9098	nan	0.7390	0.8627	0.7013	0.8987	0.9582	nan	0.6761	0.7433	0.5473	0.8693	0.9030
0.1199	36.4179	2440	0.3564	0.7413	0.8167	0.9068	nan	0.7123	0.8995	0.6188	0.9077	0.9453	nan	0.6738	0.7377	0.5256	0.8716	0.8978
0.1174	36.7164	2460	0.3414	0.7477	0.8282	0.9101	nan	0.7269	0.8867	0.6545	0.9233	0.9497	nan	0.6784	0.7474	0.5400	0.8706	0.9019
0.1253	37.0149	2480	0.3383	0.7494	0.8295	0.9107	nan	0.7388	0.8669	0.6743	0.9096	0.9580	nan	0.6782	0.7436	0.5443	0.8770	0.9037
0.0733	37.3134	2500	0.3395	0.7527	0.8336	0.9128	nan	0.7344	0.8688	0.6918	0.9137	0.9596	nan	0.6824	0.7492	0.5471	0.8780	0.9070
0.0758	37.6119	2520	0.3378	0.7503	0.8204	0.9138	nan	0.7186	0.8807	0.6250	0.9158	0.9619	nan	0.6791	0.7519	0.5313	0.8815	0.9080
0.1194	37.9104	2540	0.3321	0.7528	0.8315	0.9140	nan	0.7425	0.8737	0.6602	0.9214	0.9596	nan	0.6806	0.7521	0.5406	0.8816	0.9089
0.0844	38.2090	2560	0.3349	0.7540	0.8264	0.9145	nan	0.7297	0.8707	0.6551	0.9121	0.9646	nan	0.6848	0.7543	0.5451	0.8777	0.9080
0.0721	38.5075	2580	0.3404	0.7501	0.8339	0.9087	nan	0.7328	0.8698	0.6966	0.9193	0.9511	nan	0.6783	0.7357	0.5537	0.8823	0.9004
0.235	38.8060	2600	0.3444	0.7489	0.8321	0.9092	nan	0.7293	0.8637	0.6986	0.9137	0.9553	nan	0.6779	0.7388	0.5500	0.8768	0.9011
0.0803	39.1045	2620	0.3437	0.7481	0.8287	0.9099	nan	0.7258	0.8801	0.6723	0.9126	0.9525	nan	0.6740	0.7432	0.5435	0.8775	0.9024
0.0667	39.4030	2640	0.3408	0.7503	0.8308	0.9121	nan	0.7260	0.8695	0.6941	0.9039	0.9603	nan	0.6763	0.7499	0.5472	0.8724	0.9059
0.0795	39.7015	2660	0.3414	0.7492	0.8318	0.9115	nan	0.7452	0.8803	0.6563	0.9247	0.9523	nan	0.6799	0.7482	0.5396	0.8732	0.9053
0.1985	40.0	2680	0.3394	0.7508	0.8309	0.9122	nan	0.7204	0.8830	0.6720	0.9256	0.9538	nan	0.6764	0.7510	0.5424	0.8785	0.9055
0.0644	40.2985	2700	0.3346	0.7505	0.8352	0.9101	nan	0.7297	0.8845	0.6910	0.9228	0.9480	nan	0.6845	0.7463	0.5463	0.8740	0.9015
0.0541	40.5970	2720	0.3359	0.7528	0.8373	0.9103	nan	0.7415	0.8778	0.6908	0.9273	0.9491	nan	0.6874	0.7438	0.5506	0.8806	0.9014
0.0981	40.8955	2740	0.3375	0.7535	0.8328	0.9122	nan	0.7353	0.8818	0.6707	0.9227	0.9534	nan	0.6898	0.7512	0.5458	0.8770	0.9037
0.1954	41.1940	2760	0.3330	0.7541	0.8333	0.9134	nan	0.7324	0.8691	0.6899	0.9148	0.9606	nan	0.6859	0.7543	0.5486	0.8754	0.9060
0.1808	41.4925	2780	0.3324	0.7552	0.8372	0.9135	nan	0.7313	0.8759	0.6950	0.9280	0.9558	nan	0.6835	0.7531	0.5527	0.8800	0.9067
0.0559	41.7910	2800	0.3456	0.7512	0.8315	0.9114	nan	0.7229	0.8870	0.6722	0.9247	0.9509	nan	0.6815	0.7478	0.5427	0.8801	0.9040
0.0614	42.0896	2820	0.3376	0.7499	0.8237	0.9125	nan	0.7148	0.8923	0.6400	0.9166	0.9547	nan	0.6795	0.7510	0.5338	0.8793	0.9058
0.0866	42.3881	2840	0.3316	0.7520	0.8313	0.9121	nan	0.7333	0.8796	0.6733	0.9148	0.9554	nan	0.6852	0.7492	0.5430	0.8776	0.9051
1.58	42.6866	2860	0.3423	0.7528	0.8353	0.9127	nan	0.7338	0.8700	0.6931	0.9224	0.9575	nan	0.6833	0.7507	0.5461	0.8777	0.9061
0.1143	42.9851	2880	0.3422	0.7504	0.8296	0.9115	nan	0.7285	0.8852	0.6658	0.9158	0.9529	nan	0.6819	0.7477	0.5407	0.8770	0.9046
0.0975	43.2836	2900	0.3390	0.7526	0.8372	0.9123	nan	0.7240	0.8756	0.7080	0.9238	0.9545	nan	0.6793	0.7507	0.5508	0.8763	0.9059
0.0557	43.5821	2920	0.3421	0.7506	0.8268	0.9119	nan	0.7315	0.8793	0.6424	0.9252	0.9555	nan	0.6810	0.7482	0.5426	0.8765	0.9046
0.1321	43.8806	2940	0.3446	0.7503	0.8343	0.9104	nan	0.7335	0.8730	0.6867	0.9257	0.9523	nan	0.6786	0.7442	0.5498	0.8757	0.9029
0.0623	44.1791	2960	0.3522	0.7476	0.8346	0.9082	nan	0.7289	0.8750	0.7059	0.9142	0.9490	nan	0.6789	0.7387	0.5466	0.8736	0.9002
0.0353	44.4776	2980	0.3477	0.7476	0.8325	0.9091	nan	0.7370	0.8599	0.6969	0.9122	0.9563	nan	0.6788	0.7389	0.5474	0.8710	0.9020
0.1102	44.7761	3000	0.3583	0.7460	0.8267	0.9082	nan	0.7106	0.8884	0.6691	0.9180	0.9473	nan	0.6737	0.7398	0.5438	0.8731	0.8999
0.1072	45.0746	3020	0.3476	0.7484	0.8269	0.9094	nan	0.7256	0.8773	0.6555	0.9245	0.9518	nan	0.6804	0.7404	0.5462	0.8742	0.9009
0.293	45.3731	3040	0.3593	0.7473	0.8250	0.9096	nan	0.7062	0.8817	0.6651	0.9194	0.9526	nan	0.6711	0.7415	0.5438	0.8780	0.9020
0.0851	45.6716	3060	0.3546	0.7484	0.8329	0.9087	nan	0.7336	0.8714	0.6891	0.9196	0.9508	nan	0.6803	0.7381	0.5473	0.8758	0.9006
0.0671	45.9701	3080	0.3564	0.7466	0.8312	0.9072	nan	0.7371	0.8708	0.6922	0.9055	0.9504	nan	0.6813	0.7352	0.5456	0.8727	0.8983
0.0768	46.2687	3100	0.3489	0.7476	0.8278	0.9088	nan	0.7416	0.8625	0.6732	0.9049	0.9570	nan	0.6826	0.7387	0.5457	0.8709	0.9002
2.2003	46.5672	3120	0.3538	0.7491	0.8325	0.9094	nan	0.7289	0.8667	0.6903	0.9230	0.9536	nan	0.6791	0.7402	0.5495	0.8757	0.9012
0.1072	46.8657	3140	0.3584	0.7462	0.8271	0.9086	nan	0.7007	0.8850	0.6802	0.9204	0.9491	nan	0.6682	0.7403	0.5458	0.8763	0.9005
0.0721	47.1642	3160	0.3543	0.7468	0.8281	0.9082	nan	0.7183	0.8847	0.6657	0.9246	0.9471	nan	0.6759	0.7386	0.5439	0.8755	0.8997
0.0707	47.4627	3180	0.3538	0.7468	0.8273	0.9082	nan	0.7207	0.8861	0.6652	0.9171	0.9475	nan	0.6767	0.7384	0.5415	0.8776	0.8997
0.089	47.7612	3200	0.3608	0.7465	0.8248	0.9086	nan	0.7081	0.8860	0.6669	0.9131	0.9500	nan	0.6722	0.7407	0.5451	0.8746	0.9000
0.1766	48.0597	3220	0.3501	0.7488	0.8267	0.9099	nan	0.7227	0.8656	0.6781	0.9086	0.9586	nan	0.6792	0.7429	0.5484	0.8721	0.9015
0.065	48.3582	3240	0.3436	0.7495	0.8287	0.9099	nan	0.7232	0.8745	0.6801	0.9107	0.9548	nan	0.6802	0.7436	0.5489	0.8733	0.9015
0.0358	48.6567	3260	0.3472	0.7499	0.8336	0.9097	nan	0.7315	0.8706	0.6985	0.9138	0.9535	nan	0.6818	0.7429	0.5488	0.8746	0.9014
0.0478	48.9552	3280	0.3514	0.7489	0.8303	0.9093	nan	0.7233	0.8836	0.6771	0.9180	0.9493	nan	0.6795	0.7425	0.5467	0.8749	0.9008
0.0797	49.2537	3300	0.3615	0.7458	0.8259	0.9087	nan	0.6961	0.8836	0.6886	0.9098	0.9516	nan	0.6659	0.7421	0.5465	0.8740	0.9007
0.1638	49.5522	3320	0.3510	0.7481	0.8270	0.9095	nan	0.7188	0.8786	0.6689	0.9160	0.9527	nan	0.6777	0.7424	0.5459	0.8734	0.9011
0.0584	49.8507	3340	0.3510	0.7481	0.8280	0.9093	nan	0.7207	0.8779	0.6796	0.9087	0.9530	nan	0.6781	0.7424	0.5453	0.8738	0.9009

Framework versions

Transformers 4.48.3
Pytorch 2.6.0+cpu
Datasets 3.2.0
Tokenizers 0.21.0

dskong07/segformer-b0-finetuned-segments-chargers-2-15

segformer-b0-finetuned-segments-chargers-2-15

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

dskong07/
segformer-b0-finetuned-segments-chargers-2-15