pytorch generated_from_trainer license:apache-2.0 region:us
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: bert-base-uncased-test_2_100
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# bert-base-uncased-test_2_100

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3742
- F1: {'f1': 0.8207293666026871}
- Accuracy: {'accuracy': 0.8132}

## 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: 0.0001
- 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: 500

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1                          | Accuracy             |
|:-------------:|:-----:|:----:|:---------------:|:---------------------------:|:--------------------:|
| No log        | 1.0   | 7    | 0.6867          | {'f1': 0.6673895364597453}  | {'accuracy': 0.5092} |
| No log        | 2.0   | 14   | 0.6819          | {'f1': 0.5501760563380282}  | {'accuracy': 0.5912} |
| No log        | 3.0   | 21   | 0.6808          | {'f1': 0.37319468515309073} | {'accuracy': 0.566}  |
| No log        | 4.0   | 28   | 0.6778          | {'f1': 0.3979706877113867}  | {'accuracy': 0.5728} |
| No log        | 5.0   | 35   | 0.6748          | {'f1': 0.432258064516129}   | {'accuracy': 0.5776} |
| No log        | 6.0   | 42   | 0.6702          | {'f1': 0.5789250952179433}  | {'accuracy': 0.602}  |
| No log        | 7.0   | 49   | 0.6664          | {'f1': 0.5185891325071497}  | {'accuracy': 0.596}  |
| No log        | 8.0   | 56   | 0.6615          | {'f1': 0.5394378966455122}  | {'accuracy': 0.5936} |
| No log        | 9.0   | 63   | 0.6583          | {'f1': 0.5796124684077507}  | {'accuracy': 0.6008} |
| No log        | 10.0  | 70   | 0.6547          | {'f1': 0.628030303030303}   | {'accuracy': 0.6072} |
| No log        | 11.0  | 77   | 0.6429          | {'f1': 0.555812876331635}   | {'accuracy': 0.6164} |
| No log        | 12.0  | 84   | 0.6200          | {'f1': 0.6544731610337972}  | {'accuracy': 0.6524} |
| No log        | 13.0  | 91   | 0.6054          | {'f1': 0.6861480075901328}  | {'accuracy': 0.6692} |
| No log        | 14.0  | 98   | 0.5944          | {'f1': 0.6591107236268527}  | {'accuracy': 0.6872} |
| No log        | 15.0  | 105  | 0.5802          | {'f1': 0.6939109113199837}  | {'accuracy': 0.7004} |
| No log        | 16.0  | 112  | 0.5801          | {'f1': 0.7122069523039612}  | {'accuracy': 0.7152} |
| No log        | 17.0  | 119  | 0.5862          | {'f1': 0.7172413793103448}  | {'accuracy': 0.7212} |
| No log        | 18.0  | 126  | 0.6508          | {'f1': 0.7453769559032717}  | {'accuracy': 0.7136} |
| No log        | 19.0  | 133  | 0.5935          | {'f1': 0.7325581395348837}  | {'accuracy': 0.7424} |
| No log        | 20.0  | 140  | 0.6193          | {'f1': 0.7265029635901777}  | {'accuracy': 0.7416} |
| No log        | 21.0  | 147  | 0.6967          | {'f1': 0.7574221578566257}  | {'accuracy': 0.732}  |
| No log        | 22.0  | 154  | 0.6781          | {'f1': 0.7065267001369236}  | {'accuracy': 0.7428} |
| No log        | 23.0  | 161  | 0.6566          | {'f1': 0.7692898272552784}  | {'accuracy': 0.7596} |
| No log        | 24.0  | 168  | 0.6656          | {'f1': 0.7717265353418308}  | {'accuracy': 0.7636} |
| No log        | 25.0  | 175  | 0.6746          | {'f1': 0.7662650602409639}  | {'accuracy': 0.7672} |
| No log        | 26.0  | 182  | 0.7001          | {'f1': 0.7759433962264151}  | {'accuracy': 0.772}  |
| No log        | 27.0  | 189  | 0.7292          | {'f1': 0.7441063009001286}  | {'accuracy': 0.7612} |
| No log        | 28.0  | 196  | 0.7418          | {'f1': 0.7610474631751227}  | {'accuracy': 0.7664} |
| No log        | 29.0  | 203  | 0.7614          | {'f1': 0.751592356687898}   | {'accuracy': 0.766}  |
| No log        | 30.0  | 210  | 0.7697          | {'f1': 0.7806022682831443}  | {'accuracy': 0.7756} |
| No log        | 31.0  | 217  | 0.7885          | {'f1': 0.7721265518622348}  | {'accuracy': 0.7724} |
| No log        | 32.0  | 224  | 0.8062          | {'f1': 0.7642209398186316}  | {'accuracy': 0.7712} |
| No log        | 33.0  | 231  | 0.8301          | {'f1': 0.7805456702253853}  | {'accuracy': 0.778}  |
| No log        | 34.0  | 238  | 0.8503          | {'f1': 0.7807570977917981}  | {'accuracy': 0.7776} |
| No log        | 35.0  | 245  | 0.9258          | {'f1': 0.7845180498697432}  | {'accuracy': 0.7684} |
| No log        | 36.0  | 252  | 0.9121          | {'f1': 0.7879472693032015}  | {'accuracy': 0.7748} |
| No log        | 37.0  | 259  | 0.8719          | {'f1': 0.7829238824003222}  | {'accuracy': 0.7844} |
| No log        | 38.0  | 266  | 0.9147          | {'f1': 0.7897748950782144}  | {'accuracy': 0.7796} |
| No log        | 39.0  | 273  | 0.8983          | {'f1': 0.7862013638186923}  | {'accuracy': 0.7868} |
| No log        | 40.0  | 280  | 0.9294          | {'f1': 0.7913779830638953}  | {'accuracy': 0.7832} |
| No log        | 41.0  | 287  | 0.9203          | {'f1': 0.7841269841269841}  | {'accuracy': 0.7824} |
| No log        | 42.0  | 294  | 0.9434          | {'f1': 0.7949405902644691}  | {'accuracy': 0.786}  |
| No log        | 43.0  | 301  | 0.9415          | {'f1': 0.7944465869649053}  | {'accuracy': 0.7868} |
| No log        | 44.0  | 308  | 0.9479          | {'f1': 0.770859805167302}   | {'accuracy': 0.7836} |
| No log        | 45.0  | 315  | 0.9805          | {'f1': 0.7955927051671733}  | {'accuracy': 0.7848} |
| No log        | 46.0  | 322  | 0.9753          | {'f1': 0.788184998056743}   | {'accuracy': 0.782}  |
| No log        | 47.0  | 329  | 0.9732          | {'f1': 0.7798537774167345}  | {'accuracy': 0.7832} |
| No log        | 48.0  | 336  | 1.0218          | {'f1': 0.7910163684811572}  | {'accuracy': 0.7804} |
| No log        | 49.0  | 343  | 1.0071          | {'f1': 0.7824056052938886}  | {'accuracy': 0.7764} |
| No log        | 50.0  | 350  | 0.9941          | {'f1': 0.7769962763756723}  | {'accuracy': 0.7844} |
| No log        | 51.0  | 357  | 1.1072          | {'f1': 0.7849580138736765}  | {'accuracy': 0.7644} |
| No log        | 52.0  | 364  | 1.0659          | {'f1': 0.7905048982667672}  | {'accuracy': 0.7776} |
| No log        | 53.0  | 371  | 1.0176          | {'f1': 0.7758268681094325}  | {'accuracy': 0.7804} |
| No log        | 54.0  | 378  | 1.0482          | {'f1': 0.7857695282289249}  | {'accuracy': 0.7784} |
| No log        | 55.0  | 385  | 1.2158          | {'f1': 0.784452296819788}   | {'accuracy': 0.756}  |
| No log        | 56.0  | 392  | 1.1118          | {'f1': 0.7880575009214891}  | {'accuracy': 0.77}   |
| No log        | 57.0  | 399  | 1.0318          | {'f1': 0.7878308968787041}  | {'accuracy': 0.7852} |
| No log        | 58.0  | 406  | 1.0296          | {'f1': 0.7861178369652946}  | {'accuracy': 0.788}  |
| No log        | 59.0  | 413  | 1.1107          | {'f1': 0.7899034892353377}  | {'accuracy': 0.7736} |
| No log        | 60.0  | 420  | 1.0667          | {'f1': 0.791124713083397}   | {'accuracy': 0.7816} |
| No log        | 61.0  | 427  | 1.0478          | {'f1': 0.7916666666666666}  | {'accuracy': 0.788}  |
| No log        | 62.0  | 434  | 1.0506          | {'f1': 0.7908625443087829}  | {'accuracy': 0.7876} |
| No log        | 63.0  | 441  | 1.0569          | {'f1': 0.7927786499215072}  | {'accuracy': 0.7888} |
| No log        | 64.0  | 448  | 1.0732          | {'f1': 0.7882534775888718}  | {'accuracy': 0.7808} |
| No log        | 65.0  | 455  | 1.0744          | {'f1': 0.7902287708414115}  | {'accuracy': 0.7836} |
| No log        | 66.0  | 462  | 1.0650          | {'f1': 0.7919463087248323}  | {'accuracy': 0.7892} |
| No log        | 67.0  | 469  | 1.1210          | {'f1': 0.7916981132075471}  | {'accuracy': 0.7792} |
| No log        | 68.0  | 476  | 1.0886          | {'f1': 0.7925552539744086}  | {'accuracy': 0.786}  |
| No log        | 69.0  | 483  | 1.0712          | {'f1': 0.7895372233400404}  | {'accuracy': 0.7908} |
| No log        | 70.0  | 490  | 1.0749          | {'f1': 0.7860897695107156}  | {'accuracy': 0.7884} |
| No log        | 71.0  | 497  | 1.0807          | {'f1': 0.7931446791550419}  | {'accuracy': 0.7924} |
| 0.1431        | 72.0  | 504  | 1.0837          | {'f1': 0.7931446791550419}  | {'accuracy': 0.7924} |
| 0.1431        | 73.0  | 511  | 1.0897          | {'f1': 0.7936758893280632}  | {'accuracy': 0.7912} |
| 0.1431        | 74.0  | 518  | 1.0925          | {'f1': 0.7952755905511811}  | {'accuracy': 0.792}  |
| 0.1431        | 75.0  | 525  | 1.1018          | {'f1': 0.7951713395638628}  | {'accuracy': 0.7896} |
| 0.1431        | 76.0  | 532  | 1.1121          | {'f1': 0.7938104448742745}  | {'accuracy': 0.7868} |
| 0.1431        | 77.0  | 539  | 1.1071          | {'f1': 0.7945631067961165}  | {'accuracy': 0.7884} |
| 0.1431        | 78.0  | 546  | 1.1149          | {'f1': 0.7944250871080138}  | {'accuracy': 0.7876} |
| 0.1431        | 79.0  | 553  | 1.1702          | {'f1': 0.7919312663429211}  | {'accuracy': 0.7772} |
| 0.1431        | 80.0  | 560  | 1.1048          | {'f1': 0.7970277669143527}  | {'accuracy': 0.7924} |
| 0.1431        | 81.0  | 567  | 1.0988          | {'f1': 0.7942583732057418}  | {'accuracy': 0.7936} |
| 0.1431        | 82.0  | 574  | 1.1094          | {'f1': 0.797141722905915}   | {'accuracy': 0.7956} |
| 0.1431        | 83.0  | 581  | 1.1293          | {'f1': 0.79408330089529}    | {'accuracy': 0.7884} |
| 0.1431        | 84.0  | 588  | 1.1591          | {'f1': 0.7948229920060906}  | {'accuracy': 0.7844} |
| 0.1431        | 85.0  | 595  | 1.1706          | {'f1': 0.7921241953805376}  | {'accuracy': 0.7804} |
| 0.1431        | 86.0  | 602  | 1.1557          | {'f1': 0.792467332820907}   | {'accuracy': 0.784}  |
| 0.1431        | 87.0  | 609  | 1.1554          | {'f1': 0.76732249786142}    | {'accuracy': 0.7824} |
| 0.1431        | 88.0  | 616  | 1.1516          | {'f1': 0.7946257197696737}  | {'accuracy': 0.786}  |
| 0.1431        | 89.0  | 623  | 1.2337          | {'f1': 0.7969208211143696}  | {'accuracy': 0.7784} |
| 0.1431        | 90.0  | 630  | 1.1372          | {'f1': 0.7978227060653188}  | {'accuracy': 0.792}  |
| 0.1431        | 91.0  | 637  | 1.1228          | {'f1': 0.7916833266693323}  | {'accuracy': 0.7916} |
| 0.1431        | 92.0  | 644  | 1.1289          | {'f1': 0.7952569169960475}  | {'accuracy': 0.7928} |
| 0.1431        | 93.0  | 651  | 1.1409          | {'f1': 0.7992187500000001}  | {'accuracy': 0.7944} |
| 0.1431        | 94.0  | 658  | 1.1469          | {'f1': 0.7989109295993777}  | {'accuracy': 0.7932} |
| 0.1431        | 95.0  | 665  | 1.2357          | {'f1': 0.7549019607843137}  | {'accuracy': 0.78}   |
| 0.1431        | 96.0  | 672  | 1.1278          | {'f1': 0.789664917238595}   | {'accuracy': 0.7916} |
| 0.1431        | 97.0  | 679  | 1.1492          | {'f1': 0.8013937282229966}  | {'accuracy': 0.7948} |
| 0.1431        | 98.0  | 686  | 1.1501          | {'f1': 0.7805486284289276}  | {'accuracy': 0.7888} |
| 0.1431        | 99.0  | 693  | 1.1785          | {'f1': 0.7683807904802381}  | {'accuracy': 0.782}  |
| 0.1431        | 100.0 | 700  | 1.1602          | {'f1': 0.7807708246995443}  | {'accuracy': 0.7884} |
| 0.1431        | 101.0 | 707  | 1.1585          | {'f1': 0.7963621984974298}  | {'accuracy': 0.794}  |
| 0.1431        | 102.0 | 714  | 1.2049          | {'f1': 0.7948523845571537}  | {'accuracy': 0.7832} |
| 0.1431        | 103.0 | 721  | 1.1969          | {'f1': 0.7960275019098548}  | {'accuracy': 0.7864} |
| 0.1431        | 104.0 | 728  | 1.1693          | {'f1': 0.7960552268244576}  | {'accuracy': 0.7932} |
| 0.1431        | 105.0 | 735  | 1.1664          | {'f1': 0.7934739355352168}  | {'accuracy': 0.7924} |
| 0.1431        | 106.0 | 742  | 1.1675          | {'f1': 0.7937898089171975}  | {'accuracy': 0.7928} |
| 0.1431        | 107.0 | 749  | 1.1750          | {'f1': 0.7965299684542587}  | {'accuracy': 0.7936} |
| 0.1431        | 108.0 | 756  | 1.1829          | {'f1': 0.7989045383411582}  | {'accuracy': 0.7944} |
| 0.1431        | 109.0 | 763  | 1.1870          | {'f1': 0.797818465134398}   | {'accuracy': 0.7924} |
| 0.1431        | 110.0 | 770  | 1.1873          | {'f1': 0.7987519500780031}  | {'accuracy': 0.7936} |
| 0.1431        | 111.0 | 777  | 1.1899          | {'f1': 0.798443579766537}   | {'accuracy': 0.7928} |
| 0.1431        | 112.0 | 784  | 1.2010          | {'f1': 0.798151001540832}   | {'accuracy': 0.7904} |
| 0.1431        | 113.0 | 791  | 1.1904          | {'f1': 0.799532892175944}   | {'accuracy': 0.794}  |
| 0.1431        | 114.0 | 798  | 1.1816          | {'f1': 0.7965299684542587}  | {'accuracy': 0.7936} |
| 0.1431        | 115.0 | 805  | 1.1729          | {'f1': 0.7906413876563132}  | {'accuracy': 0.7924} |
| 0.1431        | 116.0 | 812  | 1.1751          | {'f1': 0.7868453105968332}  | {'accuracy': 0.79}   |
| 0.1431        | 117.0 | 819  | 1.1747          | {'f1': 0.7909604519774011}  | {'accuracy': 0.7928} |
| 0.1431        | 118.0 | 826  | 1.1807          | {'f1': 0.7957244655581948}  | {'accuracy': 0.7936} |
| 0.1431        | 119.0 | 833  | 1.3983          | {'f1': 0.7960199004975125}  | {'accuracy': 0.7704} |
| 0.1431        | 120.0 | 840  | 1.3032          | {'f1': 0.7992700729927008}  | {'accuracy': 0.78}   |
| 0.1431        | 121.0 | 847  | 1.2420          | {'f1': 0.7653997378768019}  | {'accuracy': 0.7852} |
| 0.1431        | 122.0 | 854  | 1.1608          | {'f1': 0.7954911433172303}  | {'accuracy': 0.7968} |
| 0.1431        | 123.0 | 861  | 1.2434          | {'f1': 0.8047512991833704}  | {'accuracy': 0.7896} |
| 0.1431        | 124.0 | 868  | 1.1561          | {'f1': 0.7962662337662338}  | {'accuracy': 0.7992} |
| 0.1431        | 125.0 | 875  | 1.1961          | {'f1': 0.7776355100298763}  | {'accuracy': 0.7916} |
| 0.1431        | 126.0 | 882  | 1.2566          | {'f1': 0.802962962962963}   | {'accuracy': 0.7872} |
| 0.1431        | 127.0 | 889  | 1.1969          | {'f1': 0.8042813455657493}  | {'accuracy': 0.7952} |
| 0.1431        | 128.0 | 896  | 1.1668          | {'f1': 0.7972480777013354}  | {'accuracy': 0.7996} |
| 0.1431        | 129.0 | 903  | 1.1762          | {'f1': 0.7916152897657213}  | {'accuracy': 0.7972} |
| 0.1431        | 130.0 | 910  | 1.1758          | {'f1': 0.791307913079131}   | {'accuracy': 0.7964} |
| 0.1431        | 131.0 | 917  | 1.1774          | {'f1': 0.8007889546351085}  | {'accuracy': 0.798}  |
| 0.1431        | 132.0 | 924  | 1.2013          | {'f1': 0.8047564250095894}  | {'accuracy': 0.7964} |
| 0.1431        | 133.0 | 931  | 1.2061          | {'f1': 0.805045871559633}   | {'accuracy': 0.796}  |
| 0.1431        | 134.0 | 938  | 1.1958          | {'f1': 0.8041714947856314}  | {'accuracy': 0.7972} |
| 0.1431        | 135.0 | 945  | 1.1887          | {'f1': 0.8040514218932606}  | {'accuracy': 0.7988} |
| 0.1431        | 136.0 | 952  | 1.1840          | {'f1': 0.8040832351786416}  | {'accuracy': 0.8004} |
| 0.1431        | 137.0 | 959  | 1.1836          | {'f1': 0.8056648308418568}  | {'accuracy': 0.8024} |
| 0.1431        | 138.0 | 966  | 1.1792          | {'f1': 0.8033175355450237}  | {'accuracy': 0.8008} |
| 0.1431        | 139.0 | 973  | 1.1881          | {'f1': 0.8073322932917315}  | {'accuracy': 0.8024} |
| 0.1431        | 140.0 | 980  | 1.2032          | {'f1': 0.8058551617873652}  | {'accuracy': 0.7984} |
| 0.1431        | 141.0 | 987  | 1.2021          | {'f1': 0.8070987654320988}  | {'accuracy': 0.8}    |
| 0.1431        | 142.0 | 994  | 1.2005          | {'f1': 0.8061895551257253}  | {'accuracy': 0.7996} |
| 0.0009        | 143.0 | 1001 | 1.1952          | {'f1': 0.8074679113185532}  | {'accuracy': 0.802}  |
| 0.0009        | 144.0 | 1008 | 1.1926          | {'f1': 0.8085937499999999}  | {'accuracy': 0.804}  |
| 0.0009        | 145.0 | 1015 | 1.1915          | {'f1': 0.8079780993351583}  | {'accuracy': 0.8036} |
| 0.0009        | 146.0 | 1022 | 1.1910          | {'f1': 0.8067424539396315}  | {'accuracy': 0.8028} |
| 0.0009        | 147.0 | 1029 | 1.1865          | {'f1': 0.806948282668772}   | {'accuracy': 0.8044} |
| 0.0009        | 148.0 | 1036 | 1.1827          | {'f1': 0.8025528520143598}  | {'accuracy': 0.802}  |
| 0.0009        | 149.0 | 1043 | 1.1839          | {'f1': 0.8004866180048661}  | {'accuracy': 0.8032} |
| 0.0009        | 150.0 | 1050 | 1.1840          | {'f1': 0.8009708737864079}  | {'accuracy': 0.8032} |
| 0.0009        | 151.0 | 1057 | 1.1846          | {'f1': 0.8025682182985554}  | {'accuracy': 0.8032} |
| 0.0009        | 152.0 | 1064 | 1.1869          | {'f1': 0.8039840637450199}  | {'accuracy': 0.8032} |
| 0.0009        | 153.0 | 1071 | 1.1888          | {'f1': 0.8044515103338633}  | {'accuracy': 0.8032} |
| 0.0009        | 154.0 | 1078 | 1.2019          | {'f1': 0.8078124999999999}  | {'accuracy': 0.8032} |
| 0.0009        | 155.0 | 1085 | 1.2122          | {'f1': 0.8083785880527542}  | {'accuracy': 0.8024} |
| 0.0009        | 156.0 | 1092 | 1.2193          | {'f1': 0.8083462132921175}  | {'accuracy': 0.8016} |
| 0.0009        | 157.0 | 1099 | 1.2198          | {'f1': 0.8083462132921175}  | {'accuracy': 0.8016} |
| 0.0009        | 158.0 | 1106 | 1.2121          | {'f1': 0.8087261394624076}  | {'accuracy': 0.8036} |
| 0.0009        | 159.0 | 1113 | 1.2084          | {'f1': 0.8078124999999999}  | {'accuracy': 0.8032} |
| 0.0009        | 160.0 | 1120 | 1.2091          | {'f1': 0.8078124999999999}  | {'accuracy': 0.8032} |
| 0.0009        | 161.0 | 1127 | 1.2117          | {'f1': 0.8074970714564623}  | {'accuracy': 0.8028} |
| 0.0009        | 162.0 | 1134 | 1.2270          | {'f1': 0.7828668363019508}  | {'accuracy': 0.7952} |
| 0.0009        | 163.0 | 1141 | 1.2069          | {'f1': 0.8028503562945369}  | {'accuracy': 0.8008} |
| 0.0009        | 164.0 | 1148 | 1.4732          | {'f1': 0.8007054673721341}  | {'accuracy': 0.774}  |
| 0.0009        | 165.0 | 1155 | 1.2911          | {'f1': 0.8055451479955038}  | {'accuracy': 0.7924} |
| 0.0009        | 166.0 | 1162 | 1.2061          | {'f1': 0.8075709779179809}  | {'accuracy': 0.8048} |
| 0.0009        | 167.0 | 1169 | 1.2534          | {'f1': 0.8086070215175539}  | {'accuracy': 0.7972} |
| 0.0009        | 168.0 | 1176 | 1.2814          | {'f1': 0.8092744951383695}  | {'accuracy': 0.796}  |
| 0.0009        | 169.0 | 1183 | 1.2533          | {'f1': 0.8111361926260346}  | {'accuracy': 0.7992} |
| 0.0009        | 170.0 | 1190 | 1.2007          | {'f1': 0.8126959247648903}  | {'accuracy': 0.8088} |
| 0.0009        | 171.0 | 1197 | 1.1935          | {'f1': 0.8106180665610143}  | {'accuracy': 0.8088} |
| 0.0009        | 172.0 | 1204 | 1.1932          | {'f1': 0.8079522862823061}  | {'accuracy': 0.8068} |
| 0.0009        | 173.0 | 1211 | 1.1938          | {'f1': 0.8079522862823061}  | {'accuracy': 0.8068} |
| 0.0009        | 174.0 | 1218 | 1.1952          | {'f1': 0.8095238095238094}  | {'accuracy': 0.808}  |
| 0.0009        | 175.0 | 1225 | 1.1973          | {'f1': 0.8118577075098814}  | {'accuracy': 0.8096} |
| 0.0009        | 176.0 | 1232 | 1.2001          | {'f1': 0.8123028391167193}  | {'accuracy': 0.8096} |
| 0.0009        | 177.0 | 1239 | 1.2003          | {'f1': 0.8126232741617356}  | {'accuracy': 0.81}   |
| 0.0009        | 178.0 | 1246 | 1.1996          | {'f1': 0.8104678826328311}  | {'accuracy': 0.8088} |
| 0.0009        | 179.0 | 1253 | 1.1999          | {'f1': 0.8095238095238094}  | {'accuracy': 0.808}  |
| 0.0009        | 180.0 | 1260 | 1.2009          | {'f1': 0.8104678826328311}  | {'accuracy': 0.8088} |
| 0.0009        | 181.0 | 1267 | 1.2028          | {'f1': 0.8126482213438735}  | {'accuracy': 0.8104} |
| 0.0009        | 182.0 | 1274 | 1.2050          | {'f1': 0.8130914826498422}  | {'accuracy': 0.8104} |
| 0.0009        | 183.0 | 1281 | 1.2959          | {'f1': 0.8094170403587443}  | {'accuracy': 0.796}  |
| 0.0009        | 184.0 | 1288 | 1.4564          | {'f1': 0.8015647226173542}  | {'accuracy': 0.7768} |
| 0.0009        | 185.0 | 1295 | 1.2213          | {'f1': 0.8090154211150652}  | {'accuracy': 0.8068} |
| 0.0009        | 186.0 | 1302 | 1.2472          | {'f1': 0.7836355967946014}  | {'accuracy': 0.7948} |
| 0.0009        | 187.0 | 1309 | 1.2286          | {'f1': 0.8066561014263074}  | {'accuracy': 0.8048} |
| 0.0009        | 188.0 | 1316 | 1.2583          | {'f1': 0.8121866563825684}  | {'accuracy': 0.8052} |
| 0.0009        | 189.0 | 1323 | 1.2744          | {'f1': 0.8105423987776929}  | {'accuracy': 0.8016} |
| 0.0009        | 190.0 | 1330 | 1.2877          | {'f1': 0.8078967350037963}  | {'accuracy': 0.7976} |
| 0.0009        | 191.0 | 1337 | 1.2626          | {'f1': 0.8108317214700194}  | {'accuracy': 0.8044} |
| 0.0009        | 192.0 | 1344 | 1.2989          | {'f1': 0.7748058671268335}  | {'accuracy': 0.7912} |
| 0.0009        | 193.0 | 1351 | 1.2673          | {'f1': 0.7831174258253238}  | {'accuracy': 0.7924} |
| 0.0009        | 194.0 | 1358 | 1.2525          | {'f1': 0.8090332805071315}  | {'accuracy': 0.8072} |
| 0.0009        | 195.0 | 1365 | 1.2736          | {'f1': 0.810077519379845}   | {'accuracy': 0.804}  |
| 0.0009        | 196.0 | 1372 | 1.3521          | {'f1': 0.8102297998517419}  | {'accuracy': 0.7952} |
| 0.0009        | 197.0 | 1379 | 1.3654          | {'f1': 0.8086828550404709}  | {'accuracy': 0.792}  |
| 0.0009        | 198.0 | 1386 | 1.3538          | {'f1': 0.8093126385809312}  | {'accuracy': 0.7936} |
| 0.0009        | 199.0 | 1393 | 1.2624          | {'f1': 0.8131782945736433}  | {'accuracy': 0.8072} |
| 0.0009        | 200.0 | 1400 | 1.2467          | {'f1': 0.7957166392092258}  | {'accuracy': 0.8016} |
| 0.0009        | 201.0 | 1407 | 1.2774          | {'f1': 0.7833474936278675}  | {'accuracy': 0.796}  |
| 0.0009        | 202.0 | 1414 | 1.2753          | {'f1': 0.7833827893175075}  | {'accuracy': 0.7956} |
| 0.0009        | 203.0 | 1421 | 1.2851          | {'f1': 0.8121398386477141}  | {'accuracy': 0.8044} |
| 0.0009        | 204.0 | 1428 | 1.4365          | {'f1': 0.8037585833032164}  | {'accuracy': 0.7828} |
| 0.0009        | 205.0 | 1435 | 1.4102          | {'f1': 0.8037997807818781}  | {'accuracy': 0.7852} |
| 0.0009        | 206.0 | 1442 | 1.3754          | {'f1': 0.8053293856402663}  | {'accuracy': 0.7896} |
| 0.0009        | 207.0 | 1449 | 1.3527          | {'f1': 0.8046407185628742}  | {'accuracy': 0.7912} |
| 0.0009        | 208.0 | 1456 | 1.3362          | {'f1': 0.8088955898982284}  | {'accuracy': 0.7972} |
| 0.0009        | 209.0 | 1463 | 1.3206          | {'f1': 0.8138561096307575}  | {'accuracy': 0.8044} |
| 0.0009        | 210.0 | 1470 | 1.3094          | {'f1': 0.8134814247414783}  | {'accuracy': 0.8052} |
| 0.0009        | 211.0 | 1477 | 1.3024          | {'f1': 0.813389765294344}   | {'accuracy': 0.806}  |
| 0.0009        | 212.0 | 1484 | 1.2958          | {'f1': 0.8108317214700194}  | {'accuracy': 0.8044} |
| 0.0009        | 213.0 | 1491 | 1.2930          | {'f1': 0.8102444703143191}  | {'accuracy': 0.8044} |
| 0.0009        | 214.0 | 1498 | 1.2977          | {'f1': 0.8108317214700194}  | {'accuracy': 0.8044} |
| 0.0003        | 215.0 | 1505 | 1.2979          | {'f1': 0.8109992254066616}  | {'accuracy': 0.8048} |
| 0.0003        | 216.0 | 1512 | 1.3123          | {'f1': 0.8141321044546852}  | {'accuracy': 0.8064} |
| 0.0003        | 217.0 | 1519 | 1.3245          | {'f1': 0.8129770992366412}  | {'accuracy': 0.804}  |
| 0.0003        | 218.0 | 1526 | 1.3279          | {'f1': 0.8126669210225105}  | {'accuracy': 0.8036} |
| 0.0003        | 219.0 | 1533 | 1.3249          | {'f1': 0.813287514318442}   | {'accuracy': 0.8044} |
| 0.0003        | 220.0 | 1540 | 1.3202          | {'f1': 0.8147013782542114}  | {'accuracy': 0.8064} |
| 0.0003        | 221.0 | 1547 | 1.3125          | {'f1': 0.8112480739599385}  | {'accuracy': 0.804}  |
| 0.0003        | 222.0 | 1554 | 1.3040          | {'f1': 0.8105385509492445}  | {'accuracy': 0.8044} |
| 0.0003        | 223.0 | 1561 | 1.3616          | {'f1': 0.8061492313460817}  | {'accuracy': 0.7932} |
| 0.0003        | 224.0 | 1568 | 1.6007          | {'f1': 0.7990196078431372}  | {'accuracy': 0.7704} |
| 0.0003        | 225.0 | 1575 | 1.5556          | {'f1': 0.8007054673721341}  | {'accuracy': 0.774}  |
| 0.0003        | 226.0 | 1582 | 1.4173          | {'f1': 0.8058608058608058}  | {'accuracy': 0.788}  |
| 0.0003        | 227.0 | 1589 | 1.2708          | {'f1': 0.8091844813935075}  | {'accuracy': 0.8072} |
| 0.0003        | 228.0 | 1596 | 1.2721          | {'f1': 0.7967145790554415}  | {'accuracy': 0.802}  |
| 0.0003        | 229.0 | 1603 | 1.2797          | {'f1': 0.7948611686697058}  | {'accuracy': 0.802}  |
| 0.0003        | 230.0 | 1610 | 1.2756          | {'f1': 0.7977020927369718}  | {'accuracy': 0.8028} |
| 0.0003        | 231.0 | 1617 | 1.2732          | {'f1': 0.7987012987012987}  | {'accuracy': 0.8016} |
| 0.0003        | 232.0 | 1624 | 1.2735          | {'f1': 0.8037007240547064}  | {'accuracy': 0.8048} |
| 0.0003        | 233.0 | 1631 | 1.2756          | {'f1': 0.8060775689724111}  | {'accuracy': 0.806}  |
| 0.0003        | 234.0 | 1638 | 1.2775          | {'f1': 0.8087649402390439}  | {'accuracy': 0.808}  |
| 0.0003        | 235.0 | 1645 | 1.2786          | {'f1': 0.8084428514536042}  | {'accuracy': 0.8076} |
| 0.0003        | 236.0 | 1652 | 1.2803          | {'f1': 0.8068362480127186}  | {'accuracy': 0.8056} |
| 0.0003        | 237.0 | 1659 | 1.2827          | {'f1': 0.8076009501187648}  | {'accuracy': 0.8056} |
| 0.0003        | 238.0 | 1666 | 1.2816          | {'f1': 0.8071570576540756}  | {'accuracy': 0.806}  |
| 0.0003        | 239.0 | 1673 | 1.2808          | {'f1': 0.8068635275339185}  | {'accuracy': 0.8064} |
| 0.0003        | 240.0 | 1680 | 1.2807          | {'f1': 0.8065547561950439}  | {'accuracy': 0.8064} |
| 0.0003        | 241.0 | 1687 | 1.2794          | {'f1': 0.8032193158953722}  | {'accuracy': 0.8044} |
| 0.0003        | 242.0 | 1694 | 1.2994          | {'f1': 0.791578947368421}   | {'accuracy': 0.802}  |
| 0.0003        | 243.0 | 1701 | 1.3223          | {'f1': 0.7840616966580977}  | {'accuracy': 0.7984} |
| 0.0003        | 244.0 | 1708 | 1.2878          | {'f1': 0.7956810631229236}  | {'accuracy': 0.8032} |
| 0.0003        | 245.0 | 1715 | 1.2761          | {'f1': 0.8040567951318459}  | {'accuracy': 0.8068} |
| 0.0003        | 246.0 | 1722 | 1.2763          | {'f1': 0.8051323175621492}  | {'accuracy': 0.8056} |
| 0.0003        | 247.0 | 1729 | 1.2789          | {'f1': 0.810207336523126}   | {'accuracy': 0.8096} |
| 0.0003        | 248.0 | 1736 | 1.2818          | {'f1': 0.8109393579072532}  | {'accuracy': 0.8092} |
| 0.0003        | 249.0 | 1743 | 1.2847          | {'f1': 0.8138801261829653}  | {'accuracy': 0.8112} |
| 0.0003        | 250.0 | 1750 | 1.2864          | {'f1': 0.8140267927501971}  | {'accuracy': 0.8112} |
| 0.0003        | 251.0 | 1757 | 1.2869          | {'f1': 0.8140267927501971}  | {'accuracy': 0.8112} |
| 0.0003        | 252.0 | 1764 | 1.2863          | {'f1': 0.8132649032767469}  | {'accuracy': 0.8108} |
| 0.0003        | 253.0 | 1771 | 1.2859          | {'f1': 0.8117088607594937}  | {'accuracy': 0.8096} |
| 0.0003        | 254.0 | 1778 | 1.2860          | {'f1': 0.811089108910891}   | {'accuracy': 0.8092} |
| 0.0003        | 255.0 | 1785 | 1.2867          | {'f1': 0.81203007518797}    | {'accuracy': 0.81}   |
| 0.0003        | 256.0 | 1792 | 1.2884          | {'f1': 0.8132649032767469}  | {'accuracy': 0.8108} |
| 0.0003        | 257.0 | 1799 | 1.2988          | {'f1': 0.8167252833137943}  | {'accuracy': 0.8124} |
| 0.0003        | 258.0 | 1806 | 1.3067          | {'f1': 0.8163424124513619}  | {'accuracy': 0.8112} |
| 0.0003        | 259.0 | 1813 | 1.2974          | {'f1': 0.8155111633372502}  | {'accuracy': 0.8116} |
| 0.0003        | 260.0 | 1820 | 1.2927          | {'f1': 0.8144654088050315}  | {'accuracy': 0.8112} |
| 0.0003        | 261.0 | 1827 | 1.2901          | {'f1': 0.8127962085308058}  | {'accuracy': 0.8104} |
| 0.0003        | 262.0 | 1834 | 1.2891          | {'f1': 0.8126732673267326}  | {'accuracy': 0.8108} |
| 0.0003        | 263.0 | 1841 | 1.2890          | {'f1': 0.8107893692978976}  | {'accuracy': 0.8092} |
| 0.0003        | 264.0 | 1848 | 1.2912          | {'f1': 0.8127962085308058}  | {'accuracy': 0.8104} |
| 0.0003        | 265.0 | 1855 | 1.2928          | {'f1': 0.8142011834319528}  | {'accuracy': 0.8116} |
| 0.0003        | 266.0 | 1862 | 1.2935          | {'f1': 0.8138801261829653}  | {'accuracy': 0.8112} |
| 0.0003        | 267.0 | 1869 | 1.2941          | {'f1': 0.814814814814815}   | {'accuracy': 0.812}  |
| 0.0003        | 268.0 | 1876 | 1.2942          | {'f1': 0.8138801261829653}  | {'accuracy': 0.8112} |
| 0.0003        | 269.0 | 1883 | 1.2951          | {'f1': 0.8144938952343442}  | {'accuracy': 0.8116} |
| 0.0003        | 270.0 | 1890 | 1.2983          | {'f1': 0.8141453831041258}  | {'accuracy': 0.8108} |
| 0.0003        | 271.0 | 1897 | 1.3002          | {'f1': 0.8142913231252454}  | {'accuracy': 0.8108} |
| 0.0003        | 272.0 | 1904 | 1.3017          | {'f1': 0.8156862745098038}  | {'accuracy': 0.812}  |
| 0.0003        | 273.0 | 1911 | 1.3045          | {'f1': 0.8161189358372457}  | {'accuracy': 0.812}  |
| 0.0003        | 274.0 | 1918 | 1.3077          | {'f1': 0.8175068386088317}  | {'accuracy': 0.8132} |
| 0.0003        | 275.0 | 1925 | 1.3098          | {'f1': 0.8173302107728336}  | {'accuracy': 0.8128} |
| 0.0003        | 276.0 | 1932 | 1.3145          | {'f1': 0.8163424124513619}  | {'accuracy': 0.8112} |
| 0.0003        | 277.0 | 1939 | 1.3161          | {'f1': 0.8168028004667445}  | {'accuracy': 0.8116} |
| 0.0003        | 278.0 | 1946 | 1.3159          | {'f1': 0.8163424124513619}  | {'accuracy': 0.8112} |
| 0.0003        | 279.0 | 1953 | 1.3156          | {'f1': 0.8166601790579991}  | {'accuracy': 0.8116} |
| 0.0003        | 280.0 | 1960 | 1.3118          | {'f1': 0.8170113148653921}  | {'accuracy': 0.8124} |
| 0.0003        | 281.0 | 1967 | 1.3088          | {'f1': 0.8161189358372457}  | {'accuracy': 0.812}  |
| 0.0003        | 282.0 | 1974 | 1.3077          | {'f1': 0.8145825166601333}  | {'accuracy': 0.8108} |
| 0.0003        | 283.0 | 1981 | 1.3072          | {'f1': 0.8149019607843137}  | {'accuracy': 0.8112} |
| 0.0003        | 284.0 | 1988 | 1.3075          | {'f1': 0.8149019607843137}  | {'accuracy': 0.8112} |
| 0.0003        | 285.0 | 1995 | 1.3084          | {'f1': 0.8149019607843137}  | {'accuracy': 0.8112} |
| 0.0001        | 286.0 | 2002 | 1.3097          | {'f1': 0.8147277712495105}  | {'accuracy': 0.8108} |
| 0.0001        | 287.0 | 2009 | 1.3106          | {'f1': 0.815655577299413}   | {'accuracy': 0.8116} |
| 0.0001        | 288.0 | 2016 | 1.3076          | {'f1': 0.8150765606595994}  | {'accuracy': 0.8116} |
| 0.0001        | 289.0 | 2023 | 1.3055          | {'f1': 0.8154269972451791}  | {'accuracy': 0.8124} |
| 0.0001        | 290.0 | 2030 | 1.3025          | {'f1': 0.8145224940805051}  | {'accuracy': 0.812}  |
| 0.0001        | 291.0 | 2037 | 1.3139          | {'f1': 0.8165819319515056}  | {'accuracy': 0.8124} |
| 0.0001        | 292.0 | 2044 | 1.3268          | {'f1': 0.8170542635658915}  | {'accuracy': 0.8112} |
| 0.0001        | 293.0 | 2051 | 1.3310          | {'f1': 0.8170212765957446}  | {'accuracy': 0.8108} |
| 0.0001        | 294.0 | 2058 | 1.3307          | {'f1': 0.8170212765957446}  | {'accuracy': 0.8108} |
| 0.0001        | 295.0 | 2065 | 1.4449          | {'f1': 0.8125}              | {'accuracy': 0.796}  |
| 0.0001        | 296.0 | 2072 | 1.5353          | {'f1': 0.8086175942549373}  | {'accuracy': 0.7868} |
| 0.0001        | 297.0 | 2079 | 1.4656          | {'f1': 0.8106530463334549}  | {'accuracy': 0.7924} |
| 0.0001        | 298.0 | 2086 | 1.3036          | {'f1': 0.8156028368794326}  | {'accuracy': 0.8128} |
| 0.0001        | 299.0 | 2093 | 1.2977          | {'f1': 0.8054410552349547}  | {'accuracy': 0.8112} |
| 0.0001        | 300.0 | 2100 | 1.2972          | {'f1': 0.8068739770867429}  | {'accuracy': 0.8112} |
| 0.0001        | 301.0 | 2107 | 1.2982          | {'f1': 0.810441767068273}   | {'accuracy': 0.8112} |
| 0.0001        | 302.0 | 2114 | 1.3025          | {'f1': 0.8116288331342094}  | {'accuracy': 0.8108} |
| 0.0001        | 303.0 | 2121 | 1.3063          | {'f1': 0.8142574257425743}  | {'accuracy': 0.8124} |
| 0.0001        | 304.0 | 2128 | 1.3108          | {'f1': 0.8148440584287406}  | {'accuracy': 0.8124} |
| 0.0001        | 305.0 | 2135 | 1.3120          | {'f1': 0.8153117600631413}  | {'accuracy': 0.8128} |
| 0.0001        | 306.0 | 2142 | 1.3152          | {'f1': 0.8146399055489965}  | {'accuracy': 0.8116} |
| 0.0001        | 307.0 | 2149 | 1.3293          | {'f1': 0.8155339805825242}  | {'accuracy': 0.81}   |
| 0.0001        | 308.0 | 2156 | 1.3356          | {'f1': 0.8165314793356508}  | {'accuracy': 0.81}   |
| 0.0001        | 309.0 | 2163 | 1.3352          | {'f1': 0.8163896405102435}  | {'accuracy': 0.81}   |
| 0.0001        | 310.0 | 2170 | 1.3325          | {'f1': 0.8156771439658517}  | {'accuracy': 0.81}   |
| 0.0001        | 311.0 | 2177 | 1.3303          | {'f1': 0.815390594636611}   | {'accuracy': 0.81}   |
| 0.0001        | 312.0 | 2184 | 1.3272          | {'f1': 0.8160561184723305}  | {'accuracy': 0.8112} |
| 0.0001        | 313.0 | 2191 | 1.3246          | {'f1': 0.8143806174286832}  | {'accuracy': 0.81}   |
| 0.0001        | 314.0 | 2198 | 1.3224          | {'f1': 0.8134796238244514}  | {'accuracy': 0.8096} |
| 0.0001        | 315.0 | 2205 | 1.3203          | {'f1': 0.815251572327044}   | {'accuracy': 0.812}  |
| 0.0001        | 316.0 | 2212 | 1.3183          | {'f1': 0.8167126527394561}  | {'accuracy': 0.814}  |
| 0.0001        | 317.0 | 2219 | 1.3132          | {'f1': 0.8129952456418383}  | {'accuracy': 0.8112} |
| 0.0001        | 318.0 | 2226 | 1.3111          | {'f1': 0.8127236580516899}  | {'accuracy': 0.8116} |
| 0.0001        | 319.0 | 2233 | 1.3078          | {'f1': 0.8101164191087917}  | {'accuracy': 0.8108} |
| 0.0001        | 320.0 | 2240 | 1.3076          | {'f1': 0.8096774193548387}  | {'accuracy': 0.8112} |
| 0.0001        | 321.0 | 2247 | 1.3090          | {'f1': 0.8101164191087917}  | {'accuracy': 0.8108} |
| 0.0001        | 322.0 | 2254 | 1.3433          | {'f1': 0.7892491467576792}  | {'accuracy': 0.8024} |
| 0.0001        | 323.0 | 2261 | 1.4595          | {'f1': 0.7642058165548098}  | {'accuracy': 0.7892} |
| 0.0001        | 324.0 | 2268 | 1.3247          | {'f1': 0.7968026924694994}  | {'accuracy': 0.8068} |
| 0.0001        | 325.0 | 2275 | 1.3326          | {'f1': 0.8177570093457942}  | {'accuracy': 0.8128} |
| 0.0001        | 326.0 | 2282 | 1.3992          | {'f1': 0.8167105758374106}  | {'accuracy': 0.8052} |
| 0.0001        | 327.0 | 2289 | 1.4017          | {'f1': 0.8177376925967682}  | {'accuracy': 0.806}  |
| 0.0001        | 328.0 | 2296 | 1.3527          | {'f1': 0.8194070080862534}  | {'accuracy': 0.8124} |
| 0.0001        | 329.0 | 2303 | 1.3316          | {'f1': 0.8175465838509317}  | {'accuracy': 0.812}  |
| 0.0001        | 330.0 | 2310 | 1.3199          | {'f1': 0.8155111633372502}  | {'accuracy': 0.8116} |
| 0.0001        | 331.0 | 2317 | 1.3143          | {'f1': 0.8127709893575089}  | {'accuracy': 0.81}   |
| 0.0001        | 332.0 | 2324 | 1.3109          | {'f1': 0.8113879003558718}  | {'accuracy': 0.8092} |
| 0.0001        | 333.0 | 2331 | 1.3092          | {'f1': 0.8114104595879558}  | {'accuracy': 0.8096} |
| 0.0001        | 334.0 | 2338 | 1.3085          | {'f1': 0.8104678826328311}  | {'accuracy': 0.8088} |
| 0.0001        | 335.0 | 2345 | 1.3083          | {'f1': 0.8107893692978976}  | {'accuracy': 0.8092} |
| 0.0001        | 336.0 | 2352 | 1.3086          | {'f1': 0.8107893692978976}  | {'accuracy': 0.8092} |
| 0.0001        | 337.0 | 2359 | 1.3096          | {'f1': 0.8109393579072532}  | {'accuracy': 0.8092} |
| 0.0001        | 338.0 | 2366 | 1.3108          | {'f1': 0.8118811881188118}  | {'accuracy': 0.81}   |
| 0.0001        | 339.0 | 2373 | 1.3119          | {'f1': 0.812351543942993}   | {'accuracy': 0.8104} |
| 0.0001        | 340.0 | 2380 | 1.3130          | {'f1': 0.8117088607594937}  | {'accuracy': 0.8096} |
| 0.0001        | 341.0 | 2387 | 1.3141          | {'f1': 0.8115369419201897}  | {'accuracy': 0.8092} |
| 0.0001        | 342.0 | 2394 | 1.3154          | {'f1': 0.811216429699842}   | {'accuracy': 0.8088} |
| 0.0001        | 343.0 | 2401 | 1.3151          | {'f1': 0.8115369419201897}  | {'accuracy': 0.8092} |
| 0.0001        | 344.0 | 2408 | 1.3154          | {'f1': 0.8115369419201897}  | {'accuracy': 0.8092} |
| 0.0001        | 345.0 | 2415 | 1.3156          | {'f1': 0.8115369419201897}  | {'accuracy': 0.8092} |
| 0.0001        | 346.0 | 2422 | 1.3157          | {'f1': 0.8115369419201897}  | {'accuracy': 0.8092} |
| 0.0001        | 347.0 | 2429 | 1.3158          | {'f1': 0.8115369419201897}  | {'accuracy': 0.8092} |
| 0.0001        | 348.0 | 2436 | 1.3338          | {'f1': 0.8160561184723305}  | {'accuracy': 0.8112} |
| 0.0001        | 349.0 | 2443 | 1.3439          | {'f1': 0.819062378922898}   | {'accuracy': 0.8132} |
| 0.0001        | 350.0 | 2450 | 1.3474          | {'f1': 0.8188854489164088}  | {'accuracy': 0.8128} |
| 0.0001        | 351.0 | 2457 | 1.3484          | {'f1': 0.8188854489164088}  | {'accuracy': 0.8128} |
| 0.0001        | 352.0 | 2464 | 1.3478          | {'f1': 0.8188854489164088}  | {'accuracy': 0.8128} |
| 0.0001        | 353.0 | 2471 | 1.3462          | {'f1': 0.8186046511627906}  | {'accuracy': 0.8128} |
| 0.0001        | 354.0 | 2478 | 1.3432          | {'f1': 0.8183229813664596}  | {'accuracy': 0.8128} |
| 0.0001        | 355.0 | 2485 | 1.3415          | {'f1': 0.8172628304821151}  | {'accuracy': 0.812}  |
| 0.0001        | 356.0 | 2492 | 1.3380          | {'f1': 0.8166601790579991}  | {'accuracy': 0.8116} |
| 0.0001        | 357.0 | 2499 | 1.3354          | {'f1': 0.8165495706479313}  | {'accuracy': 0.812}  |
| 0.0011        | 358.0 | 2506 | 1.3370          | {'f1': 0.816374269005848}   | {'accuracy': 0.8116} |
| 0.0011        | 359.0 | 2513 | 1.3384          | {'f1': 0.8172964550058435}  | {'accuracy': 0.8124} |
| 0.0011        | 360.0 | 2520 | 1.3373          | {'f1': 0.8166926677067083}  | {'accuracy': 0.812}  |
| 0.0011        | 361.0 | 2527 | 1.3354          | {'f1': 0.8157689305230289}  | {'accuracy': 0.8112} |
| 0.0011        | 362.0 | 2534 | 1.3336          | {'f1': 0.8153364632237872}  | {'accuracy': 0.8112} |
| 0.0011        | 363.0 | 2541 | 1.3321          | {'f1': 0.8145825166601333}  | {'accuracy': 0.8108} |
| 0.0011        | 364.0 | 2548 | 1.3280          | {'f1': 0.8149312377210216}  | {'accuracy': 0.8116} |
| 0.0011        | 365.0 | 2555 | 1.3711          | {'f1': 0.819433817903596}   | {'accuracy': 0.8112} |
| 0.0011        | 366.0 | 2562 | 1.4276          | {'f1': 0.8177083333333331}  | {'accuracy': 0.804}  |
| 0.0011        | 367.0 | 2569 | 1.4536          | {'f1': 0.8159645232815964}  | {'accuracy': 0.8008} |
| 0.0011        | 368.0 | 2576 | 1.4590          | {'f1': 0.8161004431314622}  | {'accuracy': 0.8008} |
| 0.0011        | 369.0 | 2583 | 1.3146          | {'f1': 0.8145224940805051}  | {'accuracy': 0.812}  |
| 0.0011        | 370.0 | 2590 | 1.3096          | {'f1': 0.8057851239669422}  | {'accuracy': 0.812}  |
| 0.0011        | 371.0 | 2597 | 1.3042          | {'f1': 0.8077080770807707}  | {'accuracy': 0.8124} |
| 0.0011        | 372.0 | 2604 | 1.3011          | {'f1': 0.8080065359477124}  | {'accuracy': 0.812}  |
| 0.0011        | 373.0 | 2611 | 1.3000          | {'f1': 0.8090982940698618}  | {'accuracy': 0.812}  |
| 0.0011        | 374.0 | 2618 | 1.3001          | {'f1': 0.8127522195318806}  | {'accuracy': 0.8144} |
| 0.0011        | 375.0 | 2625 | 1.3009          | {'f1': 0.8102893890675241}  | {'accuracy': 0.8112} |
| 0.0011        | 376.0 | 2632 | 1.3019          | {'f1': 0.8102687525070197}  | {'accuracy': 0.8108} |
| 0.0011        | 377.0 | 2639 | 1.3028          | {'f1': 0.8112}              | {'accuracy': 0.8112} |
| 0.0011        | 378.0 | 2646 | 1.3038          | {'f1': 0.8119760479041915}  | {'accuracy': 0.8116} |
| 0.0011        | 379.0 | 2653 | 1.3058          | {'f1': 0.8125746120175089}  | {'accuracy': 0.8116} |
| 0.0011        | 380.0 | 2660 | 1.3096          | {'f1': 0.8134653465346535}  | {'accuracy': 0.8116} |
| 0.0011        | 381.0 | 2667 | 1.3122          | {'f1': 0.8164232135807343}  | {'accuracy': 0.814}  |
| 0.0011        | 382.0 | 2674 | 1.3137          | {'f1': 0.8168902920284135}  | {'accuracy': 0.8144} |
| 0.0011        | 383.0 | 2681 | 1.3156          | {'f1': 0.8170347003154574}  | {'accuracy': 0.8144} |
| 0.0011        | 384.0 | 2688 | 1.3162          | {'f1': 0.8167126527394561}  | {'accuracy': 0.814}  |
| 0.0011        | 385.0 | 2695 | 1.3165          | {'f1': 0.8167126527394561}  | {'accuracy': 0.814}  |
| 0.0011        | 386.0 | 2702 | 1.3168          | {'f1': 0.8167126527394561}  | {'accuracy': 0.814}  |
| 0.0011        | 387.0 | 2709 | 1.3169          | {'f1': 0.8167126527394561}  | {'accuracy': 0.814}  |
| 0.0011        | 388.0 | 2716 | 1.3166          | {'f1': 0.8170347003154574}  | {'accuracy': 0.8144} |
| 0.0011        | 389.0 | 2723 | 1.3166          | {'f1': 0.8170347003154574}  | {'accuracy': 0.8144} |
| 0.0011        | 390.0 | 2730 | 1.3168          | {'f1': 0.8170347003154574}  | {'accuracy': 0.8144} |
| 0.0011        | 391.0 | 2737 | 1.3165          | {'f1': 0.8170347003154574}  | {'accuracy': 0.8144} |
| 0.0011        | 392.0 | 2744 | 1.3168          | {'f1': 0.8170347003154574}  | {'accuracy': 0.8144} |
| 0.0011        | 393.0 | 2751 | 1.3172          | {'f1': 0.8170347003154574}  | {'accuracy': 0.8144} |
| 0.0011        | 394.0 | 2758 | 1.3173          | {'f1': 0.8170347003154574}  | {'accuracy': 0.8144} |
| 0.0011        | 395.0 | 2765 | 1.3161          | {'f1': 0.8154879494271038}  | {'accuracy': 0.8132} |
| 0.0011        | 396.0 | 2772 | 1.3156          | {'f1': 0.8148734177215189}  | {'accuracy': 0.8128} |
| 0.0011        | 397.0 | 2779 | 1.3148          | {'f1': 0.8129952456418383}  | {'accuracy': 0.8112} |
| 0.0011        | 398.0 | 2786 | 1.3146          | {'f1': 0.8129952456418383}  | {'accuracy': 0.8112} |
| 0.0011        | 399.0 | 2793 | 1.3142          | {'f1': 0.8133174791914388}  | {'accuracy': 0.8116} |
| 0.0011        | 400.0 | 2800 | 1.3146          | {'f1': 0.8129952456418383}  | {'accuracy': 0.8112} |
| 0.0011        | 401.0 | 2807 | 1.3163          | {'f1': 0.8139350752177354}  | {'accuracy': 0.812}  |
| 0.0011        | 402.0 | 2814 | 1.3147          | {'f1': 0.8139627132090439}  | {'accuracy': 0.8124} |
| 0.0011        | 403.0 | 2821 | 1.3137          | {'f1': 0.813195548489666}   | {'accuracy': 0.812}  |
| 0.0011        | 404.0 | 2828 | 1.3133          | {'f1': 0.8135188866799204}  | {'accuracy': 0.8124} |
| 0.0011        | 405.0 | 2835 | 1.3132          | {'f1': 0.8135188866799204}  | {'accuracy': 0.8124} |
| 0.0011        | 406.0 | 2842 | 1.3132          | {'f1': 0.8125746120175089}  | {'accuracy': 0.8116} |
| 0.0011        | 407.0 | 2849 | 1.3132          | {'f1': 0.8121019108280254}  | {'accuracy': 0.8112} |
| 0.0011        | 408.0 | 2856 | 1.3146          | {'f1': 0.8130469371519491}  | {'accuracy': 0.812}  |
| 0.0011        | 409.0 | 2863 | 1.3186          | {'f1': 0.8144044321329641}  | {'accuracy': 0.8124} |
| 0.0011        | 410.0 | 2870 | 1.3217          | {'f1': 0.8156336360047375}  | {'accuracy': 0.8132} |
| 0.0011        | 411.0 | 2877 | 1.3233          | {'f1': 0.8167126527394561}  | {'accuracy': 0.814}  |
| 0.0011        | 412.0 | 2884 | 1.3243          | {'f1': 0.8167126527394561}  | {'accuracy': 0.814}  |
| 0.0011        | 413.0 | 2891 | 1.3248          | {'f1': 0.8167126527394561}  | {'accuracy': 0.814}  |
| 0.0011        | 414.0 | 2898 | 1.3249          | {'f1': 0.8167126527394561}  | {'accuracy': 0.814}  |
| 0.0011        | 415.0 | 2905 | 1.3248          | {'f1': 0.8167126527394561}  | {'accuracy': 0.814}  |
| 0.0011        | 416.0 | 2912 | 1.3249          | {'f1': 0.8167126527394561}  | {'accuracy': 0.814}  |
| 0.0011        | 417.0 | 2919 | 1.3251          | {'f1': 0.8167126527394561}  | {'accuracy': 0.814}  |
| 0.0011        | 418.0 | 2926 | 1.3250          | {'f1': 0.8167126527394561}  | {'accuracy': 0.814}  |
| 0.0011        | 419.0 | 2933 | 1.3250          | {'f1': 0.8167126527394561}  | {'accuracy': 0.814}  |
| 0.0011        | 420.0 | 2940 | 1.3250          | {'f1': 0.8167126527394561}  | {'accuracy': 0.814}  |
| 0.0011        | 421.0 | 2947 | 1.3246          | {'f1': 0.8162460567823343}  | {'accuracy': 0.8136} |
| 0.0011        | 422.0 | 2954 | 1.3244          | {'f1': 0.8156336360047375}  | {'accuracy': 0.8132} |
| 0.0011        | 423.0 | 2961 | 1.3242          | {'f1': 0.8156336360047375}  | {'accuracy': 0.8132} |
| 0.0011        | 424.0 | 2968 | 1.3245          | {'f1': 0.8156336360047375}  | {'accuracy': 0.8132} |
| 0.0011        | 425.0 | 2975 | 1.3256          | {'f1': 0.8167126527394561}  | {'accuracy': 0.814}  |
| 0.0011        | 426.0 | 2982 | 1.3260          | {'f1': 0.8167126527394561}  | {'accuracy': 0.814}  |
| 0.0011        | 427.0 | 2989 | 1.3261          | {'f1': 0.8167126527394561}  | {'accuracy': 0.814}  |
| 0.0011        | 428.0 | 2996 | 1.3264          | {'f1': 0.8167126527394561}  | {'accuracy': 0.814}  |
| 0.0           | 429.0 | 3003 | 1.3265          | {'f1': 0.8167126527394561}  | {'accuracy': 0.814}  |
| 0.0           | 430.0 | 3010 | 1.3268          | {'f1': 0.8167126527394561}  | {'accuracy': 0.814}  |
| 0.0           | 431.0 | 3017 | 1.3265          | {'f1': 0.8162460567823343}  | {'accuracy': 0.8136} |
| 0.0           | 432.0 | 3024 | 1.3260          | {'f1': 0.8161010260457774}  | {'accuracy': 0.8136} |
| 0.0           | 433.0 | 3031 | 1.3259          | {'f1': 0.8156336360047375}  | {'accuracy': 0.8132} |
| 0.0           | 434.0 | 3038 | 1.3260          | {'f1': 0.8156336360047375}  | {'accuracy': 0.8132} |
| 0.0           | 435.0 | 3045 | 1.3262          | {'f1': 0.8156336360047375}  | {'accuracy': 0.8132} |
| 0.0           | 436.0 | 3052 | 1.3257          | {'f1': 0.8156336360047375}  | {'accuracy': 0.8132} |
| 0.0           | 437.0 | 3059 | 1.3255          | {'f1': 0.8156336360047375}  | {'accuracy': 0.8132} |
| 0.0           | 438.0 | 3066 | 1.3250          | {'f1': 0.8154879494271038}  | {'accuracy': 0.8132} |
| 0.0           | 439.0 | 3073 | 1.3247          | {'f1': 0.8153420324238829}  | {'accuracy': 0.8132} |
| 0.0           | 440.0 | 3080 | 1.3245          | {'f1': 0.8144044321329641}  | {'accuracy': 0.8124} |
| 0.0           | 441.0 | 3087 | 1.3242          | {'f1': 0.8144044321329641}  | {'accuracy': 0.8124} |
| 0.0           | 442.0 | 3094 | 1.3243          | {'f1': 0.8144044321329641}  | {'accuracy': 0.8124} |
| 0.0           | 443.0 | 3101 | 1.3247          | {'f1': 0.8144044321329641}  | {'accuracy': 0.8124} |
| 0.0           | 444.0 | 3108 | 1.3250          | {'f1': 0.8144044321329641}  | {'accuracy': 0.8124} |
| 0.0           | 445.0 | 3115 | 1.3254          | {'f1': 0.8153420324238829}  | {'accuracy': 0.8132} |
| 0.0           | 446.0 | 3122 | 1.3254          | {'f1': 0.8148734177215189}  | {'accuracy': 0.8128} |
| 0.0           | 447.0 | 3129 | 1.3257          | {'f1': 0.8153420324238829}  | {'accuracy': 0.8132} |
| 0.0           | 448.0 | 3136 | 1.3258          | {'f1': 0.8153420324238829}  | {'accuracy': 0.8132} |
| 0.0           | 449.0 | 3143 | 1.3260          | {'f1': 0.8153420324238829}  | {'accuracy': 0.8132} |
| 0.0           | 450.0 | 3150 | 1.3264          | {'f1': 0.8153420324238829}  | {'accuracy': 0.8132} |
| 0.0           | 451.0 | 3157 | 1.3270          | {'f1': 0.815955766192733}   | {'accuracy': 0.8136} |
| 0.0           | 452.0 | 3164 | 1.3273          | {'f1': 0.8156336360047375}  | {'accuracy': 0.8132} |
| 0.0           | 453.0 | 3171 | 1.3276          | {'f1': 0.8156336360047375}  | {'accuracy': 0.8132} |
| 0.0           | 454.0 | 3178 | 1.3277          | {'f1': 0.8156336360047375}  | {'accuracy': 0.8132} |
| 0.0           | 455.0 | 3185 | 1.3278          | {'f1': 0.8156336360047375}  | {'accuracy': 0.8132} |
| 0.0           | 456.0 | 3192 | 1.3279          | {'f1': 0.8156336360047375}  | {'accuracy': 0.8132} |
| 0.0           | 457.0 | 3199 | 1.3283          | {'f1': 0.8156336360047375}  | {'accuracy': 0.8132} |
| 0.0           | 458.0 | 3206 | 1.3285          | {'f1': 0.8156336360047375}  | {'accuracy': 0.8132} |
| 0.0           | 459.0 | 3213 | 1.3288          | {'f1': 0.8156336360047375}  | {'accuracy': 0.8132} |
| 0.0           | 460.0 | 3220 | 1.3290          | {'f1': 0.8156336360047375}  | {'accuracy': 0.8132} |
| 0.0           | 461.0 | 3227 | 1.3291          | {'f1': 0.8156336360047375}  | {'accuracy': 0.8132} |
| 0.0           | 462.0 | 3234 | 1.3291          | {'f1': 0.8156336360047375}  | {'accuracy': 0.8132} |
| 0.0           | 463.0 | 3241 | 1.3296          | {'f1': 0.8153117600631413}  | {'accuracy': 0.8128} |
| 0.0           | 464.0 | 3248 | 1.3298          | {'f1': 0.8153117600631413}  | {'accuracy': 0.8128} |
| 0.0           | 465.0 | 3255 | 1.3297          | {'f1': 0.8153117600631413}  | {'accuracy': 0.8128} |
| 0.0           | 466.0 | 3262 | 1.3295          | {'f1': 0.8156336360047375}  | {'accuracy': 0.8132} |
| 0.0           | 467.0 | 3269 | 1.3298          | {'f1': 0.8156336360047375}  | {'accuracy': 0.8132} |
| 0.0           | 468.0 | 3276 | 1.3301          | {'f1': 0.8153117600631413}  | {'accuracy': 0.8128} |
| 0.0           | 469.0 | 3283 | 1.3306          | {'f1': 0.8153117600631413}  | {'accuracy': 0.8128} |
| 0.0           | 470.0 | 3290 | 1.3309          | {'f1': 0.8153117600631413}  | {'accuracy': 0.8128} |
| 0.0           | 471.0 | 3297 | 1.3321          | {'f1': 0.8162460567823343}  | {'accuracy': 0.8136} |
| 0.0           | 472.0 | 3304 | 1.3328          | {'f1': 0.8167126527394561}  | {'accuracy': 0.814}  |
| 0.0           | 473.0 | 3311 | 1.3333          | {'f1': 0.8176447420244192}  | {'accuracy': 0.8148} |
| 0.0           | 474.0 | 3318 | 1.3335          | {'f1': 0.8176447420244192}  | {'accuracy': 0.8148} |
| 0.0           | 475.0 | 3325 | 1.3335          | {'f1': 0.8176447420244192}  | {'accuracy': 0.8148} |
| 0.0           | 476.0 | 3332 | 1.3336          | {'f1': 0.8176447420244192}  | {'accuracy': 0.8148} |
| 0.0           | 477.0 | 3339 | 1.3336          | {'f1': 0.8176447420244192}  | {'accuracy': 0.8148} |
| 0.0           | 478.0 | 3346 | 1.3337          | {'f1': 0.8176447420244192}  | {'accuracy': 0.8148} |
| 0.0           | 479.0 | 3353 | 1.3335          | {'f1': 0.8167126527394561}  | {'accuracy': 0.814}  |
| 0.0           | 480.0 | 3360 | 1.3334          | {'f1': 0.8167126527394561}  | {'accuracy': 0.814}  |
| 0.0           | 481.0 | 3367 | 1.3336          | {'f1': 0.8167126527394561}  | {'accuracy': 0.814}  |
| 0.0           | 482.0 | 3374 | 1.3336          | {'f1': 0.8171788810086682}  | {'accuracy': 0.8144} |
| 0.0           | 483.0 | 3381 | 1.3534          | {'f1': 0.8176538908246225}  | {'accuracy': 0.8116} |
| 0.0           | 484.0 | 3388 | 1.3670          | {'f1': 0.8195836545875097}  | {'accuracy': 0.8128} |
| 0.0           | 485.0 | 3395 | 1.3735          | {'f1': 0.8201383551114528}  | {'accuracy': 0.8128} |
| 0.0           | 486.0 | 3402 | 1.3764          | {'f1': 0.8216340621403913}  | {'accuracy': 0.814}  |
| 0.0           | 487.0 | 3409 | 1.3759          | {'f1': 0.8216340621403913}  | {'accuracy': 0.814}  |
| 0.0           | 488.0 | 3416 | 1.3750          | {'f1': 0.8211818879508825}  | {'accuracy': 0.8136} |
| 0.0           | 489.0 | 3423 | 1.3743          | {'f1': 0.8207293666026871}  | {'accuracy': 0.8132} |
| 0.0           | 490.0 | 3430 | 1.3739          | {'f1': 0.8207293666026871}  | {'accuracy': 0.8132} |
| 0.0           | 491.0 | 3437 | 1.3746          | {'f1': 0.8211818879508825}  | {'accuracy': 0.8136} |
| 0.0           | 492.0 | 3444 | 1.3754          | {'f1': 0.8211818879508825}  | {'accuracy': 0.8136} |
| 0.0           | 493.0 | 3451 | 1.3755          | {'f1': 0.8211818879508825}  | {'accuracy': 0.8136} |
| 0.0           | 494.0 | 3458 | 1.3754          | {'f1': 0.8211818879508825}  | {'accuracy': 0.8136} |
| 0.0           | 495.0 | 3465 | 1.3753          | {'f1': 0.8211818879508825}  | {'accuracy': 0.8136} |
| 0.0           | 496.0 | 3472 | 1.3751          | {'f1': 0.8211818879508825}  | {'accuracy': 0.8136} |
| 0.0           | 497.0 | 3479 | 1.3749          | {'f1': 0.8211818879508825}  | {'accuracy': 0.8136} |
| 0.0           | 498.0 | 3486 | 1.3746          | {'f1': 0.8207293666026871}  | {'accuracy': 0.8132} |
| 0.0           | 499.0 | 3493 | 1.3743          | {'f1': 0.8207293666026871}  | {'accuracy': 0.8132} |
| 0.0           | 500.0 | 3500 | 1.3742          | {'f1': 0.8207293666026871}  | {'accuracy': 0.8132} |


### Framework versions

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