segformer-b0-finetuned-metallography_DsF

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

Loss: 2.0712
Mean Iou: 0.4460
Mean Accuracy: 0.6289
Overall Accuracy: 0.6854
Accuracy Background: nan
Accuracy Haz: 0.1769
Accuracy Matrix: 0.9906
Accuracy Porosity: 0.0
Accuracy Carbides: 0.9771
Accuracy Substrate: 1.0
Iou Background: 0.0
Iou Haz: 0.1769
Iou Matrix: 0.9845
Iou Porosity: 0.0
Iou Carbides: 0.9304
Iou Substrate: 0.5839

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 200

Training results

Training Loss	Epoch	Step	Validation Loss	Mean Iou	Mean Accuracy	Overall Accuracy	Accuracy Background	Accuracy Haz	Accuracy Matrix	Accuracy Carbides	Accuracy Substrate	Iou Background	Iou Haz	Iou Matrix	Iou Carbides	Iou Substrate
1.5187	1.0	8	1.7410	0.2931	0.5071	0.5435	nan	0.9993	0.9535	0.5823	0.0005	0.0	0.4722	0.8123	0.4737	0.0005
1.2073	2.0	16	1.6492	0.4611	0.6065	0.6450	nan	0.9990	0.9393	0.8738	0.2203	nan	0.5253	0.9196	0.6403	0.2201
1.0802	3.0	24	1.4742	0.4699	0.6448	0.7993	nan	0.5036	0.9851	0.7425	0.9928	0.0	0.4995	0.9430	0.6825	0.6944
1.0695	4.0	32	1.2755	0.5079	0.6803	0.8481	nan	0.6272	0.9821	0.7973	0.9950	0.0	0.6237	0.9482	0.7235	0.7523
0.7541	5.0	40	1.0442	0.4523	0.6354	0.7553	nan	0.3764	0.9795	0.8210	1.0	0.0	0.3764	0.9493	0.7386	0.6494
0.8061	6.0	48	0.8578	0.4381	0.6257	0.7233	nan	0.2902	0.9772	0.8613	1.0	0.0	0.2902	0.9532	0.7658	0.6194
0.5941	7.0	56	0.7094	0.4265	0.6125	0.7000	nan	0.2268	0.9832	0.8527	1.0	0.0	0.2268	0.9577	0.7754	0.5990
0.8048	8.0	64	0.6804	0.4300	0.6070	0.7168	nan	0.2727	0.9932	0.7690	1.0	0.0	0.2727	0.9547	0.7391	0.6136
0.6649	9.0	72	0.9445	0.3885	0.5679	0.6423	nan	0.0758	0.9942	0.7692	1.0	0.0	0.0758	0.9557	0.7442	0.5555
0.5352	10.0	80	1.1298	0.3882	0.5736	0.6265	nan	0.0315	0.9875	0.8489	1.0	0.0	0.0315	0.9613	0.7926	0.5439
0.5562	11.0	88	0.7704	0.4486	0.6331	0.7295	nan	0.3030	0.9827	0.8796	1.0	0.0	0.3030	0.9614	0.8034	0.6237
0.4015	12.0	96	1.1712	0.3857	0.5701	0.6190	nan	0.0108	0.9895	0.8502	1.0	0.0	0.0108	0.9635	0.8012	0.5387
0.5045	13.0	104	0.8262	0.4409	0.6167	0.7240	nan	0.2893	0.9939	0.8004	0.9999	0.0	0.2893	0.9601	0.7767	0.6191
0.7582	14.0	112	0.9599	0.4301	0.6037	0.7132	nan	0.2620	0.9980	0.7583	1.0	0.0	0.2620	0.9576	0.7504	0.6102
0.3979	15.0	120	1.3405	0.3849	0.5649	0.6195	nan	0.0121	0.9952	0.8171	1.0	0.0	0.0121	0.9639	0.7946	0.5390
0.3459	16.0	128	1.1669	0.4122	0.5969	0.6555	nan	0.1052	0.9871	0.8924	1.0	0.0	0.1052	0.9677	0.8369	0.5635
0.3216	17.0	136	1.2025	0.4040	0.5911	0.6383	nan	0.0601	0.9834	0.9120	1.0000	0.0	0.0601	0.9671	0.8457	0.5514
0.3998	18.0	144	1.3530	0.3953	0.5789	0.6182	nan	0.0053	0.9894	0.8999	1.0	0.0	0.0053	0.9711	0.8578	0.5373
0.4093	19.0	152	0.2906	0.5675	0.7263	0.9006	nan	0.7494	0.9929	0.8893	1.0	0.0	0.7494	0.9729	0.8608	0.8218
0.2958	20.0	160	1.6992	0.3971	0.5803	0.6189	nan	0.0067	0.9898	0.9050	1.0	0.0	0.0067	0.9723	0.8659	0.5376
0.2853	21.0	168	1.6151	0.3965	0.5772	0.6183	nan	0.0068	0.9878	0.8914	1.0	0.0	0.0068	0.9682	0.8661	0.5377
0.5007	22.0	176	1.2305	0.4258	0.6067	0.6681	nan	0.1358	0.9913	0.9066	1.0	0.0	0.1358	0.9740	0.8728	0.5720
1.1254	23.0	184	1.1864	0.4372	0.6170	0.6888	nan	0.1902	0.9922	0.9027	1.0	0.0	0.1902	0.9742	0.8710	0.5879
0.3304	24.0	192	0.9748	0.4781	0.6520	0.7609	nan	0.3819	0.9909	0.8872	1.0	0.0	0.3819	0.9706	0.8645	0.6514
0.2638	25.0	200	1.2907	0.4061	0.5861	0.6348	nan	0.0478	0.9944	0.8882	1.0	0.0	0.0478	0.9742	0.8664	0.5482
0.3102	26.0	208	1.6851	0.3982	0.5837	0.6166	nan	0.0	0.9866	0.9317	1.0	0.0	0.0	0.9734	0.8796	0.5360
1.0521	27.0	216	1.8577	0.3974	0.5792	0.6164	nan	0.0	0.9901	0.9059	1.0	0.0	0.0	0.9727	0.8756	0.5360
0.7462	28.0	224	0.8075	0.4878	0.6618	0.7722	nan	0.4089	0.9945	0.9054	1.0	0.0	0.4089	0.9770	0.8792	0.6616
0.2287	29.0	232	2.0142	0.3908	0.5691	0.6159	nan	0.0	0.9958	0.8497	1.0	0.0	0.0	0.9696	0.8394	0.5360
0.2192	30.0	240	2.0412	0.4002	0.5822	0.6176	nan	0.0019	0.9911	0.9179	1.0	0.0	0.0019	0.9756	0.8872	0.5364
0.2033	31.0	248	0.9385	0.4938	0.6777	0.7831	nan	0.4394	0.9798	0.9691	1.0	0.0	0.4394	0.9725	0.8778	0.6733
0.5603	32.0	256	1.8928	0.3973	0.5762	0.6213	nan	0.0123	0.9968	0.8720	1.0	0.0	0.0123	0.9740	0.8586	0.5391
0.3925	33.0	264	2.3578	0.3996	0.5808	0.6171	nan	0.0	0.9939	0.9103	1.0	0.0	0.0	0.9771	0.8846	0.5360
0.7285	34.0	272	2.0361	0.4037	0.5881	0.6201	nan	0.0070	0.9903	0.9433	1.0	0.0	0.0070	0.9789	0.8985	0.5377
0.3214	35.0	280	2.2648	0.3984	0.5779	0.6181	nan	0.0033	0.9956	0.8906	1.0	0.0	0.0033	0.9758	0.8745	0.5368
0.6154	36.0	288	1.7492	0.4144	0.5931	0.6461	nan	0.0776	0.9938	0.8943	1.0	0.0	0.0776	0.9745	0.8780	0.5560
0.1243	37.0	296	0.8522	0.5062	0.6802	0.7952	nan	0.4687	0.9911	0.9413	1.0	0.0	0.4687	0.9793	0.9045	0.6849
0.1868	38.0	304	1.2724	0.4668	0.6431	0.7323	nan	0.3032	0.9938	0.9183	1.0	0.0	0.3032	0.9783	0.8955	0.6238
0.1974	39.0	312	2.2168	0.4026	0.5841	0.6176	nan	0.0	0.9939	0.9265	1.0	0.0	0.0	0.9797	0.8997	0.5360
0.2558	40.0	320	1.6210	0.4063	0.5868	0.6261	nan	0.0240	0.9921	0.9179	1.0	0.0	0.0240	0.9766	0.8955	0.5421
0.1829	41.0	328	0.9688	0.4806	0.6538	0.7586	nan	0.3731	0.9949	0.9012	1.0	0.0	0.3731	0.9767	0.8858	0.6482
0.1703	42.0	336	1.3350	0.4462	0.6250	0.6950	nan	0.2038	0.9949	0.9263	1.0	0.0	0.2038	0.9806	0.9011	0.5919
0.1354	43.0	344	1.4363	0.4375	0.6170	0.6795	nan	0.1632	0.9937	0.9282	1.0	0.0	0.1632	0.9797	0.9024	0.5799
1.8428	44.0	352	1.5515	0.4524	0.6320	0.7042	nan	0.2289	0.9904	0.9408	1.0	0.0	0.2289	0.9785	0.9072	0.5997
0.2148	45.0	360	2.3857	0.4046	0.5877	0.6179	nan	0.0002	0.9925	0.9458	1.0	0.0	0.0002	0.9814	0.9098	0.5360
0.3558	46.0	368	1.6408	0.4296	0.6084	0.6672	nan	0.1308	0.9958	0.9152	1.0	0.0	0.1308	0.9798	0.8966	0.5706
0.1668	47.0	376	1.2740	0.4795	0.6541	0.7521	nan	0.3549	0.9947	0.9207	1.0	0.0	0.3549	0.9795	0.9007	0.6417
0.1406	48.0	384	1.8785	0.4503	0.6303	0.6986	nan	0.2129	0.9923	0.9461	1.0	0.0	0.2129	0.9812	0.9128	0.5947
0.1155	49.0	392	2.5516	0.4057	0.5844	0.6285	nan	0.0296	0.9973	0.8953	1.0	0.0	0.0296	0.9781	0.8831	0.5434
0.1754	50.0	400	1.1770	0.4830	0.6565	0.7591	nan	0.3733	0.9963	0.9128	1.0	0.0	0.3733	0.9799	0.8964	0.6483
0.1437	51.0	408	1.3503	0.4607	0.6404	0.7152	nan	0.2561	0.9926	0.9535	1.0	0.0	0.2561	0.9827	0.9171	0.6083
0.9567	52.0	416	2.4101	0.4082	0.5906	0.6234	nan	0.0144	0.9930	0.9459	1.0	0.0	0.0144	0.9819	0.9133	0.5396
0.1069	53.0	424	2.3543	0.4055	0.5871	0.6199	nan	0.0054	0.9940	0.9360	1.0	0.0	0.0054	0.9813	0.9092	0.5373
0.1372	54.0	432	1.8558	0.4259	0.6079	0.6546	nan	0.0965	0.9929	0.9501	1.0	0.0	0.0965	0.9825	0.9154	0.5611
0.1256	55.0	440	1.6107	0.4701	0.6463	0.7340	nan	0.3063	0.9948	0.9303	1.0	0.0	0.3063	0.9812	0.9082	0.6248
0.1052	56.0	448	2.1773	0.4252	0.6070	0.6531	nan	0.0927	0.9928	0.9493	1.0	0.0	0.0927	0.9823	0.9162	0.5601
0.1056	57.0	456	2.0693	0.4295	0.6107	0.6607	nan	0.1124	0.9935	0.9475	1.0	0.0	0.1124	0.9826	0.9163	0.5655
0.1147	58.0	464	2.5501	0.4120	0.5934	0.6296	nan	0.0310	0.9930	0.9429	1.0	0.0	0.0310	0.9814	0.9158	0.5438
0.6233	59.0	472	2.1451	0.4237	0.6057	0.6494	nan	0.0828	0.9926	0.9529	1.0	0.0	0.0828	0.9827	0.9194	0.5574
0.1155	60.0	480	2.2341	0.4231	0.6045	0.6487	nan	0.0808	0.9934	0.9485	1.0	0.0	0.0808	0.9827	0.9180	0.5569
0.0929	61.0	488	1.9055	0.4321	0.6125	0.6644	nan	0.1221	0.9939	0.9466	1.0	0.0	0.1221	0.9829	0.9193	0.5682
0.1289	62.0	496	1.8765	0.4305	0.6140	0.6613	nan	0.1144	0.9897	0.9659	1.0	0.0	0.1144	0.9818	0.9207	0.5660
0.489	63.0	504	2.2911	0.4089	0.5921	0.6216	nan	0.0090	0.9924	0.9592	1.0	0.0	0.0090	0.9834	0.9229	0.5382
1.9095	64.0	512	2.1933	0.4267	0.6070	0.6552	nan	0.0979	0.9950	0.9420	1.0	0.0	0.0979	0.9832	0.9177	0.5615
0.131	65.0	520	1.8518	0.4368	0.6159	0.6746	nan	0.1492	0.9958	0.9348	1.0	0.0	0.1492	0.9828	0.9130	0.5758
0.093	66.0	528	2.1332	0.4164	0.6038	0.6388	nan	0.0554	0.9872	0.9766	1.0	0.0	0.0554	0.9810	0.9118	0.5501
0.0769	67.0	536	2.3863	0.4085	0.5899	0.6218	nan	0.0099	0.9938	0.9457	1.0	0.0	0.0099	0.9827	0.9199	0.5385
0.0871	68.0	544	2.1332	0.4143	0.5945	0.6338	nan	0.0416	0.9950	0.9359	1.0	0.0	0.0416	0.9823	0.9151	0.5465
0.0793	69.0	552	2.4864	0.4101	0.5905	0.6261	nan	0.0210	0.9962	0.9351	1.0	0.0	0.0210	0.9834	0.9148	0.5412
0.0888	70.0	560	2.2697	0.4268	0.6071	0.6545	nan	0.0957	0.9954	0.9446	1.0	0.0	0.0957	0.9840	0.9201	0.5609
0.08	71.0	568	2.0904	0.4246	0.6105	0.6515	nan	0.0888	0.9877	0.9758	1.0	0.0	0.0888	0.9814	0.9185	0.5590
0.0897	72.0	576	1.6181	0.4453	0.6247	0.6863	nan	0.1796	0.9945	0.9496	1.0	0.0	0.1796	0.984	0.9233	0.5847
0.0944	73.0	584	2.3413	0.4231	0.6029	0.6488	nan	0.0808	0.9958	0.9377	1.0	0.0	0.0808	0.9834	0.9176	0.5568
0.075	74.0	592	2.8188	0.4132	0.5945	0.6295	nan	0.0299	0.9944	0.9484	1.0	0.0	0.0299	0.9836	0.9221	0.5435
0.0662	75.0	600	1.2679	0.4941	0.6715	0.7693	nan	0.3984	0.9914	0.9679	1.0	0.0	0.3984	0.9838	0.9252	0.6575
0.098	76.0	608	1.8848	0.4348	0.6162	0.6667	nan	0.1276	0.9932	0.9600	1.0	0.0	0.1276	0.9844	0.9270	0.5697
0.0674	77.0	616	2.2552	0.4205	0.6012	0.6420	nan	0.0625	0.9952	0.9481	1.0	0.0	0.0625	0.9844	0.9240	0.5520
0.1523	78.0	624	1.8392	0.4369	0.6177	0.6706	nan	0.1378	0.9941	0.9568	1.0	0.0	0.1378	0.9847	0.9261	0.5726
0.0885	79.0	632	1.0762	0.5071	0.6819	0.7902	nan	0.4533	0.9927	0.9638	1.0	0.0	0.4533	0.9844	0.9264	0.6787
0.0874	80.0	640	1.7894	0.4506	0.6338	0.6960	nan	0.2052	0.9899	0.9739	1.0	0.0	0.2052	0.9833	0.9226	0.5924
1.0297	81.0	648	2.4597	0.4278	0.6111	0.6544	nan	0.0952	0.9916	0.9686	1.0	0.0	0.0952	0.9841	0.9267	0.5607
0.2758	82.0	656	1.3680	0.4916	0.6664	0.7650	nan	0.3867	0.9951	0.9500	1.0	0.0	0.3867	0.9846	0.9248	0.6532
1.9304	83.0	664	1.8288	0.4472	0.6246	0.6921	nan	0.1950	0.9966	0.9315	1.0	0.0	0.1950	0.9831	0.9155	0.5893
0.121	84.0	672	2.8537	0.4170	0.5990	0.6341	nan	0.0410	0.9945	0.9593	1.0	0.0	0.0410	0.9855	0.9292	0.5464
0.0475	85.0	680	2.1935	0.4263	0.6068	0.6516	nan	0.0874	0.9955	0.9509	1.0	0.0	0.0874	0.9852	0.9267	0.5586
1.8815	86.0	688	2.4863	0.4234	0.6077	0.6471	nan	0.0762	0.9903	0.9721	1.0	0.0	0.0762	0.9834	0.9251	0.5556
0.0966	87.0	696	2.0991	0.4328	0.6194	0.6667	nan	0.1290	0.9865	0.9814	1.0	0.0	0.1290	0.9811	0.9168	0.5701
0.0843	88.0	704	1.9153	0.4436	0.6248	0.6814	nan	0.1657	0.9937	0.9645	1.0	0.0	0.1657	0.9856	0.9296	0.5806
0.0838	89.0	712	2.3200	0.4325	0.6129	0.6616	nan	0.1138	0.9947	0.9558	1.0	0.0	0.1138	0.9852	0.9299	0.5659
0.0791	90.0	720	2.3284	0.4243	0.6062	0.6467	nan	0.0748	0.9931	0.9631	1.0	0.0	0.0748	0.9848	0.9309	0.5552
0.0404	91.0	728	1.4893	0.4648	0.6427	0.7186	nan	0.2642	0.9951	0.9541	1.0	0.0	0.2642	0.9853	0.9287	0.6109
0.1114	92.0	736	1.9462	0.4330	0.6128	0.6637	nan	0.1194	0.9958	0.9490	1.0	0.0	0.1194	0.9852	0.9262	0.5674
0.0804	93.0	744	2.3175	0.4179	0.6002	0.6358	nan	0.0461	0.9934	0.9613	1.0	0.0	0.0461	0.9848	0.9289	0.5477
0.0798	94.0	752	1.7572	0.4587	0.6406	0.7095	nan	0.2410	0.9897	0.9721	1.0	0.0	0.2410	0.9829	0.9249	0.6035
0.0845	95.0	760	1.7037	0.4664	0.6492	0.7242	nan	0.2803	0.9881	0.9777	1.0	0.0	0.2803	0.9822	0.9201	0.6161
0.0615	96.0	768	2.0290	0.4425	0.6243	0.6800	nan	0.1626	0.9921	0.9666	1.0	0.0	0.1626	0.9843	0.9285	0.5797
0.0526	97.0	776	2.7374	0.4095	0.5909	0.6209	nan	0.0064	0.9952	0.9527	1.0	0.0	0.0064	0.9851	0.9279	0.5376
0.0808	98.0	784	2.0120	0.4346	0.6164	0.6655	nan	0.1241	0.9934	0.9646	1.0	0.0	0.1241	0.9853	0.9293	0.5687
0.0475	99.0	792	1.0516	0.5101	0.6878	0.7967	nan	0.4713	0.9877	0.9799	1.0	0.0	0.4713	0.9821	0.9211	0.6860
0.0678	100.0	800	1.5587	0.4879	0.6652	0.7579	nan	0.3682	0.9918	0.9659	1.0	0.0	0.3682	0.9839	0.9286	0.6464
1.6561	101.0	808	2.5298	0.4332	0.6136	0.6634	nan	0.1186	0.9948	0.9544	1.0	0.0	0.1186	0.9851	0.9284	0.5672
0.0627	102.0	816	2.1491	0.4380	0.6199	0.6716	nan	0.1403	0.9928	0.9666	1.0	0.0	0.1403	0.9850	0.9295	0.5733
0.0873	103.0	824	1.6588	0.4760	0.6550	0.7375	nan	0.3144	0.9918	0.9689	1.0	0.0	0.3144	0.9844	0.9294	0.6275
0.1551	104.0	832	1.5478	0.4884	0.6647	0.7584	nan	0.3693	0.9938	0.9604	1.0	0.0	0.3693	0.9850	0.9296	0.6468
0.0327	105.0	840	1.5536	0.4825	0.6620	0.7493	nan	0.3454	0.9907	0.9741	1.0	0.0	0.3454	0.9841	0.9271	0.6383
0.103	106.0	848	2.1304	0.4519	0.6352	0.6977	nan	0.2100	0.9888	0.9773	1.0	0.0	0.2100	0.9828	0.9248	0.5938
0.0305	107.0	856	2.1873	0.4392	0.6191	0.6741	nan	0.1470	0.9946	0.9538	1.0	0.0	0.1470	0.9847	0.9283	0.5752
0.0647	108.0	864	1.9897	0.4555	0.6371	0.7024	nan	0.2217	0.9913	0.9724	1.0	0.0	0.2217	0.9844	0.9295	0.5974
0.0474	109.0	872	2.0312	0.4396	0.6229	0.6747	nan	0.1487	0.9906	0.9752	1.0	0.0	0.1487	0.9842	0.9288	0.5757
0.0673	110.0	880	2.2469	0.4436	0.6260	0.6812	nan	0.1657	0.9918	0.9723	1.0	0.0	0.1657	0.9849	0.9303	0.5806
0.0491	111.0	888	1.9797	0.4431	0.6247	0.6800	nan	0.1622	0.9929	0.9683	1.0	0.0	0.1622	0.9854	0.9312	0.5796
0.061	112.0	896	1.5743	0.4722	0.6501	0.7304	nan	0.2954	0.9938	0.9615	1.0	0.0	0.2954	0.9852	0.9315	0.6211
0.0435	113.0	904	1.4859	0.4896	0.6693	0.7620	nan	0.3793	0.9891	0.9781	1.0	0.0	0.3793	0.9832	0.9248	0.6505
0.0453	114.0	912	1.5914	0.4932	0.6722	0.7674	nan	0.3936	0.9894	0.9782	1.0	0.0	0.3936	0.9835	0.9261	0.6557
0.0742	115.0	920	1.7837	0.4633	0.6417	0.7150	nan	0.2545	0.9942	0.9598	1.0	0.0	0.2545	0.9853	0.9319	0.6077
0.044	116.0	928	1.8849	0.4733	0.6523	0.7323	nan	0.3001	0.9927	0.9686	1.0	0.0	0.3001	0.9853	0.9319	0.6227
0.0583	117.0	936	2.1859	0.4415	0.6227	0.6768	nan	0.1536	0.9935	0.9666	1.0	0.0	0.1536	0.9857	0.9329	0.5771
0.0465	118.0	944	2.4777	0.4385	0.6191	0.6717	nan	0.1404	0.9941	0.9609	1.0	0.0	0.1404	0.9854	0.9318	0.5733
0.0459	119.0	952	2.2330	0.4397	0.6224	0.6748	nan	0.1487	0.9919	0.9713	1.0	0.0	0.1487	0.9848	0.9293	0.5757
0.0434	120.0	960	2.0761	0.4386	0.6229	0.6738	nan	0.1465	0.9899	0.9779	1.0	0.0	0.1465	0.9840	0.9262	0.5751
0.0538	121.0	968	2.0278	0.4388	0.6235	0.6746	nan	0.1486	0.9894	0.9793	1.0	0.0	0.1486	0.9837	0.9251	0.5757
0.4223	122.0	976	1.9251	0.4635	0.6429	0.7152	nan	0.2551	0.9935	0.9659	1.0	0.0	0.2551	0.9856	0.9324	0.6079
0.039	123.0	984	1.6391	0.4766	0.6566	0.7388	nan	0.3176	0.9911	0.9741	1.0	0.0	0.3176	0.9845	0.9286	0.6286
0.094	124.0	992	2.5742	0.4346	0.6188	0.6663	nan	0.1265	0.9904	0.9768	1.0	0.0	0.1265	0.9843	0.9275	0.5694
0.0481	125.0	1000	2.8845	0.4260	0.6084	0.6490	nan	0.0805	0.9930	0.9684	1.0	0.0	0.0805	0.9855	0.9332	0.5568
0.0519	126.0	1008	2.0920	0.4431	0.6257	0.6807	nan	0.1648	0.9908	0.9728	1.0	0.0	0.1648	0.9840	0.9296	0.5803
0.0408	127.0	1016	2.3639	0.4406	0.6230	0.6762	nan	0.1526	0.9912	0.9714	1.0	0.0	0.1526	0.9842	0.9302	0.5768
0.0786	128.0	1024	2.1270	0.4429	0.6251	0.6802	nan	0.1627	0.9926	0.9700	1.0	0.0	0.1627	0.9854	0.9296	0.5797
0.0475	129.0	1032	1.8585	0.4670	0.6474	0.7219	nan	0.2727	0.9921	0.9721	1.0	0.0	0.2727	0.9852	0.9302	0.6136
0.045	130.0	1040	1.6524	0.4774	0.6570	0.7397	nan	0.3199	0.9914	0.9736	1.0	0.0	0.3199	0.9847	0.9305	0.6294
0.041	131.0	1048	1.8854	0.4679	0.6492	0.7241	nan	0.2791	0.9900	0.9767	1.0	0.0	0.2791	0.9839	0.9287	0.6157
0.1093	132.0	1056	1.8038	0.4619	0.6442	0.7141	nan	0.2529	0.9893	0.9788	1.0	0.0	0.2529	0.9835	0.9276	0.6072
0.0421	133.0	1064	1.9111	0.4539	0.6347	0.6990	nan	0.2125	0.9923	0.9687	1.0	0.0	0.2125	0.9848	0.9314	0.5946
0.0453	134.0	1072	2.1196	0.4592	0.6396	0.7081	nan	0.2365	0.9926	0.9688	1.0	0.0	0.2365	0.9851	0.9315	0.6020
0.0241	135.0	1080	1.6863	0.4899	0.6687	0.7613	nan	0.3769	0.9909	0.9756	1.0	0.0	0.3769	0.9846	0.9282	0.6496
0.0254	136.0	1088	2.1083	0.4475	0.6308	0.6892	nan	0.1869	0.9903	0.9770	1.0	0.0	0.1869	0.9842	0.9273	0.5869
0.1062	137.0	1096	2.5432	0.4383	0.6209	0.6720	nan	0.1417	0.9912	0.9714	1.0	0.0	0.1417	0.9842	0.9304	0.5737
0.0501	138.0	1104	2.1469	0.4421	0.6248	0.6789	nan	0.1599	0.9906	0.9735	1.0	0.0	0.1599	0.9840	0.9298	0.5789
0.0404	139.0	1112	1.9064	0.4490	0.6318	0.6913	nan	0.1925	0.9904	0.9760	1.0	0.0	0.1925	0.9841	0.9291	0.5885
0.0482	140.0	1120	2.0069	0.4477	0.6331	0.6916	nan	0.1938	0.9879	0.9838	1.0	0.0	0.1938	0.9828	0.9206	0.5889
0.0596	141.0	1128	2.0316	0.4448	0.6260	0.6827	nan	0.1693	0.9931	0.9676	1.0	0.0	0.1693	0.9854	0.9326	0.5817
0.0618	142.0	1136	2.3923	0.4404	0.6227	0.6754	nan	0.1503	0.9918	0.9714	1.0	0.0	0.1503	0.9848	0.9312	0.5762
0.3089	143.0	1144	2.0555	0.4513	0.6339	0.6954	nan	0.2034	0.9905	0.9759	1.0	0.0	0.2034	0.9842	0.9286	0.5918
0.0641	144.0	1152	1.7879	0.4678	0.6488	0.7238	nan	0.2781	0.9907	0.9754	1.0	0.0	0.2781	0.9844	0.9292	0.6154
0.0329	145.0	1160	2.1691	0.4499	0.6328	0.6931	nan	0.1973	0.9901	0.9766	1.0	0.0	0.1973	0.9839	0.9280	0.5900
0.0467	146.0	1168	2.3254	0.4396	0.6238	0.6753	nan	0.1505	0.9897	0.9787	1.0	0.0	0.1505	0.9839	0.9269	0.5762
0.0428	147.0	1176	2.8431	0.4324	0.6154	0.6614	nan	0.1133	0.9919	0.9716	1.0	0.0	0.1133	0.9849	0.9305	0.5657
0.0557	148.0	1184	2.6073	0.4357	0.6179	0.6668	nan	0.1276	0.9921	0.9698	1.0	0.0	0.1276	0.9848	0.9318	0.5697
0.0458	149.0	1192	2.4131	0.4392	0.6226	0.6739	nan	0.1468	0.9904	0.9756	1.0	0.0	0.1468	0.9841	0.9292	0.5752
0.0471	150.0	1200	2.3525	0.4415	0.6260	0.6792	nan	0.1611	0.9890	0.9801	1.0	0.0	0.1611	0.9834	0.9250	0.5793
0.0419	151.0	1208	2.5800	0.4411	0.6246	0.6774	nan	0.1557	0.9907	0.9766	1.0	0.0	0.1557	0.9846	0.9288	0.5777
0.1147	152.0	1216	2.3918	0.4417	0.6245	0.6779	nan	0.1568	0.9915	0.9743	1.0	0.0	0.1568	0.9850	0.9306	0.5780
0.0612	153.0	1224	2.2010	0.4476	0.6309	0.6889	nan	0.1861	0.9901	0.9781	1.0	0.0	0.1861	0.9842	0.9288	0.5866
0.0705	154.0	1232	2.1664	0.4489	0.6330	0.6919	nan	0.1943	0.9892	0.9814	1.0	0.0	0.1943	0.9838	0.9262	0.5891
0.0415	155.0	1240	1.9297	0.4605	0.6427	0.7110	nan	0.2445	0.9903	0.9785	1.0	0.0	0.2445	0.9845	0.9293	0.6046
0.0467	156.0	1248	1.6941	0.4717	0.6515	0.7295	nan	0.2927	0.9920	0.9726	1.0	0.0	0.2927	0.9852	0.9318	0.6202
0.0405	157.0	1256	2.1342	0.4446	0.6267	0.6825	nan	0.1689	0.9921	0.9725	1.0	0.0	0.1689	0.9853	0.9318	0.5815
0.0345	158.0	1264	2.4181	0.4394	0.6229	0.6740	nan	0.1467	0.9906	0.9773	1.0	0.0	0.1467	0.9845	0.9299	0.5751
0.0402	159.0	1272	1.9033	0.4564	0.6378	0.7033	nan	0.2238	0.9915	0.9735	1.0	0.0	0.2238	0.9849	0.9320	0.5981
0.0232	160.0	1280	1.8925	0.4583	0.6385	0.7060	nan	0.2310	0.9927	0.9689	1.0	0.0	0.2310	0.9853	0.9331	0.6003
0.4503	161.0	1288	1.8296	0.4598	0.6400	0.7087	nan	0.2379	0.9927	0.9695	1.0	0.0	0.2379	0.9854	0.9331	0.6025
0.0341	162.0	1296	2.1864	0.4480	0.6308	0.6890	nan	0.1862	0.9910	0.9768	1.0	0.0	0.1862	0.9849	0.9305	0.5867
0.0462	163.0	1304	2.5545	0.4419	0.6257	0.6788	nan	0.1595	0.9904	0.9785	1.0	0.0	0.1595	0.9845	0.9287	0.5788
0.05	164.0	1312	2.4571	0.4411	0.6250	0.6774	nan	0.1558	0.9900	0.9794	1.0	0.0	0.1558	0.9843	0.9285	0.5777
0.0889	165.0	1320	2.2148	0.4420	0.6255	0.6788	nan	0.1596	0.9903	0.9777	1.0	0.0	0.1596	0.9843	0.9293	0.5789
0.0352	166.0	1328	2.4693	0.4437	0.6269	0.6817	nan	0.1670	0.9906	0.9771	1.0	0.0	0.1670	0.9845	0.9295	0.5810
1.7247	167.0	1336	2.4316	0.4483	0.6307	0.6894	nan	0.1873	0.9913	0.9746	1.0	0.0	0.1873	0.9848	0.9306	0.5870
0.042	168.0	1344	1.9001	0.4673	0.6468	0.7216	nan	0.2720	0.9929	0.9691	1.0	0.0	0.2720	0.9855	0.9328	0.6134
0.0724	169.0	1352	1.7586	0.4818	0.6605	0.7465	nan	0.3377	0.9923	0.9724	1.0	0.0	0.3377	0.9854	0.9321	0.6356
0.3648	170.0	1360	1.7467	0.4822	0.6602	0.7470	nan	0.3389	0.9928	0.9694	1.0	0.0	0.3389	0.9855	0.9329	0.6360
0.0397	171.0	1368	2.0050	0.4704	0.6497	0.7270	nan	0.2861	0.9927	0.9697	1.0	0.0	0.2861	0.9854	0.9329	0.6180
0.0321	172.0	1376	2.0784	0.4582	0.6393	0.7062	nan	0.2314	0.9919	0.9733	1.0	0.0	0.2314	0.9852	0.9321	0.6004
0.0469	173.0	1384	1.9418	0.4601	0.6417	0.7100	nan	0.2417	0.9909	0.9760	1.0	0.0	0.2417	0.9847	0.9304	0.6037
0.0527	174.0	1392	1.9706	0.4717	0.6522	0.7298	nan	0.2939	0.9909	0.9765	1.0	0.0	0.2939	0.9847	0.9308	0.6206
1.7826	175.0	1400	2.1285	0.4713	0.6525	0.7298	nan	0.2939	0.9902	0.9782	1.0	0.0	0.2939	0.9843	0.9291	0.6206
0.0409	176.0	1408	2.7636	0.4441	0.6278	0.6829	nan	0.1704	0.9897	0.9789	1.0	0.0	0.1704	0.9839	0.9285	0.5820
0.0368	177.0	1416	2.3225	0.4423	0.6253	0.6788	nan	0.1595	0.9907	0.9764	1.0	0.0	0.1595	0.9845	0.9310	0.5788
0.04	178.0	1424	2.9248	0.4386	0.6221	0.6725	nan	0.1427	0.9907	0.9771	1.0	0.0	0.1427	0.9846	0.9306	0.5740
0.0509	179.0	1432	2.6201	0.4391	0.6225	0.6732	nan	0.1448	0.9907	0.9769	1.0	0.0	0.1448	0.9845	0.9305	0.5746
0.0863	180.0	1440	2.3991	0.4406	0.6235	0.6757	nan	0.1510	0.9912	0.9753	1.0	0.0	0.1510	0.9848	0.9315	0.5764
0.0914	181.0	1448	2.5343	0.4414	0.6246	0.6772	nan	0.1550	0.9910	0.9769	1.0	0.0	0.1550	0.9848	0.9309	0.5775
0.3554	182.0	1456	2.3947	0.4419	0.6244	0.6778	nan	0.1565	0.9918	0.9737	1.0	0.0	0.1565	0.9851	0.9318	0.5779
0.1047	183.0	1464	2.1268	0.4442	0.6268	0.6818	nan	0.1673	0.9912	0.9757	1.0	0.0	0.1673	0.9849	0.9317	0.5811
0.0354	184.0	1472	2.1620	0.4460	0.6280	0.6848	nan	0.1751	0.9919	0.9730	1.0	0.0	0.1751	0.9851	0.9326	0.5834
0.3749	185.0	1480	2.0731	0.4481	0.6305	0.6888	nan	0.1857	0.9911	0.9756	1.0	0.0	0.1857	0.9848	0.9319	0.5865
0.0289	186.0	1488	2.0851	0.4451	0.6287	0.6845	nan	0.1747	0.9899	0.9790	1.0	0.0	0.1747	0.9841	0.9287	0.5833
0.0585	187.0	1496	2.1138	0.4431	0.6275	0.6816	nan	0.1671	0.9891	0.9815	1.0	0.0	0.1671	0.9838	0.9265	0.5810
0.0385	188.0	1504	2.0847	0.4450	0.6297	0.6855	nan	0.1777	0.9885	0.9822	1.0	0.0	0.1777	0.9833	0.9247	0.5841
0.0638	189.0	1512	2.0967	0.4482	0.6318	0.6902	nan	0.1897	0.9896	0.9797	1.0	0.0	0.1897	0.9839	0.9279	0.5877
0.0639	190.0	1520	2.5366	0.4435	0.6272	0.6817	nan	0.1671	0.9900	0.9790	1.0	0.0	0.1671	0.9842	0.9284	0.5810
0.0351	191.0	1528	2.3209	0.4448	0.6275	0.6830	nan	0.1702	0.9913	0.9758	1.0	0.0	0.1702	0.9850	0.9317	0.5819
0.0328	192.0	1536	2.5903	0.4436	0.6266	0.6810	nan	0.1650	0.9910	0.9770	1.0	0.0	0.1650	0.9849	0.9312	0.5804
0.0375	193.0	1544	2.3465	0.4439	0.6269	0.6815	nan	0.1665	0.9911	0.9768	1.0	0.0	0.1665	0.9849	0.9310	0.5808
0.0578	194.0	1552	2.1278	0.4465	0.6296	0.6866	nan	0.1800	0.9905	0.9776	1.0	0.0	0.1800	0.9844	0.9297	0.5848
0.0551	195.0	1560	2.3237	0.4444	0.6277	0.6830	nan	0.1704	0.9904	0.9779	1.0	0.0	0.1704	0.9845	0.9297	0.5820
0.0484	196.0	1568	2.2413	0.4442	0.6275	0.6826	nan	0.1694	0.9907	0.9774	1.0	0.0	0.1694	0.9846	0.9298	0.5817
0.0484	197.0	1576	2.2332	0.4438	0.6271	0.6818	nan	0.1673	0.9906	0.9778	1.0	0.0	0.1673	0.9847	0.9297	0.5811
0.4047	198.0	1584	2.1497	0.4458	0.6286	0.6850	nan	0.1756	0.9910	0.9763	1.0	0.0	0.1756	0.9848	0.9307	0.5835
0.0371	199.0	1592	2.1892	0.4457	0.6290	0.6854	nan	0.1769	0.9902	0.9779	1.0	0.0	0.1769	0.9843	0.9292	0.5839
0.0384	200.0	1600	2.0712	0.4460	0.6289	0.6854	nan	0.1769	0.9906	0.9771	1.0	0.0	0.1769	0.9845	0.9304	0.5839

Framework versions

Transformers 4.32.1
Pytorch 2.0.1+cu118
Datasets 2.14.4
Tokenizers 0.13.3

segformer-b0-finetuned-metallography_DsF

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

NSDT 3DConvert

UnrealSynth

DreamTexture.js