bert-base-uncased-test_16_1069

This model is a fine-tuned version of bert-base-uncased on the glue dataset. It achieves the following results on the evaluation set:

• Loss: 4.3588
• F1: {'f1': 0.8042394014962594}
• Accuracy: {'accuracy': 0.6989453499520614}

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: 0.001
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2000

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Accuracy
No log	1.0	67	0.5879	{'f1': 0.8174603174603174}	{'accuracy': 0.6912751677852349}
No log	2.0	134	0.5747	{'f1': 0.7801857585139319}	{'accuracy': 0.7277085330776606}
No log	3.0	201	0.5570	{'f1': 0.8424206111443978}	{'accuracy': 0.74784276126558}
No log	4.0	268	0.7406	{'f1': 0.8374851720047449}	{'accuracy': 0.7372962607861937}
No log	5.0	335	0.8201	{'f1': 0.851421188630491}	{'accuracy': 0.7794822627037392}
No log	6.0	402	0.8660	{'f1': 0.8404825737265416}	{'accuracy': 0.7718120805369127}
No log	7.0	469	1.2029	{'f1': 0.8460087994971716}	{'accuracy': 0.7651006711409396}
0.3504	8.0	536	1.2559	{'f1': 0.8422344996930632}	{'accuracy': 0.7535953978907}
0.3504	9.0	603	1.4866	{'f1': 0.8425692695214106}	{'accuracy': 0.7603068072866731}
0.3504	10.0	670	1.4314	{'f1': 0.8419023136246786}	{'accuracy': 0.7641418983700863}
0.3504	11.0	737	1.6634	{'f1': 0.8441308531109686}	{'accuracy': 0.7670182166826462}
0.3504	12.0	804	1.3683	{'f1': 0.8448500651890483}	{'accuracy': 0.7718120805369127}
0.3504	13.0	871	1.9068	{'f1': 0.8430160692212608}	{'accuracy': 0.7564717162032598}
0.3504	14.0	938	1.9702	{'f1': 0.8393194706994328}	{'accuracy': 0.7555129434324065}
0.0577	15.0	1005	1.7388	{'f1': 0.8427339084273391}	{'accuracy': 0.7727708533077661}
0.0577	16.0	1072	1.5435	{'f1': 0.8409937888198759}	{'accuracy': 0.7545541706615532}
0.0577	17.0	1139	1.6057	{'f1': 0.8374253483742535}	{'accuracy': 0.7651006711409396}
0.0577	18.0	1206	1.3399	{'f1': 0.8447284345047924}	{'accuracy': 0.7670182166826462}
0.0577	19.0	1273	1.4941	{'f1': 0.8412698412698413}	{'accuracy': 0.7698945349952061}
0.0577	20.0	1340	1.7071	{'f1': 0.8478396994364433}	{'accuracy': 0.7670182166826462}
0.0577	21.0	1407	1.2847	{'f1': 0.8509316770186335}	{'accuracy': 0.7698945349952061}
0.0577	22.0	1474	1.5951	{'f1': 0.8489483747609943}	{'accuracy': 0.7727708533077661}
0.0419	23.0	1541	1.3749	{'f1': 0.8505897771952817}	{'accuracy': 0.7813998082454459}
0.0419	24.0	1608	1.5838	{'f1': 0.8468468468468469}	{'accuracy': 0.7718120805369127}
0.0419	25.0	1675	2.0442	{'f1': 0.8368967623701894}	{'accuracy': 0.7440076701821668}
0.0419	26.0	1742	1.7379	{'f1': 0.8339719029374203}	{'accuracy': 0.75071907957814}
0.0419	27.0	1809	1.4958	{'f1': 0.8419753086419752}	{'accuracy': 0.7545541706615532}
0.0419	28.0	1876	1.6073	{'f1': 0.8396756082345601}	{'accuracy': 0.7535953978907}
0.0419	29.0	1943	1.0036	{'f1': 0.8360433604336043}	{'accuracy': 0.7679769894534996}
0.049	30.0	2010	1.5835	{'f1': 0.8313993174061434}	{'accuracy': 0.763183125599233}
0.049	31.0	2077	1.5472	{'f1': 0.8412397216951296}	{'accuracy': 0.7593480345158198}
0.049	32.0	2144	1.4587	{'f1': 0.8435643564356435}	{'accuracy': 0.7727708533077661}
0.049	33.0	2211	1.8834	{'f1': 0.8427594779366064}	{'accuracy': 0.7574304889741131}
0.049	34.0	2278	1.7062	{'f1': 0.8425584255842559}	{'accuracy': 0.7545541706615532}
0.049	35.0	2345	1.8846	{'f1': 0.8468137254901961}	{'accuracy': 0.7603068072866731}
0.049	36.0	2412	1.2837	{'f1': 0.8472843450479234}	{'accuracy': 0.7708533077660594}
0.049	37.0	2479	1.5835	{'f1': 0.8322411533420708}	{'accuracy': 0.7545541706615532}
0.0471	38.0	2546	1.7109	{'f1': 0.8350515463917526}	{'accuracy': 0.7545541706615532}
0.0471	39.0	2613	2.3271	{'f1': 0.8419721871049306}	{'accuracy': 0.7603068072866731}
0.0471	40.0	2680	2.0836	{'f1': 0.8341772151898734}	{'accuracy': 0.7488015340364333}
0.0471	41.0	2747	1.4783	{'f1': 0.8168421052631578}	{'accuracy': 0.7497603068072867}
0.0471	42.0	2814	1.5867	{'f1': 0.8466876971608833}	{'accuracy': 0.7670182166826462}
0.0471	43.0	2881	1.9556	{'f1': 0.8398791540785498}	{'accuracy': 0.7459252157238735}
0.0471	44.0	2948	1.8652	{'f1': 0.8446417247939126}	{'accuracy': 0.7651006711409396}
0.0272	45.0	3015	1.4984	{'f1': 0.8384223918575064}	{'accuracy': 0.7564717162032598}
0.0272	46.0	3082	2.2976	{'f1': 0.8434466019417476}	{'accuracy': 0.7526366251198466}
0.0272	47.0	3149	1.7726	{'f1': 0.8271687962340282}	{'accuracy': 0.7535953978907}
0.0272	48.0	3216	1.4079	{'f1': 0.8417680973734787}	{'accuracy': 0.763183125599233}
0.0272	49.0	3283	1.9601	{'f1': 0.8388780169602087}	{'accuracy': 0.763183125599233}
0.0272	50.0	3350	1.7132	{'f1': 0.8419672131147541}	{'accuracy': 0.7689357622243528}
0.0272	51.0	3417	1.9065	{'f1': 0.8423772609819122}	{'accuracy': 0.7660594439117929}
0.0272	52.0	3484	1.6271	{'f1': 0.8435374149659863}	{'accuracy': 0.7574304889741131}
0.035	53.0	3551	1.9134	{'f1': 0.839030453697949}	{'accuracy': 0.7516778523489933}
0.035	54.0	3618	1.2223	{'f1': 0.8315412186379928}	{'accuracy': 0.7296260786193672}
0.035	55.0	3685	1.9100	{'f1': 0.8471953578336557}	{'accuracy': 0.7727708533077661}
0.035	56.0	3752	1.7624	{'f1': 0.8410513141426784}	{'accuracy': 0.7564717162032598}
0.035	57.0	3819	1.6260	{'f1': 0.8396846254927727}	{'accuracy': 0.7660594439117929}
0.035	58.0	3886	1.8729	{'f1': 0.838868388683887}	{'accuracy': 0.7488015340364333}
0.035	59.0	3953	1.7361	{'f1': 0.842039800995025}	{'accuracy': 0.7564717162032598}
0.0425	60.0	4020	2.6457	{'f1': 0.8328267477203647}	{'accuracy': 0.7363374880153404}
0.0425	61.0	4087	1.6427	{'f1': 0.8251400124455508}	{'accuracy': 0.7305848513902206}
0.0425	62.0	4154	1.8693	{'f1': 0.8444444444444443}	{'accuracy': 0.7651006711409396}
0.0425	63.0	4221	1.4339	{'f1': 0.8385449904275686}	{'accuracy': 0.7574304889741131}
0.0425	64.0	4288	1.9156	{'f1': 0.8382165605095542}	{'accuracy': 0.7564717162032598}
0.0425	65.0	4355	1.8338	{'f1': 0.8368146214099217}	{'accuracy': 0.7603068072866731}
0.0425	66.0	4422	1.3498	{'f1': 0.8367473618870268}	{'accuracy': 0.74784276126558}
0.0425	67.0	4489	2.1211	{'f1': 0.8415584415584416}	{'accuracy': 0.7660594439117929}
0.049	68.0	4556	1.9182	{'f1': 0.8391332895600787}	{'accuracy': 0.7651006711409396}
0.049	69.0	4623	1.6831	{'f1': 0.8395061728395061}	{'accuracy': 0.763183125599233}
0.049	70.0	4690	1.5006	{'f1': 0.8284789644012944}	{'accuracy': 0.7459252157238735}
0.049	71.0	4757	1.1305	{'f1': 0.821664464993395}	{'accuracy': 0.7411313518696069}
0.049	72.0	4824	1.8027	{'f1': 0.8407407407407408}	{'accuracy': 0.7526366251198466}
0.049	73.0	4891	2.4575	{'f1': 0.8399044205495819}	{'accuracy': 0.7430488974113135}
0.049	74.0	4958	1.5636	{'f1': 0.8385449904275686}	{'accuracy': 0.7574304889741131}
0.0443	75.0	5025	1.5191	{'f1': 0.8409669211195929}	{'accuracy': 0.7603068072866731}
0.0443	76.0	5092	1.4819	{'f1': 0.8215994531784004}	{'accuracy': 0.7497603068072867}
0.0443	77.0	5159	1.9624	{'f1': 0.8336448598130841}	{'accuracy': 0.7440076701821668}
0.0443	78.0	5226	2.6006	{'f1': 0.8401997503121098}	{'accuracy': 0.7545541706615532}
0.0443	79.0	5293	1.7369	{'f1': 0.8461538461538463}	{'accuracy': 0.7622243528283796}
0.0443	80.0	5360	1.3129	{'f1': 0.8339920948616601}	{'accuracy': 0.7583892617449665}
0.0443	81.0	5427	2.0260	{'f1': 0.8430769230769232}	{'accuracy': 0.7555129434324065}
0.0443	82.0	5494	1.4667	{'f1': 0.8365758754863812}	{'accuracy': 0.7583892617449665}
0.0481	83.0	5561	1.3350	{'f1': 0.8410852713178294}	{'accuracy': 0.7641418983700863}
0.0481	84.0	5628	1.3928	{'f1': 0.8393977415307404}	{'accuracy': 0.7545541706615532}
0.0481	85.0	5695	1.7076	{'f1': 0.8338804990151018}	{'accuracy': 0.7574304889741131}
0.0481	86.0	5762	2.0295	{'f1': 0.824607329842932}	{'accuracy': 0.7430488974113135}
0.0481	87.0	5829	1.6961	{'f1': 0.8389560789306174}	{'accuracy': 0.7574304889741131}
0.0481	88.0	5896	1.5844	{'f1': 0.824755700325733}	{'accuracy': 0.7420901246404602}
0.0481	89.0	5963	1.9236	{'f1': 0.814411964649898}	{'accuracy': 0.738255033557047}
0.0483	90.0	6030	1.6411	{'f1': 0.8293316028552888}	{'accuracy': 0.74784276126558}
0.0483	91.0	6097	1.8739	{'f1': 0.8402439024390244}	{'accuracy': 0.7488015340364333}
0.0483	92.0	6164	1.8395	{'f1': 0.8351368555060471}	{'accuracy': 0.7516778523489933}
0.0483	93.0	6231	2.0723	{'f1': 0.8405438813349814}	{'accuracy': 0.7526366251198466}
0.0483	94.0	6298	1.8634	{'f1': 0.8415300546448088}	{'accuracy': 0.7497603068072867}
0.0483	95.0	6365	1.9256	{'f1': 0.8295662797800855}	{'accuracy': 0.7325023969319271}
0.0483	96.0	6432	2.0026	{'f1': 0.8403465346534654}	{'accuracy': 0.7526366251198466}
0.0483	97.0	6499	2.0732	{'f1': 0.8286384976525822}	{'accuracy': 0.7200383509108341}
0.0384	98.0	6566	1.8737	{'f1': 0.8503532434168274}	{'accuracy': 0.7766059443911792}
0.0384	99.0	6633	2.0952	{'f1': 0.8365444375388441}	{'accuracy': 0.74784276126558}
0.0384	100.0	6700	2.4121	{'f1': 0.8460591133004927}	{'accuracy': 0.7603068072866731}
0.0384	101.0	6767	1.8195	{'f1': 0.8396464646464646}	{'accuracy': 0.7564717162032598}
0.0384	102.0	6834	1.4623	{'f1': 0.797486033519553}	{'accuracy': 0.7219558964525408}
0.0384	103.0	6901	2.1245	{'f1': 0.8391089108910891}	{'accuracy': 0.75071907957814}
0.0384	104.0	6968	1.6440	{'f1': 0.8405797101449276}	{'accuracy': 0.7679769894534996}
0.038	105.0	7035	1.9479	{'f1': 0.8314754098360656}	{'accuracy': 0.7535953978907}
0.038	106.0	7102	1.8748	{'f1': 0.8328154133001864}	{'accuracy': 0.7420901246404602}
0.038	107.0	7169	1.4211	{'f1': 0.831151832460733}	{'accuracy': 0.7526366251198466}
0.038	108.0	7236	1.9897	{'f1': 0.823529411764706}	{'accuracy': 0.7325023969319271}
0.038	109.0	7303	1.7817	{'f1': 0.8084239130434783}	{'accuracy': 0.7296260786193672}
0.038	110.0	7370	1.8589	{'f1': 0.8134920634920636}	{'accuracy': 0.7296260786193672}
0.038	111.0	7437	2.0391	{'f1': 0.8152454780361758}	{'accuracy': 0.725790987535954}
0.0532	112.0	7504	1.6395	{'f1': 0.828996282527881}	{'accuracy': 0.7353787152444871}
0.0532	113.0	7571	2.2076	{'f1': 0.8341645885286784}	{'accuracy': 0.7449664429530202}
0.0532	114.0	7638	2.4226	{'f1': 0.8337378640776699}	{'accuracy': 0.7372962607861937}
0.0532	115.0	7705	1.2817	{'f1': 0.8342714196372732}	{'accuracy': 0.7459252157238735}
0.0532	116.0	7772	2.2737	{'f1': 0.8317073170731707}	{'accuracy': 0.7353787152444871}
0.0532	117.0	7839	1.9394	{'f1': 0.8260325406758449}	{'accuracy': 0.7334611697027804}
0.0532	118.0	7906	2.2936	{'f1': 0.8234536082474228}	{'accuracy': 0.7372962607861937}
0.0532	119.0	7973	1.8452	{'f1': 0.8306148055207027}	{'accuracy': 0.7411313518696069}
0.049	120.0	8040	2.4783	{'f1': 0.8275449101796407}	{'accuracy': 0.7238734419942474}
0.049	121.0	8107	2.1361	{'f1': 0.8167202572347267}	{'accuracy': 0.7267497603068073}
0.049	122.0	8174	2.0442	{'f1': 0.830848995463383}	{'accuracy': 0.7497603068072867}
0.049	123.0	8241	2.4047	{'f1': 0.8211920529801324}	{'accuracy': 0.7411313518696069}
0.049	124.0	8308	1.4207	{'f1': 0.8226018396846255}	{'accuracy': 0.7411313518696069}
0.049	125.0	8375	2.2460	{'f1': 0.8252184769038702}	{'accuracy': 0.7315436241610739}
0.049	126.0	8442	2.6570	{'f1': 0.8257211538461539}	{'accuracy': 0.7219558964525408}
0.0343	127.0	8509	2.5992	{'f1': 0.8293867638129933}	{'accuracy': 0.7305848513902206}
0.0343	128.0	8576	2.6733	{'f1': 0.8308823529411765}	{'accuracy': 0.7353787152444871}
0.0343	129.0	8643	2.6073	{'f1': 0.8283723875870805}	{'accuracy': 0.7401725790987536}
0.0343	130.0	8710	1.9251	{'f1': 0.805668016194332}	{'accuracy': 0.7238734419942474}
0.0343	131.0	8777	1.6319	{'f1': 0.8204456094364352}	{'accuracy': 0.7372962607861937}
0.0343	132.0	8844	1.9498	{'f1': 0.8269230769230769}	{'accuracy': 0.7411313518696069}
0.0343	133.0	8911	1.8111	{'f1': 0.8309677419354838}	{'accuracy': 0.7488015340364333}
0.0343	134.0	8978	1.9456	{'f1': 0.8246753246753247}	{'accuracy': 0.7411313518696069}
0.0361	135.0	9045	2.1826	{'f1': 0.8220937700706487}	{'accuracy': 0.7344199424736337}
0.0361	136.0	9112	1.5774	{'f1': 0.8310387984981228}	{'accuracy': 0.7411313518696069}
0.0361	137.0	9179	2.4278	{'f1': 0.8249075215782984}	{'accuracy': 0.7277085330776606}
0.0361	138.0	9246	1.3895	{'f1': 0.8233082706766918}	{'accuracy': 0.7296260786193672}
0.0361	139.0	9313	2.0902	{'f1': 0.8128342245989304}	{'accuracy': 0.7315436241610739}
0.0361	140.0	9380	2.0259	{'f1': 0.8232354778263585}	{'accuracy': 0.7286673058485139}
0.0361	141.0	9447	2.1325	{'f1': 0.825515947467167}	{'accuracy': 0.7325023969319271}
0.0562	142.0	9514	2.0610	{'f1': 0.8207426376440461}	{'accuracy': 0.7315436241610739}
0.0562	143.0	9581	1.4215	{'f1': 0.8223938223938223}	{'accuracy': 0.7353787152444871}
0.0562	144.0	9648	1.4644	{'f1': 0.8226120857699806}	{'accuracy': 0.738255033557047}
0.0562	145.0	9715	2.3814	{'f1': 0.8266003729024238}	{'accuracy': 0.7325023969319271}
0.0562	146.0	9782	2.2019	{'f1': 0.828334396936822}	{'accuracy': 0.7420901246404602}
0.0562	147.0	9849	2.4529	{'f1': 0.8213836477987422}	{'accuracy': 0.7277085330776606}
0.0562	148.0	9916	1.8754	{'f1': 0.8313479623824451}	{'accuracy': 0.7420901246404602}
0.0562	149.0	9983	2.0815	{'f1': 0.8332329921733895}	{'accuracy': 0.7344199424736337}
0.0457	150.0	10050	1.8325	{'f1': 0.8277634961439588}	{'accuracy': 0.7430488974113135}
0.0457	151.0	10117	1.9036	{'f1': 0.8309859154929577}	{'accuracy': 0.7468839884947267}
0.0457	152.0	10184	1.8461	{'f1': 0.8303516347933374}	{'accuracy': 0.7363374880153404}
0.0457	153.0	10251	1.7572	{'f1': 0.8288834951456312}	{'accuracy': 0.7296260786193672}
0.0457	154.0	10318	1.5614	{'f1': 0.8228423101881894}	{'accuracy': 0.738255033557047}
0.0457	155.0	10385	1.3556	{'f1': 0.8275862068965517}	{'accuracy': 0.7363374880153404}
0.0457	156.0	10452	1.7987	{'f1': 0.8391959798994975}	{'accuracy': 0.7545541706615532}
0.0464	157.0	10519	1.8711	{'f1': 0.827930174563591}	{'accuracy': 0.7353787152444871}
0.0464	158.0	10586	1.9391	{'f1': 0.8280407429598563}	{'accuracy': 0.7248322147651006}
0.0464	159.0	10653	1.3466	{'f1': 0.8326797385620914}	{'accuracy': 0.7545541706615532}
0.0464	160.0	10720	2.0257	{'f1': 0.8271527341294783}	{'accuracy': 0.7363374880153404}
0.0464	161.0	10787	1.5463	{'f1': 0.832089552238806}	{'accuracy': 0.7411313518696069}
0.0464	162.0	10854	2.1249	{'f1': 0.8290488431876606}	{'accuracy': 0.7449664429530202}
0.0464	163.0	10921	1.5738	{'f1': 0.8220064724919095}	{'accuracy': 0.7363374880153404}
0.0464	164.0	10988	1.4705	{'f1': 0.8270096463022508}	{'accuracy': 0.7420901246404602}
0.0465	165.0	11055	2.3533	{'f1': 0.8257107540173053}	{'accuracy': 0.7296260786193672}
0.0465	166.0	11122	2.3995	{'f1': 0.8253968253968255}	{'accuracy': 0.725790987535954}
0.0465	167.0	11189	2.1748	{'f1': 0.8285714285714286}	{'accuracy': 0.7238734419942474}
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0.0018	1346.0	90182	3.5026	{'f1': 0.7960074859638179}	{'accuracy': 0.6864813039309684}
0.0018	1347.0	90249	3.4149	{'f1': 0.7999999999999999}	{'accuracy': 0.6922339405560882}
0.0018	1348.0	90316	3.5256	{'f1': 0.8007471980074721}	{'accuracy': 0.6931927133269415}
0.0018	1349.0	90383	3.4582	{'f1': 0.7995049504950494}	{'accuracy': 0.6893576222435283}
0.0018	1350.0	90450	3.4387	{'f1': 0.7929956222639148}	{'accuracy': 0.6826462128475551}
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0.0098	1354.0	90718	3.6885	{'f1': 0.7896399241945673}	{'accuracy': 0.6807286673058485}
0.0098	1355.0	90785	3.7110	{'f1': 0.7901077996195307}	{'accuracy': 0.6826462128475551}
0.0098	1356.0	90852	2.9285	{'f1': 0.791194968553459}	{'accuracy': 0.6816874400767018}
0.0098	1357.0	90919	3.3688	{'f1': 0.8002450980392157}	{'accuracy': 0.6874400767018217}
0.0098	1358.0	90986	2.5591	{'f1': 0.7907869481765835}	{'accuracy': 0.6864813039309684}
0.0059	1359.0	91053	2.7547	{'f1': 0.8046540110226578}	{'accuracy': 0.6941514860977949}
0.0059	1360.0	91120	3.0628	{'f1': 0.8041615667074663}	{'accuracy': 0.6931927133269415}
0.0059	1361.0	91187	3.2081	{'f1': 0.7987616099071208}	{'accuracy': 0.6883988494726749}
0.0059	1362.0	91254	3.3036	{'f1': 0.8024539877300614}	{'accuracy': 0.6912751677852349}
0.0059	1363.0	91321	3.3669	{'f1': 0.7992565055762082}	{'accuracy': 0.6893576222435283}
0.0059	1364.0	91388	3.3955	{'f1': 0.7985028072364316}	{'accuracy': 0.6903163950143816}
0.0059	1365.0	91455	3.4439	{'f1': 0.7957393483709274}	{'accuracy': 0.6874400767018217}
0.0029	1366.0	91522	3.4882	{'f1': 0.7949685534591195}	{'accuracy': 0.6874400767018217}
0.0029	1367.0	91589	3.6078	{'f1': 0.8065893837705919}	{'accuracy': 0.6960690316395014}
0.0029	1368.0	91656	3.6177	{'f1': 0.8048632218844985}	{'accuracy': 0.6922339405560882}
0.0029	1369.0	91723	3.5784	{'f1': 0.801998750780762}	{'accuracy': 0.6960690316395014}
0.0029	1370.0	91790	3.6970	{'f1': 0.80440097799511}	{'accuracy': 0.6931927133269415}
0.0029	1371.0	91857	3.5104	{'f1': 0.8014796547472257}	{'accuracy': 0.6912751677852349}
0.0029	1372.0	91924	3.4500	{'f1': 0.8075060532687652}	{'accuracy': 0.6951102588686481}
0.0029	1373.0	91991	3.3145	{'f1': 0.7916137229987293}	{'accuracy': 0.6855225311601151}
0.0048	1374.0	92058	3.4664	{'f1': 0.7908745247148289}	{'accuracy': 0.6836049856184084}
0.0048	1375.0	92125	3.5522	{'f1': 0.7962962962962964}	{'accuracy': 0.6836049856184084}
0.0048	1376.0	92192	3.1959	{'f1': 0.7972805933250927}	{'accuracy': 0.6855225311601151}
0.0048	1377.0	92259	3.3601	{'f1': 0.7937694704049844}	{'accuracy': 0.6826462128475551}
0.0048	1378.0	92326	3.6030	{'f1': 0.7987692307692308}	{'accuracy': 0.6864813039309684}
0.0048	1379.0	92393	3.7060	{'f1': 0.7972889710412815}	{'accuracy': 0.6845637583892618}
0.0048	1380.0	92460	3.6752	{'f1': 0.7926442612555485}	{'accuracy': 0.6864813039309684}
0.0034	1381.0	92527	3.6294	{'f1': 0.801470588235294}	{'accuracy': 0.6893576222435283}
0.0034	1382.0	92594	3.3531	{'f1': 0.7905491698595146}	{'accuracy': 0.6855225311601151}
0.0034	1383.0	92661	3.6748	{'f1': 0.801470588235294}	{'accuracy': 0.6893576222435283}
0.0034	1384.0	92728	3.4228	{'f1': 0.8004895960832313}	{'accuracy': 0.6874400767018217}
0.0034	1385.0	92795	2.9708	{'f1': 0.798261949099938}	{'accuracy': 0.6883988494726749}
0.0034	1386.0	92862	3.1387	{'f1': 0.7951959544879897}	{'accuracy': 0.6893576222435283}
0.0034	1387.0	92929	3.4098	{'f1': 0.7695417789757413}	{'accuracy': 0.6720997123681688}
0.0034	1388.0	92996	3.3922	{'f1': 0.7936708860759493}	{'accuracy': 0.6874400767018217}
0.0052	1389.0	93063	3.4956	{'f1': 0.7913486005089059}	{'accuracy': 0.6855225311601151}
0.0052	1390.0	93130	3.5436	{'f1': 0.7923809523809524}	{'accuracy': 0.6864813039309684}
0.0052	1391.0	93197	3.4887	{'f1': 0.7864450127877236}	{'accuracy': 0.6797698945349953}
0.0052	1392.0	93264	3.6942	{'f1': 0.7830006439150032}	{'accuracy': 0.6768935762224353}
0.0052	1393.0	93331	2.9826	{'f1': 0.811332127787824}	{'accuracy': 0.6999041227229147}
0.0052	1394.0	93398	2.9983	{'f1': 0.7822736030828518}	{'accuracy': 0.6749760306807286}
0.0052	1395.0	93465	3.2938	{'f1': 0.7704590818363273}	{'accuracy': 0.6692233940556088}
0.0068	1396.0	93532	2.9958	{'f1': 0.785946649316851}	{'accuracy': 0.6845637583892618}
0.0068	1397.0	93599	3.0239	{'f1': 0.7788778877887788}	{'accuracy': 0.6788111217641419}
0.0068	1398.0	93666	3.4180	{'f1': 0.8043875685557585}	{'accuracy': 0.6922339405560882}
0.0068	1399.0	93733	3.4258	{'f1': 0.7969543147208121}	{'accuracy': 0.6931927133269415}
0.0068	1400.0	93800	3.5414	{'f1': 0.802252816020025}	{'accuracy': 0.6970278044103547}
0.0068	1401.0	93867	3.2204	{'f1': 0.8063725490196079}	{'accuracy': 0.6970278044103547}
0.0068	1402.0	93934	3.4795	{'f1': 0.8068043742405833}	{'accuracy': 0.6951102588686481}
0.0041	1403.0	94001	3.5626	{'f1': 0.8037037037037037}	{'accuracy': 0.6951102588686481}
0.0041	1404.0	94068	3.6109	{'f1': 0.8012422360248448}	{'accuracy': 0.6931927133269415}
0.0041	1405.0	94135	3.6412	{'f1': 0.8012422360248448}	{'accuracy': 0.6931927133269415}
0.0041	1406.0	94202	3.7176	{'f1': 0.8029286150091519}	{'accuracy': 0.6903163950143816}
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0.0041	1409.0	94403	3.3676	{'f1': 0.7905491698595146}	{'accuracy': 0.6855225311601151}
0.0041	1410.0	94470	3.4582	{'f1': 0.800497203231821}	{'accuracy': 0.6922339405560882}
0.0059	1411.0	94537	3.2096	{'f1': 0.7977315689981097}	{'accuracy': 0.6922339405560882}
0.0059	1412.0	94604	3.3712	{'f1': 0.7913486005089059}	{'accuracy': 0.6855225311601151}
0.0059	1413.0	94671	3.5329	{'f1': 0.7977873386601106}	{'accuracy': 0.6845637583892618}
0.0059	1414.0	94738	3.0765	{'f1': 0.7813525935653316}	{'accuracy': 0.6807286673058485}
0.0059	1415.0	94805	3.3088	{'f1': 0.7835723598435462}	{'accuracy': 0.6816874400767018}
0.0059	1416.0	94872	3.1667	{'f1': 0.7979797979797981}	{'accuracy': 0.6931927133269415}
0.0059	1417.0	94939	3.2078	{'f1': 0.798023471278567}	{'accuracy': 0.6864813039309684}
0.007	1418.0	95006	3.1327	{'f1': 0.7829508196721311}	{'accuracy': 0.6826462128475551}
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0.007	1420.0	95140	3.4375	{'f1': 0.797752808988764}	{'accuracy': 0.6893576222435283}
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0.007	1425.0	95475	3.6972	{'f1': 0.7868437697659709}	{'accuracy': 0.6768935762224353}
0.0028	1426.0	95542	3.7329	{'f1': 0.7861635220125784}	{'accuracy': 0.6740172579098753}
0.0028	1427.0	95609	3.6850	{'f1': 0.7794404684450227}	{'accuracy': 0.6749760306807286}
0.0028	1428.0	95676	3.7515	{'f1': 0.8002450980392157}	{'accuracy': 0.6874400767018217}
0.0028	1429.0	95743	3.4235	{'f1': 0.7967377666248431}	{'accuracy': 0.6893576222435283}
0.0028	1430.0	95810	3.5204	{'f1': 0.7802631578947368}	{'accuracy': 0.6797698945349953}
0.0028	1431.0	95877	3.7457	{'f1': 0.7990165949600492}	{'accuracy': 0.6864813039309684}
0.0028	1432.0	95944	3.7481	{'f1': 0.7952110901071204}	{'accuracy': 0.6883988494726749}
0.0028	1433.0	96011	3.7664	{'f1': 0.7916137229987293}	{'accuracy': 0.6855225311601151}
0.0028	1434.0	96078	4.0154	{'f1': 0.8033674082982563}	{'accuracy': 0.6864813039309684}
0.0028	1435.0	96145	3.7095	{'f1': 0.7887323943661971}	{'accuracy': 0.6836049856184084}
0.0028	1436.0	96212	3.6431	{'f1': 0.7901390644753477}	{'accuracy': 0.6816874400767018}
0.0028	1437.0	96279	3.6659	{'f1': 0.7901701323251417}	{'accuracy': 0.6807286673058485}
0.0028	1438.0	96346	3.8164	{'f1': 0.7915057915057916}	{'accuracy': 0.6893576222435283}
0.0028	1439.0	96413	4.0316	{'f1': 0.7943696450428397}	{'accuracy': 0.6778523489932886}
0.0028	1440.0	96480	3.9612	{'f1': 0.789980732177264}	{'accuracy': 0.6864813039309684}
0.0022	1441.0	96547	4.0944	{'f1': 0.7943349753694582}	{'accuracy': 0.6797698945349953}
0.0022	1442.0	96614	4.0300	{'f1': 0.7878787878787878}	{'accuracy': 0.6845637583892618}
0.0022	1443.0	96681	4.0878	{'f1': 0.7902010050251256}	{'accuracy': 0.6797698945349953}
0.0022	1444.0	96748	2.6609	{'f1': 0.7903123008285532}	{'accuracy': 0.6845637583892618}
0.0022	1445.0	96815	3.1001	{'f1': 0.7969924812030076}	{'accuracy': 0.6893576222435283}
0.0022	1446.0	96882	3.2334	{'f1': 0.7975}	{'accuracy': 0.6893576222435283}
0.0022	1447.0	96949	3.3149	{'f1': 0.7975}	{'accuracy': 0.6893576222435283}
0.0056	1448.0	97016	2.9839	{'f1': 0.7967980295566502}	{'accuracy': 0.6836049856184084}
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0.0056	1452.0	97284	3.4439	{'f1': 0.7999999999999999}	{'accuracy': 0.6893576222435283}
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0.001	1456.0	97552	3.6596	{'f1': 0.7908455181182453}	{'accuracy': 0.6845637583892618}
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0.001	1458.0	97686	3.8821	{'f1': 0.8041112454655381}	{'accuracy': 0.6893576222435283}
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0.001	1460.0	97820	3.9333	{'f1': 0.795525170913611}	{'accuracy': 0.6845637583892618}
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0.002	1470.0	98490	3.7897	{'f1': 0.7970297029702972}	{'accuracy': 0.6855225311601151}
0.0032	1471.0	98557	3.8409	{'f1': 0.7930391547545058}	{'accuracy': 0.6807286673058485}
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0.0021	1486.0	99562	3.5731	{'f1': 0.7941735275490817}	{'accuracy': 0.6883988494726749}
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0.0021	1491.0	99897	3.5840	{'f1': 0.7820429407937541}	{'accuracy': 0.6788111217641419}
0.0021	1492.0	99964	3.6197	{'f1': 0.7833441769681196}	{'accuracy': 0.6807286673058485}
0.0023	1493.0	100031	3.8801	{'f1': 0.801470588235294}	{'accuracy': 0.6893576222435283}
0.0023	1494.0	100098	3.8196	{'f1': 0.7916666666666666}	{'accuracy': 0.6836049856184084}
0.0023	1495.0	100165	3.9101	{'f1': 0.7924764890282132}	{'accuracy': 0.6826462128475551}
0.0023	1496.0	100232	3.8737	{'f1': 0.7937304075235111}	{'accuracy': 0.6845637583892618}
0.0023	1497.0	100299	3.8839	{'f1': 0.7929736511919698}	{'accuracy': 0.6836049856184084}
0.0023	1498.0	100366	3.8983	{'f1': 0.7922159447583176}	{'accuracy': 0.6826462128475551}
0.0023	1499.0	100433	3.8861	{'f1': 0.795525170913611}	{'accuracy': 0.6845637583892618}
0.0023	1500.0	100500	3.7224	{'f1': 0.7930174563591023}	{'accuracy': 0.6816874400767018}
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0.0023	1502.0	100634	3.7528	{'f1': 0.7999999999999999}	{'accuracy': 0.6874400767018217}
0.0023	1503.0	100701	3.8137	{'f1': 0.7987692307692308}	{'accuracy': 0.6864813039309684}
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0.0023	1506.0	100902	3.7625	{'f1': 0.7877237851662404}	{'accuracy': 0.6816874400767018}
0.0023	1507.0	100969	3.8550	{'f1': 0.7982673267326732}	{'accuracy': 0.6874400767018217}
0.0025	1508.0	101036	3.9085	{'f1': 0.7999999999999999}	{'accuracy': 0.6893576222435283}
0.0025	1509.0	101103	4.0174	{'f1': 0.7683997299122215}	{'accuracy': 0.6711409395973155}
0.0025	1510.0	101170	3.8887	{'f1': 0.7985028072364316}	{'accuracy': 0.6903163950143816}
0.0025	1511.0	101237	3.9713	{'f1': 0.8034292712798531}	{'accuracy': 0.6922339405560882}
0.0025	1512.0	101304	3.9676	{'f1': 0.7949843260188089}	{'accuracy': 0.6864813039309684}
0.0025	1513.0	101371	4.1217	{'f1': 0.7922885572139303}	{'accuracy': 0.6797698945349953}
0.0025	1514.0	101438	4.1307	{'f1': 0.792803970223325}	{'accuracy': 0.6797698945349953}
0.0022	1515.0	101505	4.1507	{'f1': 0.7937694704049844}	{'accuracy': 0.6826462128475551}
0.0022	1516.0	101572	4.1694	{'f1': 0.7942643391521197}	{'accuracy': 0.6836049856184084}
0.0022	1517.0	101639	4.1070	{'f1': 0.7830618892508142}	{'accuracy': 0.6807286673058485}
0.0022	1518.0	101706	4.1144	{'f1': 0.7897371714643304}	{'accuracy': 0.6778523489932886}
0.0022	1519.0	101773	4.1304	{'f1': 0.7904940587867417}	{'accuracy': 0.6788111217641419}
0.0022	1520.0	101840	4.1613	{'f1': 0.7943349753694582}	{'accuracy': 0.6797698945349953}
0.0022	1521.0	101907	2.8205	{'f1': 0.8000000000000002}	{'accuracy': 0.6864813039309684}
0.0022	1522.0	101974	2.9388	{'f1': 0.7928616953473551}	{'accuracy': 0.6883988494726749}
0.0052	1523.0	102041	3.3218	{'f1': 0.8034504004929144}	{'accuracy': 0.6941514860977949}
0.0052	1524.0	102108	3.6264	{'f1': 0.8048929663608563}	{'accuracy': 0.6941514860977949}
0.0052	1525.0	102175	3.6915	{'f1': 0.7895740623013351}	{'accuracy': 0.6826462128475551}
0.0052	1526.0	102242	3.7584	{'f1': 0.7879948914431673}	{'accuracy': 0.6816874400767018}
0.0052	1527.0	102309	3.7586	{'f1': 0.7881899871630295}	{'accuracy': 0.6836049856184084}
0.0052	1528.0	102376	3.8460	{'f1': 0.776595744680851}	{'accuracy': 0.6778523489932886}
0.0052	1529.0	102443	3.9641	{'f1': 0.7866752081998718}	{'accuracy': 0.6807286673058485}
0.0014	1530.0	102510	3.9847	{'f1': 0.7866752081998718}	{'accuracy': 0.6807286673058485}
0.0014	1531.0	102577	4.0077	{'f1': 0.7874519846350833}	{'accuracy': 0.6816874400767018}
0.0014	1532.0	102644	3.9787	{'f1': 0.7925233644859814}	{'accuracy': 0.6807286673058485}
0.0014	1533.0	102711	4.0011	{'f1': 0.7927815805849409}	{'accuracy': 0.6807286673058485}
0.0014	1534.0	102778	4.0214	{'f1': 0.7927815805849409}	{'accuracy': 0.6807286673058485}
0.0014	1535.0	102845	4.0718	{'f1': 0.7932118164676305}	{'accuracy': 0.6845637583892618}
0.0014	1536.0	102912	4.1053	{'f1': 0.7939508506616256}	{'accuracy': 0.6864813039309684}
0.0014	1537.0	102979	4.1312	{'f1': 0.7932118164676305}	{'accuracy': 0.6845637583892618}
0.0004	1538.0	103046	4.1561	{'f1': 0.7949843260188089}	{'accuracy': 0.6864813039309684}
0.0004	1539.0	103113	4.1738	{'f1': 0.7952261306532664}	{'accuracy': 0.6874400767018217}
0.0004	1540.0	103180	4.2048	{'f1': 0.7929292929292929}	{'accuracy': 0.6855225311601151}
0.0004	1541.0	103247	4.2178	{'f1': 0.7929292929292929}	{'accuracy': 0.6855225311601151}
0.0004	1542.0	103314	4.2313	{'f1': 0.7929292929292929}	{'accuracy': 0.6855225311601151}
0.0004	1543.0	103381	4.2515	{'f1': 0.7926675094816686}	{'accuracy': 0.6855225311601151}
0.0004	1544.0	103448	4.2633	{'f1': 0.7926675094816686}	{'accuracy': 0.6855225311601151}
0.0	1545.0	103515	4.2731	{'f1': 0.7926675094816686}	{'accuracy': 0.6855225311601151}
0.0	1546.0	103582	4.3004	{'f1': 0.7905792488860598}	{'accuracy': 0.6845637583892618}
0.0	1547.0	103649	4.2600	{'f1': 0.8108433734939758}	{'accuracy': 0.6989453499520614}
0.0	1548.0	103716	4.2463	{'f1': 0.7972889710412815}	{'accuracy': 0.6845637583892618}
0.0	1549.0	103783	4.2732	{'f1': 0.7924764890282132}	{'accuracy': 0.6826462128475551}
0.0	1550.0	103850	3.8756	{'f1': 0.8043875685557585}	{'accuracy': 0.6922339405560882}
0.0	1551.0	103917	3.2448	{'f1': 0.7796610169491526}	{'accuracy': 0.675934803451582}
0.0	1552.0	103984	3.3519	{'f1': 0.7755905511811024}	{'accuracy': 0.6720997123681688}
0.0053	1553.0	104051	3.4056	{'f1': 0.7838541666666667}	{'accuracy': 0.6816874400767018}
0.0053	1554.0	104118	3.3728	{'f1': 0.7960687960687961}	{'accuracy': 0.6816874400767018}
0.0053	1555.0	104185	3.4948	{'f1': 0.7962962962962964}	{'accuracy': 0.6836049856184084}
0.0053	1556.0	104252	3.5787	{'f1': 0.7975155279503106}	{'accuracy': 0.6874400767018217}
0.0053	1557.0	104319	3.6518	{'f1': 0.802937576499388}	{'accuracy': 0.6912751677852349}
0.0053	1558.0	104386	3.6993	{'f1': 0.7856685860524631}	{'accuracy': 0.6788111217641419}
0.0053	1559.0	104453	3.7444	{'f1': 0.7858974358974359}	{'accuracy': 0.6797698945349953}
0.0023	1560.0	104520	3.7746	{'f1': 0.7929956222639148}	{'accuracy': 0.6826462128475551}
0.0023	1561.0	104587	3.7981	{'f1': 0.7909604519774011}	{'accuracy': 0.6807286673058485}
0.0023	1562.0	104654	3.8361	{'f1': 0.7914572864321608}	{'accuracy': 0.6816874400767018}
0.0023	1563.0	104721	3.4894	{'f1': 0.797724399494311}	{'accuracy': 0.6931927133269415}
0.0023	1564.0	104788	3.3312	{'f1': 0.7967067764407854}	{'accuracy': 0.6922339405560882}
0.0023	1565.0	104855	3.4150	{'f1': 0.7933461292386437}	{'accuracy': 0.6903163950143816}
0.0023	1566.0	104922	3.5188	{'f1': 0.8034610630407911}	{'accuracy': 0.6951102588686481}
0.0023	1567.0	104989	3.5993	{'f1': 0.7944688874921433}	{'accuracy': 0.6864813039309684}
0.0039	1568.0	105056	3.6588	{'f1': 0.7954688483322845}	{'accuracy': 0.6883988494726749}
0.0039	1569.0	105123	3.6182	{'f1': 0.8049230769230769}	{'accuracy': 0.6960690316395014}
0.0039	1570.0	105190	3.6035	{'f1': 0.797752808988764}	{'accuracy': 0.6893576222435283}
0.0039	1571.0	105257	3.0259	{'f1': 0.8034934497816594}	{'accuracy': 0.697986577181208}
0.0039	1572.0	105324	2.7303	{'f1': 0.7826657912015758}	{'accuracy': 0.6826462128475551}
0.0039	1573.0	105391	3.0361	{'f1': 0.8044554455445544}	{'accuracy': 0.6970278044103547}
0.0039	1574.0	105458	3.1971	{'f1': 0.8027380211574363}	{'accuracy': 0.6960690316395014}
0.0041	1575.0	105525	3.3204	{'f1': 0.8007542426147077}	{'accuracy': 0.6960690316395014}
0.0041	1576.0	105592	3.3879	{'f1': 0.7997473152242578}	{'accuracy': 0.6960690316395014}
0.0041	1577.0	105659	3.4529	{'f1': 0.799240025332489}	{'accuracy': 0.6960690316395014}
0.0041	1578.0	105726	3.4423	{'f1': 0.7910828025477706}	{'accuracy': 0.6855225311601151}
0.0041	1579.0	105793	3.5559	{'f1': 0.7997520148791073}	{'accuracy': 0.6903163950143816}
0.0041	1580.0	105860	3.5181	{'f1': 0.7915330339961514}	{'accuracy': 0.6883988494726749}
0.0041	1581.0	105927	3.7802	{'f1': 0.7982673267326732}	{'accuracy': 0.6874400767018217}
0.0041	1582.0	105994	3.7558	{'f1': 0.7856677524429967}	{'accuracy': 0.6845637583892618}
0.0021	1583.0	106061	3.8630	{'f1': 0.7937304075235111}	{'accuracy': 0.6845637583892618}
0.0021	1584.0	106128	3.8877	{'f1': 0.794486215538847}	{'accuracy': 0.6855225311601151}
0.0021	1585.0	106195	3.9093	{'f1': 0.794486215538847}	{'accuracy': 0.6855225311601151}
0.0021	1586.0	106262	4.0294	{'f1': 0.8098974049487024}	{'accuracy': 0.697986577181208}
0.0021	1587.0	106329	4.1821	{'f1': 0.7855297157622738}	{'accuracy': 0.6816874400767018}
0.0021	1588.0	106396	4.1093	{'f1': 0.7920298879202988}	{'accuracy': 0.6797698945349953}
0.0021	1589.0	106463	4.0642	{'f1': 0.8004910988336403}	{'accuracy': 0.6883988494726749}
0.0022	1590.0	106530	4.1014	{'f1': 0.8002458512599877}	{'accuracy': 0.6883988494726749}
0.0022	1591.0	106597	4.1137	{'f1': 0.8002458512599877}	{'accuracy': 0.6883988494726749}
0.0022	1592.0	106664	4.1217	{'f1': 0.8002466091245377}	{'accuracy': 0.6893576222435283}
0.0022	1593.0	106731	4.1343	{'f1': 0.8002466091245377}	{'accuracy': 0.6893576222435283}
0.0022	1594.0	106798	3.8850	{'f1': 0.788896061975468}	{'accuracy': 0.6864813039309684}
0.0022	1595.0	106865	4.0425	{'f1': 0.7970660146699265}	{'accuracy': 0.6816874400767018}
0.0022	1596.0	106932	4.0677	{'f1': 0.7968078575813382}	{'accuracy': 0.6826462128475551}
0.0022	1597.0	106999	4.0900	{'f1': 0.7990105132962277}	{'accuracy': 0.6883988494726749}
0.0012	1598.0	107066	4.1110	{'f1': 0.7967781908302354}	{'accuracy': 0.6855225311601151}
0.0012	1599.0	107133	4.1241	{'f1': 0.7967781908302354}	{'accuracy': 0.6855225311601151}
0.0012	1600.0	107200	4.1416	{'f1': 0.7965260545905707}	{'accuracy': 0.6855225311601151}
0.0012	1601.0	107267	4.1563	{'f1': 0.796273291925466}	{'accuracy': 0.6855225311601151}
0.0012	1602.0	107334	4.1722	{'f1': 0.7970204841713222}	{'accuracy': 0.6864813039309684}
0.0012	1603.0	107401	4.1870	{'f1': 0.7975155279503106}	{'accuracy': 0.6874400767018217}
0.0012	1604.0	107468	4.2041	{'f1': 0.7970204841713222}	{'accuracy': 0.6864813039309684}
0.0	1605.0	107535	4.2186	{'f1': 0.7975155279503106}	{'accuracy': 0.6874400767018217}
0.0	1606.0	107602	3.8197	{'f1': 0.7879564381806533}	{'accuracy': 0.6826462128475551}
0.0	1607.0	107669	3.9413	{'f1': 0.7885350318471337}	{'accuracy': 0.6816874400767018}
0.0	1608.0	107736	4.0083	{'f1': 0.7918781725888324}	{'accuracy': 0.6855225311601151}
0.0	1609.0	107803	4.0489	{'f1': 0.7936908517350159}	{'accuracy': 0.6864813039309684}
0.0	1610.0	107870	4.0726	{'f1': 0.7949685534591195}	{'accuracy': 0.6874400767018217}
0.0	1611.0	107937	4.1010	{'f1': 0.794451450189155}	{'accuracy': 0.6874400767018217}
0.0009	1612.0	108004	4.1190	{'f1': 0.7936908517350159}	{'accuracy': 0.6864813039309684}
0.0009	1613.0	108071	4.1431	{'f1': 0.794451450189155}	{'accuracy': 0.6874400767018217}
0.0009	1614.0	108138	4.1575	{'f1': 0.7962264150943396}	{'accuracy': 0.6893576222435283}
0.0009	1615.0	108205	3.1793	{'f1': 0.7915601023017901}	{'accuracy': 0.6874400767018217}
0.0009	1616.0	108272	3.1908	{'f1': 0.7969348659003831}	{'accuracy': 0.6951102588686481}
0.0009	1617.0	108339	3.4530	{'f1': 0.7982176957352005}	{'accuracy': 0.6960690316395014}
0.0009	1618.0	108406	3.6305	{'f1': 0.7972465581977473}	{'accuracy': 0.6893576222435283}
0.0009	1619.0	108473	3.7223	{'f1': 0.8017294626312539}	{'accuracy': 0.6922339405560882}
0.0039	1620.0	108540	3.7554	{'f1': 0.7987460815047022}	{'accuracy': 0.6922339405560882}
0.0039	1621.0	108607	3.7986	{'f1': 0.7987421383647799}	{'accuracy': 0.6931927133269415}
0.0039	1622.0	108674	3.8255	{'f1': 0.7979861548143485}	{'accuracy': 0.6922339405560882}
0.0039	1623.0	108741	3.8519	{'f1': 0.8}	{'accuracy': 0.6970278044103547}
0.0039	1624.0	108808	3.9522	{'f1': 0.8007425742574258}	{'accuracy': 0.6912751677852349}
0.0039	1625.0	108875	4.0400	{'f1': 0.8017135862913096}	{'accuracy': 0.6893576222435283}
0.0039	1626.0	108942	4.0046	{'f1': 0.8007542426147077}	{'accuracy': 0.6960690316395014}
0.0007	1627.0	109009	4.0444	{'f1': 0.7987500000000002}	{'accuracy': 0.6912751677852349}
0.0007	1628.0	109076	4.0479	{'f1': 0.7989949748743719}	{'accuracy': 0.6931927133269415}
0.0007	1629.0	109143	4.0185	{'f1': 0.7808764940239044}	{'accuracy': 0.6836049856184084}
0.0007	1630.0	109210	4.0807	{'f1': 0.7735849056603774}	{'accuracy': 0.6778523489932886}
0.0007	1631.0	109277	4.0875	{'f1': 0.7811671087533156}	{'accuracy': 0.6836049856184084}
0.0007	1632.0	109344	4.0152	{'f1': 0.8002496878901374}	{'accuracy': 0.6931927133269415}
0.0007	1633.0	109411	4.0305	{'f1': 0.7969639468690701}	{'accuracy': 0.6922339405560882}
0.0007	1634.0	109478	4.0407	{'f1': 0.7969639468690701}	{'accuracy': 0.6922339405560882}
0.0008	1635.0	109545	4.2311	{'f1': 0.8021978021978021}	{'accuracy': 0.6893576222435283}
0.0008	1636.0	109612	4.2416	{'f1': 0.8009797917942437}	{'accuracy': 0.6883988494726749}
0.0008	1637.0	109679	3.9004	{'f1': 0.7959053103007038}	{'accuracy': 0.6941514860977949}
0.0008	1638.0	109746	3.9997	{'f1': 0.7989918084436043}	{'accuracy': 0.6941514860977949}
0.0008	1639.0	109813	4.0388	{'f1': 0.8002496878901374}	{'accuracy': 0.6931927133269415}
0.0008	1640.0	109880	4.0510	{'f1': 0.8002496878901374}	{'accuracy': 0.6931927133269415}
0.0008	1641.0	109947	4.0671	{'f1': 0.8002496878901374}	{'accuracy': 0.6931927133269415}
0.001	1642.0	110014	4.0815	{'f1': 0.8002496878901374}	{'accuracy': 0.6931927133269415}
0.001	1643.0	110081	4.1041	{'f1': 0.802252816020025}	{'accuracy': 0.6970278044103547}
0.001	1644.0	110148	4.0852	{'f1': 0.778585591539987}	{'accuracy': 0.6788111217641419}
0.001	1645.0	110215	4.1923	{'f1': 0.7933461292386437}	{'accuracy': 0.6903163950143816}
0.001	1646.0	110282	3.5644	{'f1': 0.7862156987874921}	{'accuracy': 0.6788111217641419}
0.001	1647.0	110349	3.7453	{'f1': 0.800497203231821}	{'accuracy': 0.6922339405560882}
0.001	1648.0	110416	3.7919	{'f1': 0.7990043559427504}	{'accuracy': 0.6903163950143816}
0.001	1649.0	110483	3.8302	{'f1': 0.7990043559427504}	{'accuracy': 0.6903163950143816}
0.002	1650.0	110550	3.8901	{'f1': 0.7932118164676305}	{'accuracy': 0.6845637583892618}
0.002	1651.0	110617	3.9527	{'f1': 0.7942283563362609}	{'accuracy': 0.6855225311601151}
0.002	1652.0	110684	3.9801	{'f1': 0.7942283563362609}	{'accuracy': 0.6855225311601151}
0.002	1653.0	110751	4.0161	{'f1': 0.7949843260188089}	{'accuracy': 0.6864813039309684}
0.002	1654.0	110818	4.0293	{'f1': 0.7957393483709274}	{'accuracy': 0.6874400767018217}
0.002	1655.0	110885	4.0505	{'f1': 0.7921667719519899}	{'accuracy': 0.6845637583892618}
0.002	1656.0	110952	4.0706	{'f1': 0.7911111111111112}	{'accuracy': 0.6845637583892618}
0.0003	1657.0	111019	4.1681	{'f1': 0.8021911138161899}	{'accuracy': 0.6883988494726749}
0.0003	1658.0	111086	4.2152	{'f1': 0.8007334963325183}	{'accuracy': 0.6874400767018217}
0.0003	1659.0	111153	4.2482	{'f1': 0.8007334963325183}	{'accuracy': 0.6874400767018217}
0.0003	1660.0	111220	4.2729	{'f1': 0.7995079950799507}	{'accuracy': 0.6874400767018217}
0.0003	1661.0	111287	4.2937	{'f1': 0.7970297029702972}	{'accuracy': 0.6855225311601151}
0.0003	1662.0	111354	4.1520	{'f1': 0.7900128040973112}	{'accuracy': 0.6855225311601151}
0.0003	1663.0	111421	4.1884	{'f1': 0.791025641025641}	{'accuracy': 0.6874400767018217}
0.0003	1664.0	111488	4.2273	{'f1': 0.7933673469387755}	{'accuracy': 0.6893576222435283}
0.0005	1665.0	111555	4.2483	{'f1': 0.7969543147208121}	{'accuracy': 0.6931927133269415}
0.0005	1666.0	111622	4.2647	{'f1': 0.7964489537095751}	{'accuracy': 0.6922339405560882}
0.0005	1667.0	111689	4.3076	{'f1': 0.7979797979797981}	{'accuracy': 0.6931927133269415}
0.0005	1668.0	111756	4.3231	{'f1': 0.7974763406940064}	{'accuracy': 0.6922339405560882}
0.0005	1669.0	111823	4.4933	{'f1': 0.8014842300556587}	{'accuracy': 0.6922339405560882}
0.0005	1670.0	111890	4.5103	{'f1': 0.8014842300556587}	{'accuracy': 0.6922339405560882}
0.0005	1671.0	111957	4.5242	{'f1': 0.8014842300556587}	{'accuracy': 0.6922339405560882}
0.0	1672.0	112024	4.6731	{'f1': 0.8120924718435093}	{'accuracy': 0.6960690316395014}
0.0	1673.0	112091	3.9627	{'f1': 0.7881519639407599}	{'accuracy': 0.6845637583892618}
0.0	1674.0	112158	4.0934	{'f1': 0.7830065359477124}	{'accuracy': 0.6816874400767018}
0.0	1675.0	112225	4.1837	{'f1': 0.780392156862745}	{'accuracy': 0.6778523489932886}
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0.0006	1841.0	123347	4.7601	{'f1': 0.7997512437810945}	{'accuracy': 0.6912751677852349}
0.0006	1842.0	123414	4.6926	{'f1': 0.7989821882951653}	{'accuracy': 0.6970278044103547}
0.0006	1843.0	123481	4.7036	{'f1': 0.7992376111817027}	{'accuracy': 0.6970278044103547}
0.0006	1844.0	123548	4.7190	{'f1': 0.7979734008866372}	{'accuracy': 0.6941514860977949}
0.0006	1845.0	123615	4.7204	{'f1': 0.7982289690069577}	{'accuracy': 0.6941514860977949}
0.0006	1846.0	123682	4.8204	{'f1': 0.8017031630170317}	{'accuracy': 0.6874400767018217}
0.0006	1847.0	123749	4.8245	{'f1': 0.8017031630170317}	{'accuracy': 0.6874400767018217}
0.0006	1848.0	123816	4.8301	{'f1': 0.8014616321559075}	{'accuracy': 0.6874400767018217}
0.0006	1849.0	123883	4.8336	{'f1': 0.8014616321559075}	{'accuracy': 0.6874400767018217}
0.0006	1850.0	123950	4.7868	{'f1': 0.798261949099938}	{'accuracy': 0.6883988494726749}
0.0006	1851.0	124017	4.7720	{'f1': 0.7975077881619936}	{'accuracy': 0.6883988494726749}
0.0006	1852.0	124084	4.7746	{'f1': 0.7975077881619936}	{'accuracy': 0.6883988494726749}
0.0006	1853.0	124151	4.7768	{'f1': 0.7975077881619936}	{'accuracy': 0.6883988494726749}
0.0006	1854.0	124218	4.6521	{'f1': 0.7944162436548224}	{'accuracy': 0.6893576222435283}
0.0006	1855.0	124285	4.5963	{'f1': 0.7931034482758621}	{'accuracy': 0.6893576222435283}
0.0006	1856.0	124352	4.5755	{'f1': 0.8017241379310345}	{'accuracy': 0.6912751677852349}
0.0006	1857.0	124419	4.5805	{'f1': 0.8007402837754474}	{'accuracy': 0.6903163950143816}
0.0006	1858.0	124486	4.5869	{'f1': 0.8007402837754474}	{'accuracy': 0.6903163950143816}
0.0018	1859.0	124553	4.5948	{'f1': 0.8007402837754474}	{'accuracy': 0.6903163950143816}
0.0018	1860.0	124620	4.5946	{'f1': 0.8002481389578164}	{'accuracy': 0.6912751677852349}
0.0018	1861.0	124687	4.5962	{'f1': 0.7999999999999999}	{'accuracy': 0.6922339405560882}
0.0018	1862.0	124754	4.6003	{'f1': 0.7999999999999999}	{'accuracy': 0.6922339405560882}
0.0018	1863.0	124821	4.6047	{'f1': 0.7999999999999999}	{'accuracy': 0.6922339405560882}
0.0018	1864.0	124888	4.6092	{'f1': 0.7999999999999999}	{'accuracy': 0.6922339405560882}
0.0018	1865.0	124955	4.6142	{'f1': 0.7999999999999999}	{'accuracy': 0.6922339405560882}
0.0001	1866.0	125022	4.6254	{'f1': 0.7999999999999999}	{'accuracy': 0.6922339405560882}
0.0001	1867.0	125089	4.6366	{'f1': 0.7999999999999999}	{'accuracy': 0.6922339405560882}
0.0001	1868.0	125156	4.6408	{'f1': 0.7999999999999999}	{'accuracy': 0.6922339405560882}
0.0001	1869.0	125223	4.6449	{'f1': 0.7999999999999999}	{'accuracy': 0.6922339405560882}
0.0001	1870.0	125290	4.6498	{'f1': 0.7999999999999999}	{'accuracy': 0.6922339405560882}
0.0001	1871.0	125357	4.6553	{'f1': 0.7999999999999999}	{'accuracy': 0.6922339405560882}
0.0001	1872.0	125424	4.6598	{'f1': 0.7999999999999999}	{'accuracy': 0.6922339405560882}
0.0001	1873.0	125491	4.6642	{'f1': 0.7999999999999999}	{'accuracy': 0.6922339405560882}
0.0	1874.0	125558	4.6686	{'f1': 0.7999999999999999}	{'accuracy': 0.6922339405560882}
0.0	1875.0	125625	4.6729	{'f1': 0.7999999999999999}	{'accuracy': 0.6922339405560882}
0.0	1876.0	125692	4.6783	{'f1': 0.7999999999999999}	{'accuracy': 0.6922339405560882}
0.0	1877.0	125759	4.6849	{'f1': 0.7999999999999999}	{'accuracy': 0.6922339405560882}
0.0	1878.0	125826	4.6888	{'f1': 0.7999999999999999}	{'accuracy': 0.6922339405560882}
0.0	1879.0	125893	4.6877	{'f1': 0.7946428571428571}	{'accuracy': 0.6912751677852349}
0.0	1880.0	125960	4.6872	{'f1': 0.7946428571428571}	{'accuracy': 0.6912751677852349}
0.0	1881.0	126027	4.6923	{'f1': 0.7946428571428571}	{'accuracy': 0.6912751677852349}
0.0	1882.0	126094	4.6982	{'f1': 0.7946428571428571}	{'accuracy': 0.6912751677852349}
0.0	1883.0	126161	4.7022	{'f1': 0.7946428571428571}	{'accuracy': 0.6912751677852349}
0.0	1884.0	126228	4.7074	{'f1': 0.7946428571428571}	{'accuracy': 0.6912751677852349}
0.0	1885.0	126295	4.7128	{'f1': 0.7946428571428571}	{'accuracy': 0.6912751677852349}
0.0	1886.0	126362	4.7175	{'f1': 0.7946428571428571}	{'accuracy': 0.6912751677852349}
0.0	1887.0	126429	4.7244	{'f1': 0.7946428571428571}	{'accuracy': 0.6912751677852349}
0.0	1888.0	126496	4.7505	{'f1': 0.7956715467854869}	{'accuracy': 0.6922339405560882}
0.0	1889.0	126563	4.7559	{'f1': 0.7956715467854869}	{'accuracy': 0.6922339405560882}
0.0	1890.0	126630	4.7650	{'f1': 0.7956715467854869}	{'accuracy': 0.6922339405560882}
0.0	1891.0	126697	4.7739	{'f1': 0.7956715467854869}	{'accuracy': 0.6922339405560882}
0.0	1892.0	126764	4.7773	{'f1': 0.7956715467854869}	{'accuracy': 0.6922339405560882}
0.0	1893.0	126831	4.7800	{'f1': 0.7956715467854869}	{'accuracy': 0.6922339405560882}
0.0	1894.0	126898	4.7842	{'f1': 0.7956715467854869}	{'accuracy': 0.6922339405560882}
0.0	1895.0	126965	4.7866	{'f1': 0.7956715467854869}	{'accuracy': 0.6922339405560882}
0.0	1896.0	127032	4.7890	{'f1': 0.7956715467854869}	{'accuracy': 0.6922339405560882}
0.0	1897.0	127099	4.8025	{'f1': 0.7956715467854869}	{'accuracy': 0.6922339405560882}
0.0	1898.0	127166	4.8056	{'f1': 0.7956715467854869}	{'accuracy': 0.6922339405560882}
0.0	1899.0	127233	4.8082	{'f1': 0.7956715467854869}	{'accuracy': 0.6922339405560882}
0.0	1900.0	127300	4.8109	{'f1': 0.7956715467854869}	{'accuracy': 0.6922339405560882}
0.0	1901.0	127367	4.8284	{'f1': 0.7972027972027972}	{'accuracy': 0.6941514860977949}
0.0	1902.0	127434	4.8315	{'f1': 0.7972027972027972}	{'accuracy': 0.6941514860977949}
0.0011	1903.0	127501	4.6853	{'f1': 0.7997520148791073}	{'accuracy': 0.6903163950143816}
0.0011	1904.0	127568	4.7537	{'f1': 0.8014796547472257}	{'accuracy': 0.6912751677852349}
0.0011	1905.0	127635	4.7589	{'f1': 0.8017241379310345}	{'accuracy': 0.6912751677852349}
0.0011	1906.0	127702	4.7685	{'f1': 0.8014796547472257}	{'accuracy': 0.6912751677852349}
0.0011	1907.0	127769	4.7712	{'f1': 0.8014796547472257}	{'accuracy': 0.6912751677852349}
0.0011	1908.0	127836	4.7751	{'f1': 0.8014796547472257}	{'accuracy': 0.6912751677852349}
0.0011	1909.0	127903	4.7726	{'f1': 0.8014796547472257}	{'accuracy': 0.6912751677852349}
0.0011	1910.0	127970	4.7092	{'f1': 0.8004987531172071}	{'accuracy': 0.6931927133269415}
0.0	1911.0	128037	4.7111	{'f1': 0.8004987531172071}	{'accuracy': 0.6931927133269415}
0.0	1912.0	128104	4.7130	{'f1': 0.8004987531172071}	{'accuracy': 0.6931927133269415}
0.0	1913.0	128171	4.7146	{'f1': 0.8004987531172071}	{'accuracy': 0.6931927133269415}
0.0	1914.0	128238	4.7179	{'f1': 0.8004987531172071}	{'accuracy': 0.6931927133269415}
0.0	1915.0	128305	4.2913	{'f1': 0.8017565872020074}	{'accuracy': 0.6970278044103547}
0.0	1916.0	128372	4.2390	{'f1': 0.8022598870056498}	{'accuracy': 0.697986577181208}
0.0	1917.0	128439	4.2404	{'f1': 0.8027638190954774}	{'accuracy': 0.6989453499520614}
0.0021	1918.0	128506	4.2473	{'f1': 0.7989886219974714}	{'accuracy': 0.6951102588686481}
0.0021	1919.0	128573	4.2483	{'f1': 0.7946257197696738}	{'accuracy': 0.6922339405560882}
0.0021	1920.0	128640	4.2498	{'f1': 0.7946257197696738}	{'accuracy': 0.6922339405560882}
0.0021	1921.0	128707	4.2520	{'f1': 0.7946257197696738}	{'accuracy': 0.6922339405560882}
0.0021	1922.0	128774	4.2534	{'f1': 0.7946257197696738}	{'accuracy': 0.6922339405560882}
0.0021	1923.0	128841	4.2570	{'f1': 0.7953964194373401}	{'accuracy': 0.6931927133269415}
0.0021	1924.0	128908	4.2587	{'f1': 0.7953964194373401}	{'accuracy': 0.6931927133269415}
0.0021	1925.0	128975	4.2603	{'f1': 0.7948881789137379}	{'accuracy': 0.6922339405560882}
0.0	1926.0	129042	4.2616	{'f1': 0.7948881789137379}	{'accuracy': 0.6922339405560882}
0.0	1927.0	129109	4.2935	{'f1': 0.8010043942247331}	{'accuracy': 0.6960690316395014}
0.0	1928.0	129176	4.3010	{'f1': 0.8010043942247331}	{'accuracy': 0.6960690316395014}
0.0	1929.0	129243	4.3028	{'f1': 0.8010043942247331}	{'accuracy': 0.6960690316395014}
0.0	1930.0	129310	4.3041	{'f1': 0.8010043942247331}	{'accuracy': 0.6960690316395014}
0.0	1931.0	129377	4.3057	{'f1': 0.8010043942247331}	{'accuracy': 0.6960690316395014}
0.0	1932.0	129444	4.3070	{'f1': 0.8010043942247331}	{'accuracy': 0.6960690316395014}
0.0	1933.0	129511	4.3084	{'f1': 0.8010043942247331}	{'accuracy': 0.6960690316395014}
0.0	1934.0	129578	4.3506	{'f1': 0.8014888337468983}	{'accuracy': 0.6931927133269415}
0.0	1935.0	129645	4.3537	{'f1': 0.8022318660880349}	{'accuracy': 0.6941514860977949}
0.0	1936.0	129712	4.3551	{'f1': 0.8022318660880349}	{'accuracy': 0.6941514860977949}
0.0	1937.0	129779	4.3653	{'f1': 0.802721088435374}	{'accuracy': 0.6941514860977949}
0.0	1938.0	129846	4.3667	{'f1': 0.802721088435374}	{'accuracy': 0.6941514860977949}
0.0	1939.0	129913	4.3682	{'f1': 0.802721088435374}	{'accuracy': 0.6941514860977949}
0.0	1940.0	129980	4.3697	{'f1': 0.802721088435374}	{'accuracy': 0.6941514860977949}
0.0001	1941.0	130047	4.3712	{'f1': 0.802721088435374}	{'accuracy': 0.6941514860977949}
0.0001	1942.0	130114	4.3729	{'f1': 0.802721088435374}	{'accuracy': 0.6941514860977949}
0.0001	1943.0	130181	4.3744	{'f1': 0.802721088435374}	{'accuracy': 0.6941514860977949}
0.0001	1944.0	130248	4.3757	{'f1': 0.802721088435374}	{'accuracy': 0.6941514860977949}
0.0001	1945.0	130315	4.3771	{'f1': 0.802721088435374}	{'accuracy': 0.6941514860977949}
0.0001	1946.0	130382	4.3786	{'f1': 0.802721088435374}	{'accuracy': 0.6941514860977949}
0.0001	1947.0	130449	4.3801	{'f1': 0.802721088435374}	{'accuracy': 0.6941514860977949}
0.0	1948.0	130516	4.3816	{'f1': 0.802721088435374}	{'accuracy': 0.6941514860977949}
0.0	1949.0	130583	4.3831	{'f1': 0.802721088435374}	{'accuracy': 0.6941514860977949}
0.0	1950.0	130650	4.3859	{'f1': 0.8012383900928793}	{'accuracy': 0.6922339405560882}
0.0	1951.0	130717	4.3872	{'f1': 0.8012383900928793}	{'accuracy': 0.6922339405560882}
0.0	1952.0	130784	4.3942	{'f1': 0.8044417026526834}	{'accuracy': 0.6960690316395014}
0.0	1953.0	130851	4.4247	{'f1': 0.8065893837705919}	{'accuracy': 0.6960690316395014}
0.0	1954.0	130918	4.4262	{'f1': 0.8065893837705919}	{'accuracy': 0.6960690316395014}
0.0	1955.0	130985	4.4287	{'f1': 0.8051313378130727}	{'accuracy': 0.6941514860977949}
0.0	1956.0	131052	4.4302	{'f1': 0.8056234718826406}	{'accuracy': 0.6951102588686481}
0.0	1957.0	131119	4.4316	{'f1': 0.8056234718826406}	{'accuracy': 0.6951102588686481}
0.0	1958.0	131186	4.4339	{'f1': 0.8056234718826406}	{'accuracy': 0.6951102588686481}
0.0	1959.0	131253	4.4352	{'f1': 0.8056234718826406}	{'accuracy': 0.6951102588686481}
0.0	1960.0	131320	4.4367	{'f1': 0.8056234718826406}	{'accuracy': 0.6951102588686481}
0.0	1961.0	131387	4.4382	{'f1': 0.8056234718826406}	{'accuracy': 0.6951102588686481}
0.0	1962.0	131454	4.4398	{'f1': 0.8056234718826406}	{'accuracy': 0.6951102588686481}
0.0	1963.0	131521	4.4283	{'f1': 0.8034504004929144}	{'accuracy': 0.6941514860977949}
0.0	1964.0	131588	4.3914	{'f1': 0.8029739776951673}	{'accuracy': 0.6951102588686481}
0.0	1965.0	131655	4.3890	{'f1': 0.8029739776951673}	{'accuracy': 0.6951102588686481}
0.0	1966.0	131722	4.3900	{'f1': 0.8029739776951673}	{'accuracy': 0.6951102588686481}
0.0	1967.0	131789	4.3909	{'f1': 0.8029739776951673}	{'accuracy': 0.6951102588686481}
0.0	1968.0	131856	4.3922	{'f1': 0.8029739776951673}	{'accuracy': 0.6951102588686481}
0.0	1969.0	131923	4.3933	{'f1': 0.8029739776951673}	{'accuracy': 0.6951102588686481}
0.0	1970.0	131990	4.3942	{'f1': 0.8029739776951673}	{'accuracy': 0.6951102588686481}
0.0003	1971.0	132057	4.3952	{'f1': 0.8029739776951673}	{'accuracy': 0.6951102588686481}
0.0003	1972.0	132124	4.3966	{'f1': 0.8029739776951673}	{'accuracy': 0.6951102588686481}
0.0003	1973.0	132191	4.3978	{'f1': 0.8029739776951673}	{'accuracy': 0.6951102588686481}
0.0003	1974.0	132258	4.3988	{'f1': 0.8029739776951673}	{'accuracy': 0.6951102588686481}
0.0003	1975.0	132325	4.3998	{'f1': 0.8022318660880349}	{'accuracy': 0.6941514860977949}
0.0003	1976.0	132392	4.4105	{'f1': 0.8029739776951673}	{'accuracy': 0.6951102588686481}
0.0003	1977.0	132459	4.4185	{'f1': 0.8029739776951673}	{'accuracy': 0.6951102588686481}
0.0	1978.0	132526	4.4202	{'f1': 0.8029739776951673}	{'accuracy': 0.6951102588686481}
0.0	1979.0	132593	4.4210	{'f1': 0.8029739776951673}	{'accuracy': 0.6951102588686481}
0.0	1980.0	132660	4.4217	{'f1': 0.8029739776951673}	{'accuracy': 0.6951102588686481}
0.0	1981.0	132727	4.4224	{'f1': 0.8029739776951673}	{'accuracy': 0.6951102588686481}
0.0	1982.0	132794	4.4028	{'f1': 0.8034825870646766}	{'accuracy': 0.6970278044103547}
0.0	1983.0	132861	4.4034	{'f1': 0.8034825870646766}	{'accuracy': 0.6970278044103547}
0.0	1984.0	132928	4.4041	{'f1': 0.8034825870646766}	{'accuracy': 0.6970278044103547}
0.0	1985.0	132995	4.4046	{'f1': 0.8034825870646766}	{'accuracy': 0.6970278044103547}
0.0003	1986.0	133062	4.3821	{'f1': 0.8044831880448319}	{'accuracy': 0.6989453499520614}
0.0003	1987.0	133129	4.3550	{'f1': 0.8049844236760124}	{'accuracy': 0.6999041227229147}
0.0003	1988.0	133196	4.3580	{'f1': 0.8044831880448319}	{'accuracy': 0.6989453499520614}
0.0003	1989.0	133263	4.3584	{'f1': 0.8044831880448319}	{'accuracy': 0.6989453499520614}
0.0003	1990.0	133330	4.3589	{'f1': 0.8044831880448319}	{'accuracy': 0.6989453499520614}
0.0003	1991.0	133397	4.3592	{'f1': 0.8044831880448319}	{'accuracy': 0.6989453499520614}
0.0003	1992.0	133464	4.3594	{'f1': 0.8044831880448319}	{'accuracy': 0.6989453499520614}
0.0015	1993.0	133531	4.3597	{'f1': 0.8044831880448319}	{'accuracy': 0.6989453499520614}
0.0015	1994.0	133598	4.3599	{'f1': 0.8044831880448319}	{'accuracy': 0.6989453499520614}
0.0015	1995.0	133665	4.3601	{'f1': 0.8044831880448319}	{'accuracy': 0.6989453499520614}
0.0015	1996.0	133732	4.3603	{'f1': 0.8044831880448319}	{'accuracy': 0.6989453499520614}
0.0015	1997.0	133799	4.3604	{'f1': 0.8044831880448319}	{'accuracy': 0.6989453499520614}
0.0015	1998.0	133866	4.3605	{'f1': 0.8044831880448319}	{'accuracy': 0.6989453499520614}
0.0015	1999.0	133933	4.3588	{'f1': 0.8042394014962594}	{'accuracy': 0.6989453499520614}
0.0	2000.0	134000	4.3588	{'f1': 0.8042394014962594}	{'accuracy': 0.6989453499520614}

Framework versions

• Transformers 4.29.2
• Pytorch 2.0.1+cu117
• Datasets 2.12.0
• Tokenizers 0.13.3