efficientvit-ena24-Original

This model is a fine-tuned version of timm/efficientvit_b0.r224_in1k on the Pamreth/ena24 dataset. It achieves the following results on the evaluation set:

• Loss: 0.0992
• Accuracy: 0.9786
• F1: 0.9755
• Acc American black bear: 0.9850
• Acc American crow: 0.9853
• Acc Bird: 0.9667
• Acc Bobcat: 0.9792
• Acc Chicken: 0.9744
• Acc Coyote: 0.98
• Acc Dog: 0.9905
• Acc Domestic cat: 1.0
• Acc Eastern chipmunk: 1.0
• Acc Eastern cottontail: 0.8889
• Acc Eastern fox squirrel: 1.0
• Acc Eastern gray squirrel: 0.9778
• Acc Grey fox: 0.9524
• Acc Horse: 0.875
• Acc Northern raccoon: 0.9535
• Acc Red fox: 0.9344
• Acc Striped skunk: 0.9545
• Acc Vehicle: 1.0
• Acc Virginia opossum: 1.0
• Acc White Tailed Deer: 1.0
• Acc Wild turkey: 1.0
• Acc Woodchuck: 1.0
• F1 American black bear: 0.9813
• F1 American crow: 0.9745
• F1 Bird: 0.9831
• F1 Bobcat: 0.9691
• F1 Chicken: 0.9870
• F1 Coyote: 0.98
• F1 Dog: 0.9952
• F1 Domestic cat: 0.9863
• F1 Eastern chipmunk: 0.9892
• F1 Eastern cottontail: 0.9091
• F1 Eastern fox squirrel: 0.9903
• F1 Eastern gray squirrel: 0.9670
• F1 Grey fox: 0.9677
• F1 Horse: 0.9333
• F1 Northern raccoon: 0.9535
• F1 Red fox: 0.9580
• F1 Striped skunk: 0.9655
• F1 Vehicle: 1.0
• F1 Virginia opossum: 1.0
• F1 White Tailed Deer: 0.9714
• F1 Wild turkey: 1.0
• F1 Woodchuck: 1.0

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: 0.0002
• 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: linear
• num_epochs: 7
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Acc American black bear	Acc American crow	Acc Bird	Acc Bobcat	Acc Chicken	Acc Coyote	Acc Dog	Acc Domestic cat	Acc Eastern chipmunk	Acc Eastern cottontail	Acc Eastern fox squirrel	Acc Eastern gray squirrel	Acc Grey fox	Acc Horse	Acc Northern raccoon	Acc Red fox	Acc Striped skunk	Acc Vehicle	Acc Virginia opossum	Acc White Tailed Deer	Acc Wild turkey	Acc Woodchuck	F1 American black bear	F1 American crow	F1 Bird	F1 Bobcat	F1 Chicken	F1 Coyote	F1 Dog	F1 Domestic cat	F1 Eastern chipmunk	F1 Eastern cottontail	F1 Eastern fox squirrel	F1 Eastern gray squirrel	F1 Grey fox	F1 Horse	F1 Northern raccoon	F1 Red fox	F1 Striped skunk	F1 Vehicle	F1 Virginia opossum	F1 White Tailed Deer	F1 Wild turkey	F1 Woodchuck
1.3767	0.1302	100	1.9571	0.4626	0.3682	0.9774	0.5294	0.0	0.0	0.7564	0.72	0.3619	0.4722	0.8043	0.1556	0.4118	0.7111	0.4603	0.0	0.2093	0.0	0.0	0.0	0.7593	0.1765	0.0	0.3667	0.3626	0.4932	0.0	0.0	0.7195	0.6990	0.5205	0.4444	0.8810	0.2154	0.5526	0.8205	0.6304	0.0	0.2951	0.0	0.0	0.0	0.8586	0.2647	0.0	0.3438
0.9485	0.2604	200	1.3869	0.6191	0.5612	0.9323	0.8603	0.7333	0.25	0.4872	0.98	0.5524	0.5417	0.9348	0.2222	0.8039	0.7556	0.6190	0.125	0.3488	0.2131	0.3182	0.55	0.8148	0.4706	0.4186	0.0333	0.6108	0.8269	0.6769	0.3636	0.6387	0.4395	0.6629	0.4756	0.9663	0.3175	0.6613	0.8608	0.5493	0.2222	0.4839	0.3210	0.3944	0.7097	0.8934	0.6316	0.5806	0.0606
0.5111	0.3906	300	1.2253	0.6992	0.7108	0.6391	0.9118	0.7	0.8333	0.8718	0.8	0.8095	0.7778	0.9348	0.3556	0.9804	0.7778	0.5714	0.625	0.8372	0.2787	0.3409	0.95	0.4167	0.6471	0.5814	0.7333	0.7489	0.8185	0.6885	0.2817	0.8193	0.8602	0.8374	0.7619	0.9663	0.5	0.8696	0.8434	0.7273	0.7692	0.6857	0.4359	0.4688	0.7917	0.5844	0.6875	0.6757	0.8148
0.5202	0.5208	400	1.0903	0.6504	0.6495	0.9850	0.3235	0.7667	0.4167	0.7821	0.82	0.6286	0.5	0.9565	0.6667	0.7451	0.7778	0.6190	0.0	0.3256	0.8033	0.3864	0.7	0.5926	0.6863	0.6977	0.7	0.5078	0.4862	0.6765	0.4255	0.8079	0.8542	0.7630	0.6207	0.9670	0.6316	0.8261	0.7609	0.7647	0.0	0.4746	0.6759	0.5075	0.8	0.7442	0.7692	0.5128	0.7119
0.6265	0.6510	500	0.8185	0.7947	0.7629	0.8496	0.9118	0.2	0.7917	0.9615	1.0	0.7429	0.8056	0.9565	0.6444	0.8431	0.8889	0.5079	0.625	0.7442	0.7377	0.5227	0.8	0.9907	0.5686	0.7209	0.7667	0.8933	0.8921	0.2667	0.5170	0.8108	0.8475	0.8387	0.6784	0.9670	0.6304	0.8515	0.7843	0.6667	0.7692	0.8205	0.8108	0.5412	0.8889	0.9907	0.7160	0.7949	0.8070
0.4103	0.7812	600	1.2751	0.6298	0.5905	0.9474	0.7353	0.8	0.375	0.7436	0.9	0.6	0.5278	0.9348	0.2667	0.4314	0.7111	0.5397	0.0	0.6512	0.1639	0.5682	0.3	0.9630	0.2745	0.1860	0.5	0.4764	0.8	0.7059	0.4390	0.7945	0.8654	0.7456	0.6496	0.9663	0.4211	0.6027	0.8101	0.7010	0.0	0.7368	0.2817	0.2538	0.3529	0.9765	0.4308	0.3137	0.6667
0.355	0.9115	700	0.8689	0.7672	0.7439	0.9699	0.9191	0.8333	0.4792	0.7692	0.92	0.6476	0.6389	0.9783	0.7111	0.9608	0.8444	0.4762	0.75	0.8605	0.1475	0.6591	0.9	0.8981	0.8824	0.5814	0.7667	0.8113	0.8117	0.7463	0.5227	0.8571	0.8679	0.7640	0.6970	0.9783	0.6957	0.9608	0.8736	0.6452	0.8571	0.6435	0.2571	0.6988	0.5373	0.9463	0.6767	0.6494	0.8679
0.3807	1.0417	800	0.8685	0.7527	0.7404	0.6992	1.0	0.8333	0.375	0.6667	0.7	0.9238	0.8333	0.8913	0.6667	0.9608	0.7111	0.7937	0.75	0.6744	0.4918	0.3409	0.85	0.9907	0.6667	0.2093	0.7	0.8017	0.64	0.6667	0.4186	0.8	0.8235	0.9108	0.8451	0.9318	0.5405	0.784	0.6957	0.8	0.8571	0.7733	0.6593	0.5085	0.9189	0.9427	0.8	0.3462	0.8235
0.204	1.1719	900	0.6047	0.8366	0.8159	0.9398	0.8088	0.4667	0.8333	0.9231	0.9	0.8952	0.9306	0.9348	0.7111	1.0	0.8889	0.7302	0.875	0.7674	0.7049	0.7273	0.8	0.9537	0.6471	0.5814	0.8333	0.8562	0.8907	0.6087	0.6061	0.8834	0.9184	0.94	0.8272	0.9556	0.7191	0.7786	0.7843	0.8364	0.8235	0.825	0.7414	0.7711	0.8889	0.9763	0.7765	0.7353	0.8065
0.3145	1.3021	1000	0.5570	0.8489	0.8175	0.9774	0.9779	0.4667	0.7292	0.9231	0.98	0.9524	0.7639	1.0	0.5778	1.0	0.9111	0.8254	0.875	0.5581	0.7213	0.7045	0.85	0.9907	0.8824	0.2558	0.7333	0.8497	0.8808	0.5957	0.7692	0.8780	0.9703	0.9615	0.7971	0.9787	0.65	0.8430	0.9425	0.8189	0.875	0.7059	0.8148	0.6966	0.9189	0.9817	0.8036	0.4074	0.8462
0.2662	1.4323	1100	0.4117	0.8901	0.8754	0.9549	0.9485	0.8667	0.7292	0.7692	0.96	0.9048	0.9167	0.9565	0.7333	1.0	0.9111	0.9048	0.875	0.8605	0.8197	0.7727	0.7	0.9907	0.9216	0.6744	0.9667	0.9170	0.9214	0.7536	0.5983	0.8333	0.9697	0.9453	0.9296	0.9670	0.7416	0.9714	0.9425	0.9344	0.9333	0.9024	0.8333	0.8193	0.8235	0.9907	0.9216	0.7436	0.8657
0.391	1.5625	1200	0.4867	0.8664	0.8440	0.9398	0.8382	0.9667	0.4792	0.6795	0.9	0.9143	0.875	1.0	0.7778	0.9020	0.9333	0.8889	0.875	0.9070	0.7705	0.75	0.9	0.9907	0.9608	0.9070	0.7667	0.8741	0.9084	0.5421	0.6389	0.8092	0.9278	0.9552	0.8936	0.8598	0.6604	0.9485	0.9545	0.8296	0.6667	0.8966	0.8545	0.8049	0.8372	0.9953	0.9423	0.9176	0.8519
0.3194	1.6927	1300	0.2562	0.9237	0.9099	0.9624	0.8676	0.9667	0.7292	0.9359	0.94	0.9810	0.9722	1.0	0.7556	1.0	0.9111	0.9365	0.625	0.9767	0.9016	0.75	0.95	0.9907	0.9216	0.9070	0.9667	0.9275	0.9008	0.9206	0.8140	0.9605	0.94	0.9856	0.9272	0.9892	0.68	1.0	0.9318	0.8939	0.7143	0.9655	0.9167	0.8049	0.9744	0.9953	0.9216	0.9176	0.9355
0.0988	1.8229	1400	0.3040	0.9092	0.8956	0.9850	0.8824	0.9667	0.8542	0.9103	0.94	0.9333	0.9028	1.0	0.8222	0.9608	0.9556	0.9524	0.875	0.8605	0.7869	0.75	0.85	1.0	0.9412	0.6512	0.9333	0.9493	0.8955	0.9355	0.7961	0.9281	0.9592	0.9655	0.9028	0.9787	0.74	0.9608	0.9451	0.8333	0.7778	0.8916	0.8807	0.7952	0.9189	0.9863	0.9412	0.7887	0.9333
0.0861	1.9531	1500	0.2570	0.9298	0.9183	0.9624	0.9926	0.9667	0.8125	0.9103	0.94	0.9524	0.875	1.0	0.6444	1.0	0.9111	0.8571	0.875	0.9302	0.8852	0.9545	1.0	0.9907	0.9412	0.9070	0.9333	0.9734	0.9712	0.8788	0.78	0.9281	0.9216	0.9662	0.8811	0.9892	0.7532	0.9808	0.9425	0.9153	0.9333	0.8421	0.8926	0.8936	0.9302	0.9817	0.9320	0.9512	0.9655
0.1595	2.0833	1600	0.2599	0.9359	0.9282	0.9850	0.9926	0.8333	0.9167	0.7949	0.96	0.9905	0.9444	1.0	0.6444	1.0	0.9778	0.9206	0.875	0.9767	0.8361	0.8864	0.95	0.9630	0.9804	0.9302	0.9667	0.9424	0.9677	0.8929	0.9167	0.8671	0.9505	0.9455	0.9067	0.9892	0.7436	0.9714	0.9778	0.9431	0.875	0.8842	0.9107	0.9176	0.95	0.9811	0.9524	0.9524	0.9831
0.102	2.2135	1700	0.2977	0.9214	0.9054	0.9850	0.9044	0.9667	0.7917	0.8846	0.94	0.9810	0.9167	1.0	0.7333	1.0	0.9778	0.8571	0.875	0.9535	0.8197	0.8864	0.95	0.9907	0.9020	0.8140	0.9667	0.9097	0.9425	0.8923	0.8736	0.9324	0.9495	0.9904	0.9103	0.9787	0.7416	0.8793	0.9263	0.9153	0.6667	0.9318	0.8696	0.8764	0.9744	0.9907	0.92	0.8974	0.9508
0.3103	2.3438	1800	0.2418	0.9313	0.9239	0.9699	0.9338	0.9	0.8542	0.9615	0.96	0.9714	0.8056	1.0	0.9111	0.9804	0.9333	0.9206	0.875	0.9302	0.9672	0.8864	1.0	0.9537	0.7451	0.9535	0.9667	0.9556	0.9585	0.9153	0.8817	0.9146	0.9796	0.9623	0.8855	0.9892	0.7387	0.9524	0.9655	0.9431	0.875	0.9302	0.9219	0.8764	0.9524	0.9763	0.8352	0.9647	0.9508
0.0823	2.4740	1900	0.2137	0.9458	0.9382	0.9699	0.9485	0.9667	0.875	0.9359	0.96	0.9905	0.9583	1.0	0.8222	0.9412	0.9556	0.9048	0.875	0.8837	0.9180	0.9318	0.95	0.9907	0.9804	0.8837	0.9667	0.9382	0.9520	0.9355	0.8317	0.9669	0.9796	0.9952	0.9324	0.9892	0.7957	0.9697	0.9663	0.9268	0.875	0.9383	0.9412	0.9111	0.9744	0.9953	0.9524	0.9383	0.9355
0.0975	2.6042	2000	0.1996	0.9450	0.9378	0.9624	0.8824	0.6667	0.8542	0.9615	0.96	0.9905	0.9722	1.0	0.9111	1.0	0.9333	0.9683	0.875	0.9767	0.9508	0.8864	1.0	0.9815	0.9608	0.9767	0.9333	0.9734	0.9231	0.7843	0.9011	0.9317	0.9796	0.9858	0.9589	0.9892	0.7736	0.9623	0.9655	0.9313	0.9333	0.9767	0.9431	0.9070	0.9756	0.9907	0.9245	0.9882	0.9333
0.1853	2.7344	2100	0.2121	0.9489	0.9399	0.9474	0.9485	0.8333	0.875	0.9231	0.96	0.9905	1.0	1.0	0.8222	1.0	0.9778	0.9524	0.75	0.9535	0.8525	0.9318	0.95	0.9907	1.0	0.9767	0.9333	0.9692	0.9314	0.8929	0.8317	0.9412	0.96	0.9952	0.9474	0.9892	0.8315	0.9808	0.9888	0.9449	0.8571	0.9425	0.9204	0.9011	0.95	0.9953	0.9533	0.9882	0.9655
0.0936	2.8646	2200	0.1857	0.9527	0.9481	0.9774	0.9265	0.9667	0.7292	0.9744	0.98	0.9619	0.9861	1.0	0.9333	0.9020	0.9556	0.9365	0.875	0.9070	0.9508	0.9545	1.0	0.9907	1.0	0.9535	1.0	0.9524	0.9509	0.9667	0.8140	0.9806	0.98	0.9806	0.9726	0.9892	0.8571	0.9388	0.9773	0.9672	0.9333	0.9286	0.928	0.8485	1.0	0.9953	0.9808	0.9647	0.9524
0.2936	2.9948	2300	0.1717	0.9588	0.9569	0.8947	0.9926	0.9333	1.0	0.9615	0.96	0.9714	0.9861	1.0	0.8	1.0	0.9778	0.9524	0.875	0.9535	0.8852	0.9091	1.0	1.0	1.0	1.0	0.9667	0.9407	0.9541	0.9655	0.9412	0.9677	0.9796	0.9855	0.9726	0.9892	0.8675	1.0	0.9670	0.9023	0.9333	0.9318	0.9391	0.9302	1.0	1.0	0.9623	0.9556	0.9667
0.0065	3.125	2400	0.1338	0.9733	0.9711	0.9699	0.9779	0.9667	1.0	0.9615	0.96	0.9905	1.0	1.0	0.8667	1.0	0.9778	0.9365	0.875	0.9767	0.9344	0.9091	1.0	1.0	1.0	1.0	1.0	0.9736	0.9708	0.9831	0.9505	0.9804	0.9796	0.9905	0.9796	0.9892	0.8864	1.0	0.9888	0.9291	0.9333	0.9655	0.9580	0.9524	1.0	1.0	0.9533	1.0	1.0
0.0467	3.2552	2500	0.1448	0.9672	0.9640	0.9699	0.9338	0.9667	0.9167	0.9487	0.96	0.9905	0.9583	1.0	0.9556	1.0	0.9556	0.9365	0.875	0.9767	0.9508	0.9773	1.0	1.0	0.9804	1.0	1.0	0.9810	0.9585	0.9667	0.9263	0.9737	0.9796	0.9952	0.9650	0.9892	0.86	0.9714	0.9773	0.9593	0.9333	0.9655	0.9431	0.9348	1.0	1.0	0.9434	1.0	0.9836
0.0757	3.3854	2600	0.1638	0.9626	0.9592	0.9624	1.0	0.9667	0.9375	0.9615	0.96	0.9905	0.9583	1.0	0.8	1.0	0.9556	0.9841	0.875	0.8837	0.8852	0.9091	1.0	1.0	0.9804	0.9767	1.0	0.9697	0.9577	0.9831	0.9184	0.9740	0.9796	0.9905	0.9583	0.9892	0.8571	0.9903	0.9663	0.9118	0.9333	0.9383	0.9310	0.9524	1.0	1.0	0.9615	0.9882	0.9524
0.0302	3.5156	2700	0.1556	0.9702	0.9657	0.9925	0.9926	0.9667	1.0	0.9744	0.98	0.9905	0.9861	1.0	0.8	1.0	0.9778	0.9841	0.875	0.9535	0.8852	0.8636	1.0	1.0	0.9412	0.9767	1.0	0.9851	0.9677	0.9667	0.9231	0.9806	0.9899	0.9952	0.9595	0.9892	0.8675	1.0	0.9462	0.9612	0.9333	0.9762	0.9391	0.9268	1.0	1.0	0.9505	0.9882	1.0
0.2921	3.6458	2800	0.1312	0.9656	0.9635	0.9624	0.9412	0.9667	0.9583	0.9744	0.96	0.9905	0.9861	1.0	0.9111	1.0	0.9778	0.9524	0.875	0.9302	0.9016	0.8864	1.0	1.0	1.0	1.0	1.0	0.9734	0.9481	0.9831	0.8846	0.9870	0.9796	0.9952	0.9660	0.9892	0.8454	1.0	0.9888	0.9677	0.9333	0.9412	0.9244	0.9286	1.0	1.0	0.9623	1.0	1.0
0.0554	3.7760	2900	0.1303	0.9740	0.9701	0.9850	0.9853	0.9667	0.9375	0.9615	0.98	0.9905	1.0	1.0	0.8222	1.0	0.9778	0.9683	0.875	0.9302	0.9344	0.9545	1.0	1.0	1.0	1.0	1.0	0.9887	0.9675	0.9831	0.9375	0.9804	0.98	0.9952	0.9730	0.9892	0.8706	0.9714	0.9888	0.9606	0.9333	0.9639	0.9580	0.9545	1.0	1.0	0.9623	1.0	0.9836
0.0171	3.9062	3000	0.1468	0.9733	0.9703	0.9850	1.0	0.9667	0.9792	0.9615	0.96	0.9905	1.0	1.0	0.8	1.0	0.9778	0.9524	0.875	0.9302	0.8852	1.0	1.0	1.0	0.9804	1.0	1.0	0.9813	0.9749	0.9831	0.9895	0.9804	0.9796	0.9858	0.9730	0.9892	0.8780	0.9808	0.9778	0.9449	0.9333	0.9412	0.9231	0.9778	1.0	1.0	0.9524	1.0	1.0
0.0813	4.0365	3100	0.1277	0.9748	0.9721	0.9850	0.9632	0.9667	0.9583	0.9744	0.98	0.9810	1.0	1.0	0.9111	1.0	0.9778	0.9524	0.875	0.9302	0.9344	0.9773	1.0	1.0	0.9804	1.0	1.0	0.9813	0.9740	0.9831	0.9684	0.9806	0.98	0.9856	0.9730	0.9892	0.8913	0.9714	0.9778	0.9677	0.9333	0.9524	0.95	0.9663	1.0	1.0	0.9615	1.0	1.0
0.0048	4.1667	3200	0.1341	0.9733	0.9710	0.9850	0.9265	0.9667	0.9792	0.9744	0.98	0.9810	1.0	1.0	0.9333	1.0	0.9778	0.9524	0.875	0.9302	0.9344	1.0	1.0	1.0	0.9804	1.0	1.0	0.9813	0.9582	0.9831	0.9895	0.9806	0.9899	0.9856	0.9730	0.9892	0.8571	1.0	0.9778	0.9677	0.9333	0.9302	0.95	0.9778	0.9756	1.0	0.9615	1.0	1.0
0.0939	4.2969	3300	0.1393	0.9733	0.9705	0.9850	0.9338	0.9667	0.9792	0.9615	0.98	0.9810	1.0	1.0	0.9333	1.0	0.9778	0.9524	0.875	0.9535	0.9344	0.9545	1.0	1.0	1.0	1.0	1.0	0.9813	0.9585	0.9831	0.9592	0.9740	0.9899	0.9904	0.9796	0.9892	0.8660	1.0	0.9778	0.9756	0.9333	0.9425	0.9580	0.9545	0.9756	1.0	0.9623	1.0	1.0
0.0281	4.4271	3400	0.1279	0.9748	0.9712	0.9925	0.9853	0.9667	0.9583	0.9615	0.98	0.9905	1.0	1.0	0.8222	1.0	0.9778	0.9683	0.875	0.9302	0.9672	0.9545	1.0	0.9907	0.9608	1.0	1.0	0.9814	0.9710	0.9831	0.9485	0.9804	0.98	0.9952	0.9796	0.9892	0.8706	1.0	0.9888	0.976	0.9333	0.9639	0.9365	0.9655	0.9756	0.9953	0.9515	1.0	1.0
0.0157	4.5573	3500	0.1141	0.9748	0.9715	0.9850	0.9853	0.9667	0.9583	0.9744	0.96	0.9905	1.0	1.0	0.8222	1.0	0.9778	0.9683	0.875	0.9302	0.9508	0.9773	1.0	1.0	0.9608	1.0	1.0	0.9850	0.9675	0.9831	0.9583	0.9870	0.9697	0.9952	0.9796	0.9892	0.8706	0.9623	0.9888	0.9606	0.9333	0.9639	0.9508	0.9773	1.0	1.0	0.9515	1.0	1.0
0.0007	4.6875	3600	0.1217	0.9794	0.9761	0.9925	0.9926	0.9667	0.9792	1.0	0.98	0.9905	0.9861	1.0	0.8444	1.0	0.9778	0.9365	0.875	0.9535	0.9672	0.9773	1.0	1.0	0.9608	1.0	1.0	0.9814	0.9747	0.9831	0.9691	0.9873	0.98	0.9952	0.9861	0.9892	0.8837	0.9903	0.9778	0.9672	0.9333	0.9535	0.9752	0.9773	1.0	1.0	0.9703	1.0	1.0
0.0003	4.8177	3700	0.1051	0.9756	0.9723	0.9850	0.9632	0.9667	0.9583	0.9615	0.98	0.9905	1.0	1.0	0.9333	1.0	0.9778	0.9524	0.875	0.9535	0.9344	0.9318	1.0	1.0	1.0	1.0	1.0	0.9813	0.9704	0.9831	0.9583	0.9804	0.98	0.9952	0.9863	0.9892	0.9032	0.9903	0.9670	0.9756	0.9333	0.9425	0.95	0.9425	1.0	1.0	0.9623	1.0	1.0
0.0675	4.9479	3800	0.0992	0.9786	0.9755	0.9850	0.9853	0.9667	0.9792	0.9744	0.98	0.9905	1.0	1.0	0.8889	1.0	0.9778	0.9524	0.875	0.9535	0.9344	0.9545	1.0	1.0	1.0	1.0	1.0	0.9813	0.9745	0.9831	0.9691	0.9870	0.98	0.9952	0.9863	0.9892	0.9091	0.9903	0.9670	0.9677	0.9333	0.9535	0.9580	0.9655	1.0	1.0	0.9714	1.0	1.0
0.0207	5.0781	3900	0.1001	0.9794	0.9762	0.9925	0.9706	0.9667	0.9792	0.9744	0.98	1.0	0.9722	1.0	0.9556	1.0	0.9778	0.9524	0.875	0.9535	0.9344	0.9545	1.0	1.0	1.0	1.0	1.0	0.9888	0.9778	0.9831	0.9592	0.9870	0.98	0.9906	0.9790	0.9892	0.9247	0.9903	0.9778	0.9677	0.9333	0.9535	0.9661	0.9655	1.0	1.0	0.9623	1.0	1.0
0.0024	5.2083	4000	0.1021	0.9763	0.9745	0.9850	0.9338	0.9667	1.0	0.9872	0.98	1.0	0.9583	1.0	1.0	1.0	0.9778	0.9524	0.875	0.9535	0.9344	0.9545	1.0	1.0	0.9804	1.0	1.0	0.9813	0.9621	0.9831	0.9796	0.9935	0.9899	0.9906	0.9718	0.9892	0.8911	0.9903	0.9778	0.9677	0.9333	0.9535	0.9580	0.9655	1.0	1.0	0.9615	1.0	1.0
0.0001	5.3385	4100	0.1299	0.9740	0.9723	0.9774	0.9338	0.9667	1.0	0.9615	0.98	1.0	0.9722	1.0	0.9778	1.0	0.9778	0.9524	0.875	0.9535	0.9016	0.9773	1.0	1.0	1.0	1.0	1.0	0.9811	0.9621	0.9831	0.9796	0.9804	0.9899	0.9906	0.9722	0.9892	0.8889	0.9903	0.9670	0.9524	0.9333	0.9425	0.9483	0.9773	1.0	1.0	0.9623	1.0	1.0
0.071	5.4688	4200	0.1155	0.9786	0.9759	0.9850	0.9926	0.9667	0.9792	0.9744	0.96	0.9905	1.0	1.0	0.8667	1.0	0.9778	0.9841	0.875	0.9535	0.9180	0.9545	1.0	1.0	1.0	1.0	1.0	0.9813	0.9712	0.9831	0.9691	0.9870	0.9697	0.9952	0.9863	0.9892	0.9070	0.9903	0.9670	0.9688	0.9333	0.9762	0.9573	0.9655	1.0	1.0	0.9714	1.0	1.0
0.0005	5.5990	4300	0.1067	0.9763	0.9736	0.9850	0.9485	0.9667	0.9583	0.9744	0.96	0.9905	1.0	1.0	0.9778	1.0	0.9778	0.9683	0.875	0.9535	0.9180	0.9545	1.0	1.0	1.0	1.0	1.0	0.9850	0.9663	0.9831	0.9485	0.9870	0.9697	0.9952	0.9863	0.9892	0.9072	0.9808	0.9670	0.9606	0.9333	0.9647	0.9573	0.9655	1.0	1.0	0.9714	1.0	1.0
0.0656	5.7292	4400	0.1128	0.9802	0.9774	0.9850	0.9853	0.9667	0.9792	0.9744	0.96	0.9905	1.0	1.0	0.8889	1.0	0.9778	0.9841	0.875	0.9535	0.9344	0.9773	1.0	1.0	1.0	1.0	1.0	0.9850	0.9745	0.9831	0.9691	0.9870	0.9697	0.9952	0.9863	0.9892	0.9091	0.9903	0.9778	0.9612	0.9333	0.9762	0.9661	0.9773	1.0	1.0	0.9714	1.0	1.0
0.0503	5.8594	4500	0.1144	0.9779	0.9751	0.9850	0.9926	0.9667	0.9792	0.9744	0.96	1.0	0.9722	1.0	0.8444	1.0	0.9778	0.9841	0.875	0.9535	0.9180	0.9773	1.0	1.0	1.0	1.0	1.0	0.9850	0.9712	0.9831	0.9592	0.9870	0.9697	0.9906	0.9722	0.9892	0.8941	0.9903	0.9778	0.9764	0.9333	0.9762	0.9573	0.9773	1.0	1.0	0.9623	1.0	1.0
0.0072	5.9896	4600	0.1050	0.9763	0.9736	0.9850	0.9853	0.9667	0.9792	0.9872	0.96	1.0	0.9722	1.0	0.8667	1.0	0.9778	0.9683	0.875	0.9535	0.9180	0.9773	1.0	1.0	0.9608	1.0	1.0	0.9850	0.9710	0.9831	0.9691	0.9809	0.9697	0.9906	0.9722	0.9892	0.8966	0.9903	0.9670	0.9606	0.9333	0.9647	0.9573	0.9773	1.0	1.0	0.9608	1.0	1.0
0.0001	6.1198	4700	0.1132	0.9786	0.9763	0.9850	0.9485	0.9667	0.9792	0.9744	0.96	0.9905	1.0	1.0	0.9778	1.0	0.9778	0.9841	0.875	0.9535	0.9344	0.9545	1.0	1.0	1.0	1.0	1.0	0.9813	0.9663	0.9831	0.9592	0.9870	0.9697	0.9952	0.9863	0.9892	0.9072	0.9903	0.9670	0.9841	0.9333	0.9762	0.9661	0.9655	1.0	1.0	0.9714	1.0	1.0
0.0001	6.25	4800	0.1129	0.9779	0.9752	0.9850	0.9632	0.9667	0.9792	0.9744	0.96	0.9905	1.0	1.0	0.9111	1.0	0.9778	0.9841	0.875	0.9535	0.9344	0.9545	1.0	1.0	1.0	1.0	1.0	0.9850	0.9632	0.9831	0.94	0.9870	0.9697	0.9952	0.9863	0.9892	0.8913	1.0	0.9670	0.9841	0.9333	0.9762	0.9661	0.9655	1.0	1.0	0.9714	1.0	1.0
0.0001	6.3802	4900	0.1115	0.9794	0.9769	0.9850	0.9632	0.9667	0.9792	0.9744	0.98	0.9905	1.0	1.0	0.9556	1.0	0.9778	0.9683	0.875	0.9535	0.9344	0.9545	1.0	1.0	1.0	1.0	1.0	0.9813	0.9704	0.9831	0.9691	0.9870	0.98	0.9952	0.9863	0.9892	0.9149	0.9903	0.9670	0.976	0.9333	0.9647	0.9661	0.9655	1.0	1.0	0.9714	1.0	1.0
0.0135	6.5104	5000	0.1094	0.9779	0.9754	0.9850	0.9779	0.9667	0.9792	0.9744	0.96	0.9905	1.0	1.0	0.8667	1.0	0.9778	0.9683	0.875	0.9535	0.9344	0.9773	1.0	1.0	1.0	1.0	1.0	0.9813	0.9638	0.9831	0.9691	0.9870	0.9697	0.9952	0.9863	0.9892	0.8864	1.0	0.9670	0.9683	0.9333	0.9647	0.9661	0.9773	1.0	1.0	0.9714	1.0	1.0
0.0001	6.6406	5100	0.1110	0.9794	0.9770	0.9850	0.9779	0.9667	0.9792	0.9744	0.98	0.9905	1.0	1.0	0.8889	1.0	0.9778	0.9683	0.875	0.9535	0.9344	0.9773	1.0	1.0	1.0	1.0	1.0	0.9813	0.9673	0.9831	0.9792	0.9870	0.98	0.9952	0.9863	0.9892	0.8989	0.9903	0.9670	0.976	0.9333	0.9647	0.9661	0.9773	1.0	1.0	0.9714	1.0	1.0
0.0003	6.7708	5200	0.1118	0.9786	0.9760	0.9850	0.9779	0.9667	0.9792	0.9744	0.98	0.9905	1.0	1.0	0.8889	1.0	0.9778	0.9683	0.875	0.9535	0.9344	0.9545	1.0	1.0	1.0	1.0	1.0	0.9813	0.9673	0.9831	0.9691	0.9870	0.98	0.9952	0.9863	0.9892	0.8989	0.9903	0.9670	0.976	0.9333	0.9647	0.9661	0.9655	1.0	1.0	0.9714	1.0	1.0
0.0104	6.9010	5300	0.1088	0.9809	0.9785	0.9850	0.9779	0.9667	0.9792	0.9744	0.98	0.9905	1.0	1.0	0.9111	1.0	0.9778	0.9841	0.875	0.9535	0.9508	0.9545	1.0	1.0	1.0	1.0	1.0	0.9813	0.9708	0.9831	0.9691	0.9870	0.98	0.9952	0.9863	0.9892	0.9111	0.9903	0.9778	0.9841	0.9333	0.9762	0.9748	0.9655	1.0	1.0	0.9714	1.0	1.0

Framework versions

• Transformers 4.52.2
• Pytorch 2.6.0+cu124
• Datasets 3.6.0
• Tokenizers 0.21.1