README.md

metadata

library_name: transformers
tags:
  - generated_from_trainer
model-index:
  - name: segformer-b1-finetuned-segments-sidewalks-6
    results: []

segformer-b1-finetuned-segments-sidewalks-6

This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0400
• Mean Iou: 0.7845
• Mean Accuracy: 0.8382
• Overall Accuracy: 0.9924
• Accuracy Bkg: 0.9973
• Accuracy Knife: 0.6791
• Accuracy Gun: nan
• Iou Bkg: 0.9924
• Iou Knife: 0.5766
• Iou Gun: nan

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: 6
• eval_batch_size: 6
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Mean Iou	Mean Accuracy	Overall Accuracy	Accuracy Bkg	Accuracy Knife	Accuracy Gun	Iou Bkg	Iou Knife	Iou Gun
0.0094	0.1613	20	0.0278	0.7697	0.8289	0.9917	0.9968	0.6609	nan	0.9917	0.5477	nan
0.0096	0.3226	40	0.0288	0.7684	0.8181	0.9919	0.9974	0.6389	nan	0.9918	0.5450	nan
0.0086	0.4839	60	0.0289	0.7675	0.8143	0.9920	0.9975	0.6311	nan	0.9919	0.5431	nan
0.0081	0.6452	80	0.0288	0.7694	0.8485	0.9912	0.9957	0.7014	nan	0.9911	0.5477	nan
0.0113	0.8065	100	0.0300	0.7690	0.8309	0.9916	0.9967	0.6652	nan	0.9916	0.5464	nan
0.0083	0.9677	120	0.0325	0.7635	0.8051	0.9919	0.9978	0.6123	nan	0.9919	0.5351	nan
0.0087	1.1290	140	0.0303	0.7704	0.8419	0.9915	0.9961	0.6877	nan	0.9914	0.5494	nan
0.0075	1.2903	160	0.0290	0.7645	0.8333	0.9913	0.9962	0.6703	nan	0.9912	0.5378	nan
0.0129	1.4516	180	0.0327	0.7551	0.7845	0.9920	0.9985	0.5705	nan	0.9919	0.5183	nan
0.0087	1.6129	200	0.0285	0.7708	0.8519	0.9912	0.9956	0.7081	nan	0.9911	0.5505	nan
0.0144	1.7742	220	0.0294	0.7675	0.8220	0.9918	0.9971	0.6470	nan	0.9917	0.5433	nan
0.0073	1.9355	240	0.0323	0.7656	0.8140	0.9918	0.9974	0.6306	nan	0.9918	0.5394	nan
0.0071	2.0968	260	0.0297	0.7685	0.8555	0.9910	0.9952	0.7158	nan	0.9909	0.5462	nan
0.0116	2.2581	280	0.0315	0.7680	0.8353	0.9915	0.9963	0.6742	nan	0.9914	0.5447	nan
0.0084	2.4194	300	0.0322	0.7628	0.8066	0.9919	0.9976	0.6156	nan	0.9918	0.5338	nan
0.0107	2.5806	320	0.0293	0.7722	0.8320	0.9918	0.9968	0.6672	nan	0.9917	0.5527	nan
0.0078	2.7419	340	0.0297	0.7681	0.8578	0.9909	0.9951	0.7204	nan	0.9908	0.5455	nan
0.0065	2.9032	360	0.0287	0.7742	0.8419	0.9917	0.9964	0.6874	nan	0.9916	0.5567	nan
0.009	3.0645	380	0.0300	0.7732	0.8319	0.9919	0.9969	0.6669	nan	0.9918	0.5546	nan
0.008	3.2258	400	0.0303	0.7717	0.8383	0.9916	0.9964	0.6802	nan	0.9915	0.5518	nan
0.0084	3.3871	420	0.0313	0.7670	0.8171	0.9919	0.9973	0.6368	nan	0.9918	0.5423	nan
0.0086	3.5484	440	0.0321	0.7673	0.8119	0.9920	0.9976	0.6261	nan	0.9919	0.5426	nan
0.0061	3.7097	460	0.0292	0.7797	0.8412	0.9921	0.9968	0.6856	nan	0.9920	0.5674	nan
0.0075	3.8710	480	0.0308	0.7751	0.8224	0.9922	0.9975	0.6473	nan	0.9922	0.5580	nan
0.0065	4.0323	500	0.0318	0.7706	0.8140	0.9922	0.9977	0.6302	nan	0.9921	0.5490	nan
0.007	4.1935	520	0.0309	0.7716	0.8269	0.9919	0.9971	0.6567	nan	0.9918	0.5514	nan
0.0107	4.3548	540	0.0315	0.7736	0.8288	0.9920	0.9971	0.6604	nan	0.9919	0.5554	nan
0.0094	4.5161	560	0.0300	0.7736	0.8309	0.9919	0.9970	0.6648	nan	0.9919	0.5553	nan
0.0057	4.6774	580	0.0299	0.7779	0.8386	0.9920	0.9968	0.6804	nan	0.9919	0.5639	nan
0.0084	4.8387	600	0.0304	0.7754	0.8404	0.9918	0.9966	0.6843	nan	0.9917	0.5591	nan
0.0068	5.0	620	0.0307	0.7721	0.8556	0.9912	0.9955	0.7158	nan	0.9911	0.5531	nan
0.0078	5.1613	640	0.0312	0.7733	0.8608	0.9912	0.9953	0.7263	nan	0.9911	0.5555	nan
0.0075	5.3226	660	0.0341	0.7666	0.8081	0.9921	0.9978	0.6185	nan	0.9920	0.5413	nan
0.0053	5.4839	680	0.0309	0.7733	0.8235	0.9921	0.9974	0.6497	nan	0.9920	0.5546	nan
0.0064	5.6452	700	0.0311	0.7772	0.8427	0.9919	0.9965	0.6889	nan	0.9918	0.5625	nan
0.0063	5.8065	720	0.0319	0.7745	0.8226	0.9922	0.9975	0.6477	nan	0.9921	0.5569	nan
0.0065	5.9677	740	0.0365	0.7623	0.7948	0.9921	0.9983	0.5913	nan	0.9921	0.5325	nan
0.0071	6.1290	760	0.0312	0.7757	0.8321	0.9920	0.9970	0.6672	nan	0.9920	0.5594	nan
0.0086	6.2903	780	0.0310	0.7777	0.8462	0.9918	0.9964	0.6960	nan	0.9918	0.5637	nan
0.0054	6.4516	800	0.0301	0.7792	0.8504	0.9918	0.9963	0.7046	nan	0.9917	0.5666	nan
0.0077	6.6129	820	0.0325	0.7760	0.8233	0.9923	0.9975	0.6490	nan	0.9922	0.5598	nan
0.0082	6.7742	840	0.0317	0.7746	0.8343	0.9919	0.9968	0.6717	nan	0.9918	0.5573	nan
0.0064	6.9355	860	0.0326	0.7766	0.8333	0.9921	0.9970	0.6696	nan	0.9920	0.5612	nan
0.0045	7.0968	880	0.0331	0.7733	0.8177	0.9922	0.9977	0.6378	nan	0.9922	0.5545	nan
0.0066	7.2581	900	0.0325	0.7751	0.8288	0.9921	0.9972	0.6605	nan	0.9920	0.5582	nan
0.0115	7.4194	920	0.0324	0.7773	0.8378	0.9920	0.9968	0.6788	nan	0.9919	0.5626	nan
0.0049	7.5806	940	0.0332	0.7743	0.8301	0.9920	0.9971	0.6632	nan	0.9919	0.5567	nan
0.0093	7.7419	960	0.0345	0.7708	0.8081	0.9923	0.9981	0.6181	nan	0.9923	0.5494	nan
0.0082	7.9032	980	0.0326	0.7752	0.8386	0.9919	0.9966	0.6805	nan	0.9918	0.5586	nan
0.0064	8.0645	1000	0.0332	0.7741	0.8265	0.9921	0.9972	0.6557	nan	0.9920	0.5561	nan
0.0061	8.2258	1020	0.0330	0.7766	0.8306	0.9921	0.9972	0.6640	nan	0.9921	0.5611	nan
0.0065	8.3871	1040	0.0339	0.7748	0.8245	0.9922	0.9974	0.6516	nan	0.9921	0.5575	nan
0.0068	8.5484	1060	0.0327	0.7769	0.8428	0.9919	0.9965	0.6891	nan	0.9918	0.5619	nan
0.0058	8.7097	1080	0.0332	0.7762	0.8383	0.9919	0.9967	0.6798	nan	0.9918	0.5606	nan
0.0074	8.8710	1100	0.0351	0.7732	0.8195	0.9922	0.9976	0.6414	nan	0.9921	0.5543	nan
0.0066	9.0323	1120	0.0339	0.7786	0.8276	0.9923	0.9975	0.6576	nan	0.9923	0.5650	nan
0.004	9.1935	1140	0.0338	0.7771	0.8349	0.9921	0.9970	0.6728	nan	0.9920	0.5621	nan
0.0118	9.3548	1160	0.0349	0.7745	0.8197	0.9923	0.9977	0.6418	nan	0.9922	0.5568	nan
0.0063	9.5161	1180	0.0332	0.7750	0.8336	0.9920	0.9969	0.6702	nan	0.9919	0.5581	nan
0.0061	9.6774	1200	0.0343	0.7768	0.8245	0.9923	0.9975	0.6515	nan	0.9922	0.5614	nan
0.0067	9.8387	1220	0.0336	0.7820	0.8308	0.9925	0.9975	0.6641	nan	0.9924	0.5716	nan
0.0067	10.0	1240	0.0324	0.7794	0.8422	0.9920	0.9967	0.6877	nan	0.9920	0.5669	nan
0.0057	10.1613	1260	0.0333	0.7803	0.8370	0.9922	0.9971	0.6768	nan	0.9921	0.5684	nan
0.0058	10.3226	1280	0.0325	0.7813	0.8451	0.9921	0.9967	0.6936	nan	0.9920	0.5706	nan
0.006	10.4839	1300	0.0331	0.7786	0.8333	0.9922	0.9972	0.6694	nan	0.9921	0.5650	nan
0.0052	10.6452	1320	0.0361	0.7772	0.8246	0.9923	0.9976	0.6516	nan	0.9922	0.5622	nan
0.005	10.8065	1340	0.0345	0.7787	0.8359	0.9921	0.9970	0.6747	nan	0.9921	0.5654	nan
0.0057	10.9677	1360	0.0340	0.7789	0.8376	0.9921	0.9969	0.6782	nan	0.9920	0.5657	nan
0.0048	11.1290	1380	0.0349	0.7794	0.8263	0.9924	0.9976	0.6549	nan	0.9923	0.5665	nan
0.0059	11.2903	1400	0.0326	0.7764	0.8539	0.9916	0.9959	0.7118	nan	0.9915	0.5614	nan
0.0043	11.4516	1420	0.0334	0.7791	0.8406	0.9921	0.9968	0.6845	nan	0.9920	0.5663	nan
0.0044	11.6129	1440	0.0331	0.7829	0.8391	0.9923	0.9971	0.6811	nan	0.9923	0.5735	nan
0.0062	11.7742	1460	0.0339	0.7813	0.8369	0.9923	0.9971	0.6767	nan	0.9922	0.5705	nan
0.0062	11.9355	1480	0.0334	0.7806	0.8417	0.9921	0.9968	0.6865	nan	0.9920	0.5691	nan
0.0052	12.0968	1500	0.0342	0.7802	0.8354	0.9922	0.9971	0.6736	nan	0.9922	0.5682	nan
0.0049	12.2581	1520	0.0337	0.7818	0.8418	0.9922	0.9969	0.6868	nan	0.9921	0.5715	nan
0.004	12.4194	1540	0.0347	0.7815	0.8382	0.9923	0.9971	0.6793	nan	0.9922	0.5709	nan
0.0054	12.5806	1560	0.0346	0.7790	0.8379	0.9921	0.9969	0.6788	nan	0.9920	0.5659	nan
0.0076	12.7419	1580	0.0332	0.7821	0.8499	0.9920	0.9965	0.7033	nan	0.9920	0.5723	nan
0.0046	12.9032	1600	0.0346	0.7826	0.8398	0.9923	0.9971	0.6825	nan	0.9922	0.5731	nan
0.0069	13.0645	1620	0.0324	0.7842	0.8507	0.9922	0.9966	0.7048	nan	0.9921	0.5762	nan
0.0064	13.2258	1640	0.0342	0.7808	0.8430	0.9921	0.9968	0.6892	nan	0.9920	0.5695	nan
0.0056	13.3871	1660	0.0336	0.7839	0.8444	0.9923	0.9969	0.6918	nan	0.9922	0.5755	nan
0.0048	13.5484	1680	0.0352	0.7817	0.8335	0.9924	0.9973	0.6697	nan	0.9923	0.5711	nan
0.0059	13.7097	1700	0.0345	0.7817	0.8419	0.9922	0.9969	0.6870	nan	0.9921	0.5713	nan
0.0077	13.8710	1720	0.0353	0.7808	0.8370	0.9923	0.9971	0.6768	nan	0.9922	0.5695	nan
0.0043	14.0323	1740	0.0355	0.7790	0.8344	0.9922	0.9971	0.6717	nan	0.9921	0.5659	nan
0.0044	14.1935	1760	0.0362	0.7800	0.8330	0.9923	0.9973	0.6687	nan	0.9922	0.5678	nan
0.0064	14.3548	1780	0.0355	0.7803	0.8452	0.9920	0.9966	0.6938	nan	0.9919	0.5687	nan
0.0043	14.5161	1800	0.0364	0.7800	0.8390	0.9922	0.9969	0.6811	nan	0.9921	0.5680	nan
0.0065	14.6774	1820	0.0368	0.7806	0.8396	0.9922	0.9969	0.6822	nan	0.9921	0.5692	nan
0.0054	14.8387	1840	0.0359	0.7820	0.8424	0.9922	0.9969	0.6879	nan	0.9921	0.5719	nan
0.0058	15.0	1860	0.0388	0.7790	0.8286	0.9923	0.9974	0.6598	nan	0.9923	0.5657	nan
0.005	15.1613	1880	0.0349	0.7816	0.8490	0.9920	0.9965	0.7016	nan	0.9919	0.5712	nan
0.0039	15.3226	1900	0.0355	0.7807	0.8342	0.9923	0.9972	0.6711	nan	0.9922	0.5692	nan
0.0052	15.4839	1920	0.0353	0.7797	0.8386	0.9921	0.9969	0.6803	nan	0.9921	0.5673	nan
0.0065	15.6452	1940	0.0360	0.7820	0.8371	0.9923	0.9972	0.6771	nan	0.9922	0.5717	nan
0.0052	15.8065	1960	0.0359	0.7797	0.8418	0.9921	0.9968	0.6869	nan	0.9920	0.5674	nan
0.006	15.9677	1980	0.0354	0.7811	0.8412	0.9922	0.9969	0.6855	nan	0.9921	0.5700	nan
0.0044	16.1290	2000	0.0375	0.7800	0.8310	0.9923	0.9974	0.6647	nan	0.9923	0.5678	nan
0.0052	16.2903	2020	0.0376	0.7797	0.8318	0.9923	0.9973	0.6662	nan	0.9922	0.5671	nan
0.0038	16.4516	2040	0.0368	0.7808	0.8399	0.9922	0.9969	0.6829	nan	0.9921	0.5695	nan
0.0067	16.6129	2060	0.0373	0.7803	0.8311	0.9924	0.9974	0.6649	nan	0.9923	0.5684	nan
0.0056	16.7742	2080	0.0370	0.7794	0.8291	0.9923	0.9974	0.6608	nan	0.9923	0.5666	nan
0.0064	16.9355	2100	0.0371	0.7809	0.8365	0.9923	0.9971	0.6759	nan	0.9922	0.5695	nan
0.0038	17.0968	2120	0.0367	0.7818	0.8483	0.9921	0.9965	0.7000	nan	0.9920	0.5716	nan
0.0041	17.2581	2140	0.0366	0.7837	0.8423	0.9923	0.9970	0.6876	nan	0.9922	0.5752	nan
0.0039	17.4194	2160	0.0370	0.7819	0.8394	0.9923	0.9970	0.6818	nan	0.9922	0.5716	nan
0.0046	17.5806	2180	0.0366	0.7822	0.8406	0.9923	0.9970	0.6843	nan	0.9922	0.5722	nan
0.0053	17.7419	2200	0.0376	0.7810	0.8327	0.9924	0.9973	0.6681	nan	0.9923	0.5697	nan
0.0046	17.9032	2220	0.0374	0.7836	0.8376	0.9924	0.9972	0.6780	nan	0.9923	0.5748	nan
0.0045	18.0645	2240	0.0385	0.7812	0.8324	0.9924	0.9974	0.6675	nan	0.9923	0.5701	nan
0.0043	18.2258	2260	0.0380	0.7811	0.8298	0.9924	0.9975	0.6621	nan	0.9924	0.5699	nan
0.0057	18.3871	2280	0.0355	0.7845	0.8481	0.9922	0.9967	0.6995	nan	0.9921	0.5768	nan
0.0037	18.5484	2300	0.0377	0.7808	0.8358	0.9923	0.9972	0.6745	nan	0.9922	0.5694	nan
0.0054	18.7097	2320	0.0361	0.7831	0.8470	0.9922	0.9967	0.6973	nan	0.9921	0.5742	nan
0.0076	18.8710	2340	0.0376	0.7831	0.8354	0.9924	0.9973	0.6734	nan	0.9923	0.5738	nan
0.0057	19.0323	2360	0.0370	0.7837	0.8409	0.9923	0.9971	0.6848	nan	0.9923	0.5752	nan
0.0039	19.1935	2380	0.0371	0.7837	0.8424	0.9923	0.9970	0.6878	nan	0.9922	0.5752	nan
0.0053	19.3548	2400	0.0380	0.7819	0.8385	0.9923	0.9971	0.6799	nan	0.9922	0.5717	nan
0.0028	19.5161	2420	0.0373	0.7820	0.8422	0.9922	0.9969	0.6875	nan	0.9921	0.5720	nan
0.0064	19.6774	2440	0.0377	0.7814	0.8324	0.9924	0.9974	0.6674	nan	0.9923	0.5705	nan
0.0048	19.8387	2460	0.0383	0.7816	0.8280	0.9925	0.9976	0.6583	nan	0.9924	0.5707	nan
0.0036	20.0	2480	0.0381	0.7829	0.8347	0.9924	0.9974	0.6721	nan	0.9924	0.5734	nan
0.0039	20.1613	2500	0.0386	0.7816	0.8336	0.9924	0.9973	0.6699	nan	0.9923	0.5710	nan
0.0051	20.3226	2520	0.0380	0.7825	0.8378	0.9923	0.9972	0.6784	nan	0.9923	0.5727	nan
0.0051	20.4839	2540	0.0404	0.7802	0.8272	0.9924	0.9976	0.6569	nan	0.9924	0.5681	nan
0.0056	20.6452	2560	0.0398	0.7803	0.8258	0.9925	0.9977	0.6540	nan	0.9924	0.5682	nan
0.005	20.8065	2580	0.0393	0.7803	0.8266	0.9925	0.9976	0.6555	nan	0.9924	0.5682	nan
0.0044	20.9677	2600	0.0383	0.7806	0.8333	0.9923	0.9973	0.6694	nan	0.9922	0.5690	nan
0.0056	21.1290	2620	0.0394	0.7807	0.8308	0.9924	0.9974	0.6641	nan	0.9923	0.5692	nan
0.0039	21.2903	2640	0.0391	0.7821	0.8340	0.9924	0.9973	0.6707	nan	0.9923	0.5718	nan
0.0042	21.4516	2660	0.0373	0.7824	0.8439	0.9922	0.9968	0.6911	nan	0.9921	0.5727	nan
0.0039	21.6129	2680	0.0384	0.7816	0.8405	0.9922	0.9970	0.6840	nan	0.9921	0.5712	nan
0.0052	21.7742	2700	0.0375	0.7837	0.8396	0.9924	0.9971	0.6820	nan	0.9923	0.5751	nan
0.0066	21.9355	2720	0.0388	0.7812	0.8371	0.9923	0.9971	0.6770	nan	0.9922	0.5703	nan
0.0042	22.0968	2740	0.0385	0.7818	0.8379	0.9923	0.9971	0.6786	nan	0.9922	0.5715	nan
0.0057	22.2581	2760	0.0386	0.7828	0.8402	0.9923	0.9971	0.6833	nan	0.9922	0.5735	nan
0.0048	22.4194	2780	0.0383	0.7823	0.8435	0.9922	0.9968	0.6901	nan	0.9921	0.5724	nan
0.0042	22.5806	2800	0.0395	0.7798	0.8350	0.9922	0.9971	0.6729	nan	0.9922	0.5675	nan
0.0068	22.7419	2820	0.0387	0.7820	0.8360	0.9923	0.9972	0.6748	nan	0.9923	0.5717	nan
0.0067	22.9032	2840	0.0386	0.7837	0.8391	0.9924	0.9972	0.6810	nan	0.9923	0.5750	nan
0.0053	23.0645	2860	0.0386	0.7835	0.8421	0.9923	0.9970	0.6872	nan	0.9922	0.5748	nan
0.0047	23.2258	2880	0.0408	0.7802	0.8263	0.9925	0.9976	0.6550	nan	0.9924	0.5680	nan
0.0053	23.3871	2900	0.0387	0.7826	0.8338	0.9924	0.9974	0.6701	nan	0.9924	0.5729	nan
0.0034	23.5484	2920	0.0380	0.7831	0.8375	0.9924	0.9972	0.6778	nan	0.9923	0.5739	nan
0.0059	23.7097	2940	0.0380	0.7831	0.8406	0.9923	0.9970	0.6842	nan	0.9922	0.5740	nan
0.0041	23.8710	2960	0.0384	0.7829	0.8386	0.9923	0.9971	0.6801	nan	0.9923	0.5736	nan
0.0036	24.0323	2980	0.0387	0.7829	0.8351	0.9924	0.9973	0.6729	nan	0.9923	0.5735	nan
0.004	24.1935	3000	0.0391	0.7814	0.8342	0.9924	0.9973	0.6711	nan	0.9923	0.5706	nan
0.0037	24.3548	3020	0.0405	0.7793	0.8286	0.9923	0.9975	0.6598	nan	0.9923	0.5662	nan
0.0037	24.5161	3040	0.0394	0.7822	0.8410	0.9922	0.9970	0.6850	nan	0.9922	0.5722	nan
0.0043	24.6774	3060	0.0398	0.7820	0.8364	0.9923	0.9972	0.6757	nan	0.9923	0.5718	nan
0.0039	24.8387	3080	0.0394	0.7814	0.8366	0.9923	0.9972	0.6760	nan	0.9922	0.5706	nan
0.0036	25.0	3100	0.0395	0.7818	0.8387	0.9923	0.9971	0.6803	nan	0.9922	0.5713	nan
0.0034	25.1613	3120	0.0401	0.7802	0.8319	0.9923	0.9973	0.6664	nan	0.9923	0.5681	nan
0.0041	25.3226	3140	0.0382	0.7830	0.8439	0.9922	0.9969	0.6910	nan	0.9921	0.5738	nan
0.005	25.4839	3160	0.0395	0.7825	0.8360	0.9924	0.9973	0.6748	nan	0.9923	0.5726	nan
0.0052	25.6452	3180	0.0388	0.7832	0.8371	0.9924	0.9972	0.6770	nan	0.9923	0.5741	nan
0.0043	25.8065	3200	0.0382	0.7837	0.8427	0.9923	0.9970	0.6885	nan	0.9922	0.5752	nan
0.0058	25.9677	3220	0.0381	0.7833	0.8434	0.9923	0.9969	0.6900	nan	0.9922	0.5745	nan
0.0081	26.1290	3240	0.0395	0.7823	0.8343	0.9924	0.9973	0.6712	nan	0.9923	0.5722	nan
0.0047	26.2903	3260	0.0401	0.7822	0.8322	0.9924	0.9975	0.6669	nan	0.9924	0.5721	nan
0.005	26.4516	3280	0.0395	0.7829	0.8346	0.9924	0.9974	0.6718	nan	0.9924	0.5735	nan
0.0035	26.6129	3300	0.0391	0.7840	0.8406	0.9924	0.9971	0.6842	nan	0.9923	0.5757	nan
0.0048	26.7742	3320	0.0393	0.7835	0.8379	0.9924	0.9972	0.6786	nan	0.9923	0.5746	nan
0.0044	26.9355	3340	0.0400	0.7831	0.8354	0.9924	0.9973	0.6734	nan	0.9923	0.5738	nan
0.0031	27.0968	3360	0.0401	0.7834	0.8378	0.9924	0.9972	0.6783	nan	0.9923	0.5745	nan
0.0042	27.2581	3380	0.0403	0.7830	0.8370	0.9924	0.9972	0.6768	nan	0.9923	0.5736	nan
0.0045	27.4194	3400	0.0400	0.7838	0.8361	0.9925	0.9973	0.6749	nan	0.9924	0.5753	nan
0.0039	27.5806	3420	0.0390	0.7844	0.8415	0.9924	0.9971	0.6860	nan	0.9923	0.5765	nan
0.004	27.7419	3440	0.0385	0.7842	0.8387	0.9924	0.9972	0.6801	nan	0.9923	0.5760	nan
0.0042	27.9032	3460	0.0390	0.7841	0.8391	0.9924	0.9972	0.6810	nan	0.9923	0.5759	nan
0.0042	28.0645	3480	0.0403	0.7835	0.8359	0.9924	0.9973	0.6745	nan	0.9924	0.5747	nan
0.0051	28.2258	3500	0.0397	0.7840	0.8402	0.9924	0.9971	0.6834	nan	0.9923	0.5758	nan
0.0037	28.3871	3520	0.0400	0.7838	0.8381	0.9924	0.9972	0.6790	nan	0.9923	0.5752	nan
0.0046	28.5484	3540	0.0395	0.7837	0.8367	0.9924	0.9973	0.6760	nan	0.9924	0.5751	nan
0.0062	28.7097	3560	0.0402	0.7837	0.8382	0.9924	0.9972	0.6793	nan	0.9923	0.5751	nan
0.0049	28.8710	3580	0.0390	0.7841	0.8386	0.9924	0.9972	0.6799	nan	0.9923	0.5759	nan
0.004	29.0323	3600	0.0395	0.7837	0.8353	0.9925	0.9974	0.6733	nan	0.9924	0.5751	nan
0.004	29.1935	3620	0.0394	0.7842	0.8383	0.9924	0.9972	0.6794	nan	0.9924	0.5761	nan
0.0038	29.3548	3640	0.0395	0.7844	0.8377	0.9925	0.9973	0.6782	nan	0.9924	0.5764	nan
0.0046	29.5161	3660	0.0398	0.7841	0.8359	0.9925	0.9974	0.6745	nan	0.9924	0.5757	nan
0.0034	29.6774	3680	0.0398	0.7841	0.8367	0.9925	0.9973	0.6760	nan	0.9924	0.5759	nan
0.0041	29.8387	3700	0.0397	0.7845	0.8381	0.9924	0.9973	0.6790	nan	0.9924	0.5766	nan
0.0039	30.0	3720	0.0400	0.7845	0.8382	0.9924	0.9973	0.6791	nan	0.9924	0.5766	nan

Framework versions

• Transformers 4.44.2
• Pytorch 2.4.1+cu121
• Datasets 3.0.1
• Tokenizers 0.19.1