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_16_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_16_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: 1.4509
- F1: {'f1': 0.795623290347792}
- Accuracy: {'accuracy': 0.7908}

## 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    | 0.6989          | {'f1': 0.5576858392196434}  | {'accuracy': 0.474}  |
| No log        | 2.0   | 14   | 0.6959          | {'f1': 0.3558974358974359}  | {'accuracy': 0.4976} |
| No log        | 3.0   | 21   | 0.6937          | {'f1': 0.20887728459530028} | {'accuracy': 0.5152} |
| No log        | 4.0   | 28   | 0.6882          | {'f1': 0.29038112522686027} | {'accuracy': 0.5308} |
| No log        | 5.0   | 35   | 0.6813          | {'f1': 0.4042780748663102}  | {'accuracy': 0.5544} |
| No log        | 6.0   | 42   | 0.6713          | {'f1': 0.6004008016032063}  | {'accuracy': 0.6012} |
| No log        | 7.0   | 49   | 0.6636          | {'f1': 0.5108481262327416}  | {'accuracy': 0.6032} |
| No log        | 8.0   | 56   | 0.6479          | {'f1': 0.5741583257506825}  | {'accuracy': 0.6256} |
| No log        | 9.0   | 63   | 0.6377          | {'f1': 0.5568776772965255}  | {'accuracy': 0.6276} |
| No log        | 10.0  | 70   | 0.6173          | {'f1': 0.6251082251082252}  | {'accuracy': 0.6536} |
| No log        | 11.0  | 77   | 0.6139          | {'f1': 0.6412017167381974}  | {'accuracy': 0.6656} |
| No log        | 12.0  | 84   | 0.6046          | {'f1': 0.6773136773136773}  | {'accuracy': 0.6848} |
| No log        | 13.0  | 91   | 0.5947          | {'f1': 0.699759807846277}   | {'accuracy': 0.7}    |
| No log        | 14.0  | 98   | 0.6145          | {'f1': 0.7012882447665056}  | {'accuracy': 0.7032} |
| No log        | 15.0  | 105  | 0.6231          | {'f1': 0.7110036275695284}  | {'accuracy': 0.7132} |
| No log        | 16.0  | 112  | 0.6193          | {'f1': 0.7321981424148607}  | {'accuracy': 0.7232} |
| No log        | 17.0  | 119  | 0.6490          | {'f1': 0.7197986577181208}  | {'accuracy': 0.7328} |
| No log        | 18.0  | 126  | 0.7302          | {'f1': 0.7480501865038997}  | {'accuracy': 0.7028} |
| No log        | 19.0  | 133  | 0.6882          | {'f1': 0.7303042934556065}  | {'accuracy': 0.7412} |
| No log        | 20.0  | 140  | 0.7858          | {'f1': 0.7411965811965813}  | {'accuracy': 0.6972} |
| No log        | 21.0  | 147  | 0.7169          | {'f1': 0.7423167848699764}  | {'accuracy': 0.7384} |
| No log        | 22.0  | 154  | 0.7337          | {'f1': 0.7538699690402476}  | {'accuracy': 0.7456} |
| No log        | 23.0  | 161  | 0.7640          | {'f1': 0.7517455391776571}  | {'accuracy': 0.744}  |
| No log        | 24.0  | 168  | 0.7882          | {'f1': 0.7474747474747474}  | {'accuracy': 0.75}   |
| No log        | 25.0  | 175  | 0.8841          | {'f1': 0.7670275934334614}  | {'accuracy': 0.7332} |
| No log        | 26.0  | 182  | 0.8158          | {'f1': 0.7625391849529781}  | {'accuracy': 0.7576} |
| No log        | 27.0  | 189  | 0.8408          | {'f1': 0.7698113207547169}  | {'accuracy': 0.756}  |
| No log        | 28.0  | 196  | 0.8525          | {'f1': 0.7698776758409785}  | {'accuracy': 0.7592} |
| No log        | 29.0  | 203  | 0.9124          | {'f1': 0.7715959004392385}  | {'accuracy': 0.7504} |
| No log        | 30.0  | 210  | 0.8864          | {'f1': 0.7682737169517886}  | {'accuracy': 0.7616} |
| No log        | 31.0  | 217  | 0.9029          | {'f1': 0.7697063369397218}  | {'accuracy': 0.7616} |
| No log        | 32.0  | 224  | 1.0050          | {'f1': 0.7792022792022792}  | {'accuracy': 0.752}  |
| No log        | 33.0  | 231  | 0.9465          | {'f1': 0.7596834652228238}  | {'accuracy': 0.7692} |
| No log        | 34.0  | 238  | 0.9308          | {'f1': 0.7711797307996834}  | {'accuracy': 0.7688} |
| No log        | 35.0  | 245  | 0.9586          | {'f1': 0.7802321228004493}  | {'accuracy': 0.7652} |
| No log        | 36.0  | 252  | 0.9790          | {'f1': 0.7811921510551647}  | {'accuracy': 0.7636} |
| No log        | 37.0  | 259  | 1.0231          | {'f1': 0.7810351067680059}  | {'accuracy': 0.758}  |
| No log        | 38.0  | 266  | 0.9654          | {'f1': 0.7820464054773678}  | {'accuracy': 0.7708} |
| No log        | 39.0  | 273  | 0.9940          | {'f1': 0.7839940718784735}  | {'accuracy': 0.7668} |
| No log        | 40.0  | 280  | 1.0142          | {'f1': 0.781524926686217}   | {'accuracy': 0.7616} |
| No log        | 41.0  | 287  | 0.9734          | {'f1': 0.7821401077752117}  | {'accuracy': 0.7736} |
| No log        | 42.0  | 294  | 1.0272          | {'f1': 0.7828947368421054}  | {'accuracy': 0.7624} |
| No log        | 43.0  | 301  | 1.1120          | {'f1': 0.78005657708628}    | {'accuracy': 0.7512} |
| No log        | 44.0  | 308  | 0.9847          | {'f1': 0.7783094098883573}  | {'accuracy': 0.7776} |
| No log        | 45.0  | 315  | 1.1667          | {'f1': 0.7783558792924037}  | {'accuracy': 0.7444} |
| No log        | 46.0  | 322  | 0.9812          | {'f1': 0.7874509803921568}  | {'accuracy': 0.7832} |
| No log        | 47.0  | 329  | 0.9943          | {'f1': 0.7906441717791411}  | {'accuracy': 0.7816} |
| No log        | 48.0  | 336  | 1.0160          | {'f1': 0.7903650733910426}  | {'accuracy': 0.7772} |
| No log        | 49.0  | 343  | 0.9967          | {'f1': 0.7893903404592241}  | {'accuracy': 0.7872} |
| No log        | 50.0  | 350  | 1.0146          | {'f1': 0.7908571428571428}  | {'accuracy': 0.7804} |
| No log        | 51.0  | 357  | 1.2253          | {'f1': 0.7803187803187804}  | {'accuracy': 0.7464} |
| No log        | 52.0  | 364  | 1.1539          | {'f1': 0.7857651245551601}  | {'accuracy': 0.7592} |
| No log        | 53.0  | 371  | 1.0245          | {'f1': 0.7900466562986004}  | {'accuracy': 0.784}  |
| No log        | 54.0  | 378  | 1.0217          | {'f1': 0.7878545745105873}  | {'accuracy': 0.7876} |
| No log        | 55.0  | 385  | 1.0649          | {'f1': 0.7927056196501675}  | {'accuracy': 0.7772} |
| No log        | 56.0  | 392  | 1.0459          | {'f1': 0.7894937190711839}  | {'accuracy': 0.7788} |
| No log        | 57.0  | 399  | 1.0372          | {'f1': 0.7898832684824902}  | {'accuracy': 0.784}  |
| No log        | 58.0  | 406  | 1.0391          | {'f1': 0.78984375}          | {'accuracy': 0.7848} |
| No log        | 59.0  | 413  | 1.0456          | {'f1': 0.7893106119287374}  | {'accuracy': 0.7824} |
| No log        | 60.0  | 420  | 1.0520          | {'f1': 0.7903039630627166}  | {'accuracy': 0.782}  |
| No log        | 61.0  | 427  | 1.0643          | {'f1': 0.7903963414634146}  | {'accuracy': 0.78}   |
| No log        | 62.0  | 434  | 1.0581          | {'f1': 0.7901802838511699}  | {'accuracy': 0.7812} |
| No log        | 63.0  | 441  | 1.0626          | {'f1': 0.7914110429447851}  | {'accuracy': 0.7824} |
| No log        | 64.0  | 448  | 1.0688          | {'f1': 0.7949599083619702}  | {'accuracy': 0.7852} |
| No log        | 65.0  | 455  | 1.0655          | {'f1': 0.7936507936507937}  | {'accuracy': 0.7868} |
| No log        | 66.0  | 462  | 1.4237          | {'f1': 0.7764705882352941}  | {'accuracy': 0.734}  |
| No log        | 67.0  | 469  | 1.1680          | {'f1': 0.7911530094271211}  | {'accuracy': 0.7696} |
| No log        | 68.0  | 476  | 1.0930          | {'f1': 0.7932618683001532}  | {'accuracy': 0.784}  |
| No log        | 69.0  | 483  | 1.0860          | {'f1': 0.7917981072555204}  | {'accuracy': 0.7888} |
| No log        | 70.0  | 490  | 1.0901          | {'f1': 0.7907899960301707}  | {'accuracy': 0.7892} |
| No log        | 71.0  | 497  | 1.0984          | {'f1': 0.7927300850734724}  | {'accuracy': 0.7856} |
| 0.1314        | 72.0  | 504  | 1.1386          | {'f1': 0.7922272047832587}  | {'accuracy': 0.7776} |
| 0.1314        | 73.0  | 511  | 1.1201          | {'f1': 0.7810309278350516}  | {'accuracy': 0.7876} |
| 0.1314        | 74.0  | 518  | 1.1620          | {'f1': 0.7892607576314822}  | {'accuracy': 0.7708} |
| 0.1314        | 75.0  | 525  | 1.2650          | {'f1': 0.7887624466571835}  | {'accuracy': 0.7624} |
| 0.1314        | 76.0  | 532  | 1.2139          | {'f1': 0.7917570498915402}  | {'accuracy': 0.7696} |
| 0.1314        | 77.0  | 539  | 1.1546          | {'f1': 0.7930904994367254}  | {'accuracy': 0.7796} |
| 0.1314        | 78.0  | 546  | 1.1401          | {'f1': 0.7948229920060906}  | {'accuracy': 0.7844} |
| 0.1314        | 79.0  | 553  | 1.1279          | {'f1': 0.7967161845191557}  | {'accuracy': 0.792}  |
| 0.1314        | 80.0  | 560  | 1.1326          | {'f1': 0.7880741337630943}  | {'accuracy': 0.7896} |
| 0.1314        | 81.0  | 567  | 1.1339          | {'f1': 0.790548658390068}   | {'accuracy': 0.7908} |
| 0.1314        | 82.0  | 574  | 1.1349          | {'f1': 0.7938144329896908}  | {'accuracy': 0.792}  |
| 0.1314        | 83.0  | 581  | 1.1369          | {'f1': 0.793713163064833}   | {'accuracy': 0.79}   |
| 0.1314        | 84.0  | 588  | 1.1434          | {'f1': 0.7972136222910217}  | {'accuracy': 0.7904} |
| 0.1314        | 85.0  | 595  | 1.1554          | {'f1': 0.7945101029355699}  | {'accuracy': 0.7844} |
| 0.1314        | 86.0  | 602  | 1.1637          | {'f1': 0.7942402425161046}  | {'accuracy': 0.7828} |
| 0.1314        | 87.0  | 609  | 1.1688          | {'f1': 0.7933509633547412}  | {'accuracy': 0.7812} |
| 0.1314        | 88.0  | 616  | 1.1697          | {'f1': 0.7934947049924357}  | {'accuracy': 0.7816} |
| 0.1314        | 89.0  | 623  | 1.1627          | {'f1': 0.7945205479452054}  | {'accuracy': 0.784}  |
| 0.1314        | 90.0  | 630  | 1.1591          | {'f1': 0.7943425076452599}  | {'accuracy': 0.7848} |
| 0.1314        | 91.0  | 637  | 1.1593          | {'f1': 0.7946462715105163}  | {'accuracy': 0.7852} |
| 0.1314        | 92.0  | 644  | 1.1609          | {'f1': 0.7946462715105163}  | {'accuracy': 0.7852} |
| 0.1314        | 93.0  | 651  | 1.1630          | {'f1': 0.7940389759266335}  | {'accuracy': 0.7844} |
| 0.1314        | 94.0  | 658  | 1.1652          | {'f1': 0.7937356760886172}  | {'accuracy': 0.784}  |
| 0.1314        | 95.0  | 665  | 1.1745          | {'f1': 0.7945309532852259}  | {'accuracy': 0.7836} |
| 0.1314        | 96.0  | 672  | 1.1740          | {'f1': 0.7954372623574144}  | {'accuracy': 0.7848} |
| 0.1314        | 97.0  | 679  | 1.1792          | {'f1': 0.795144157814871}   | {'accuracy': 0.784}  |
| 0.1314        | 98.0  | 686  | 1.1818          | {'f1': 0.7940953822861468}  | {'accuracy': 0.7824} |
| 0.1314        | 99.0  | 693  | 1.1840          | {'f1': 0.7945516458569807}  | {'accuracy': 0.7828} |
| 0.1314        | 100.0 | 700  | 1.1871          | {'f1': 0.7927519818799548}  | {'accuracy': 0.7804} |
| 0.1314        | 101.0 | 707  | 1.1823          | {'f1': 0.7957479119210327}  | {'accuracy': 0.7848} |
| 0.1314        | 102.0 | 714  | 1.1863          | {'f1': 0.7942402425161046}  | {'accuracy': 0.7828} |
| 0.1314        | 103.0 | 721  | 1.1918          | {'f1': 0.7930513595166163}  | {'accuracy': 0.7808} |
| 0.1314        | 104.0 | 728  | 1.1911          | {'f1': 0.7937949300037835}  | {'accuracy': 0.782}  |
| 0.1314        | 105.0 | 735  | 1.1899          | {'f1': 0.7942402425161046}  | {'accuracy': 0.7828} |
| 0.1314        | 106.0 | 742  | 1.1899          | {'f1': 0.794541319181198}   | {'accuracy': 0.7832} |
| 0.1314        | 107.0 | 749  | 1.2050          | {'f1': 0.7917448405253283}  | {'accuracy': 0.778}  |
| 0.1314        | 108.0 | 756  | 1.2009          | {'f1': 0.7927656367746798}  | {'accuracy': 0.78}   |
| 0.1314        | 109.0 | 763  | 1.1883          | {'f1': 0.7961904761904762}  | {'accuracy': 0.786}  |
| 0.1314        | 110.0 | 770  | 1.1846          | {'f1': 0.7966231772831925}  | {'accuracy': 0.788}  |
| 0.1314        | 111.0 | 777  | 1.1764          | {'f1': 0.7963836477987422}  | {'accuracy': 0.7928} |
| 0.1314        | 112.0 | 784  | 1.1790          | {'f1': 0.7925129430505774}  | {'accuracy': 0.7916} |
| 0.1314        | 113.0 | 791  | 1.1812          | {'f1': 0.7912175648702595}  | {'accuracy': 0.7908} |
| 0.1314        | 114.0 | 798  | 1.1818          | {'f1': 0.7946074544012688}  | {'accuracy': 0.7928} |
| 0.1314        | 115.0 | 805  | 1.2656          | {'f1': 0.7910883856829803}  | {'accuracy': 0.7712} |
| 0.1314        | 116.0 | 812  | 1.3465          | {'f1': 0.7908799429996437}  | {'accuracy': 0.7652} |
| 0.1314        | 117.0 | 819  | 1.3676          | {'f1': 0.7467619472979008}  | {'accuracy': 0.7732} |
| 0.1314        | 118.0 | 826  | 1.1959          | {'f1': 0.793343653250774}   | {'accuracy': 0.7864} |
| 0.1314        | 119.0 | 833  | 1.7826          | {'f1': 0.7632348164988633}  | {'accuracy': 0.7084} |
| 0.1314        | 120.0 | 840  | 1.3750          | {'f1': 0.7883315546069015}  | {'accuracy': 0.762}  |
| 0.1314        | 121.0 | 847  | 1.3752          | {'f1': 0.7448397013614404}  | {'accuracy': 0.7676} |
| 0.1314        | 122.0 | 854  | 1.3570          | {'f1': 0.7528187337380745}  | {'accuracy': 0.772}  |
| 0.1314        | 123.0 | 861  | 1.2615          | {'f1': 0.7824412783981518}  | {'accuracy': 0.774}  |
| 0.1314        | 124.0 | 868  | 1.4186          | {'f1': 0.784062611170402}   | {'accuracy': 0.7572} |
| 0.1314        | 125.0 | 875  | 1.3408          | {'f1': 0.7841409691629957}  | {'accuracy': 0.7648} |
| 0.1314        | 126.0 | 882  | 1.2820          | {'f1': 0.7837014470677838}  | {'accuracy': 0.7728} |
| 0.1314        | 127.0 | 889  | 1.2712          | {'f1': 0.7812133072407045}  | {'accuracy': 0.7764} |
| 0.1314        | 128.0 | 896  | 1.2721          | {'f1': 0.7791898332009531}  | {'accuracy': 0.7776} |
| 0.1314        | 129.0 | 903  | 1.2767          | {'f1': 0.7793880837359098}  | {'accuracy': 0.7808} |
| 0.1314        | 130.0 | 910  | 1.2776          | {'f1': 0.7798792756539236}  | {'accuracy': 0.7812} |
| 0.1314        | 131.0 | 917  | 1.2761          | {'f1': 0.7800399201596806}  | {'accuracy': 0.7796} |
| 0.1314        | 132.0 | 924  | 1.2763          | {'f1': 0.7783955520254171}  | {'accuracy': 0.7768} |
| 0.1314        | 133.0 | 931  | 1.2775          | {'f1': 0.7808326787117046}  | {'accuracy': 0.7768} |
| 0.1314        | 134.0 | 938  | 1.2832          | {'f1': 0.783113865220759}   | {'accuracy': 0.776}  |
| 0.1314        | 135.0 | 945  | 1.2875          | {'f1': 0.7847516365036581}  | {'accuracy': 0.7764} |
| 0.1314        | 136.0 | 952  | 1.2848          | {'f1': 0.783113865220759}   | {'accuracy': 0.776}  |
| 0.1314        | 137.0 | 959  | 1.2817          | {'f1': 0.7817614964925955}  | {'accuracy': 0.776}  |
| 0.1314        | 138.0 | 966  | 1.2795          | {'f1': 0.782472613458529}   | {'accuracy': 0.7776} |
| 0.1314        | 139.0 | 973  | 1.2813          | {'f1': 0.7837943124269575}  | {'accuracy': 0.778}  |
| 0.1314        | 140.0 | 980  | 1.2845          | {'f1': 0.7849670670282836}  | {'accuracy': 0.778}  |
| 0.1314        | 141.0 | 987  | 1.2940          | {'f1': 0.7870476190476191}  | {'accuracy': 0.7764} |
| 0.1314        | 142.0 | 994  | 1.3119          | {'f1': 0.7866014301844184}  | {'accuracy': 0.7732} |
| 0.0011        | 143.0 | 1001 | 1.3219          | {'f1': 0.7857677902621724}  | {'accuracy': 0.7712} |
| 0.0011        | 144.0 | 1008 | 1.3216          | {'f1': 0.7860621955788686}  | {'accuracy': 0.7716} |
| 0.0011        | 145.0 | 1015 | 1.3180          | {'f1': 0.7864661654135338}  | {'accuracy': 0.7728} |
| 0.0011        | 146.0 | 1022 | 1.2972          | {'f1': 0.7888507063764795}  | {'accuracy': 0.7788} |
| 0.0011        | 147.0 | 1029 | 1.2832          | {'f1': 0.7831893165750198}  | {'accuracy': 0.7792} |
| 0.0011        | 148.0 | 1036 | 1.2828          | {'f1': 0.7818471337579618}  | {'accuracy': 0.7808} |
| 0.0011        | 149.0 | 1043 | 1.2832          | {'f1': 0.7818471337579618}  | {'accuracy': 0.7808} |
| 0.0011        | 150.0 | 1050 | 1.2842          | {'f1': 0.7844827586206896}  | {'accuracy': 0.78}   |
| 0.0011        | 151.0 | 1057 | 1.2883          | {'f1': 0.7882307394502517}  | {'accuracy': 0.7812} |
| 0.0011        | 152.0 | 1064 | 1.2936          | {'f1': 0.7872258560984994}  | {'accuracy': 0.7788} |
| 0.0011        | 153.0 | 1071 | 1.2996          | {'f1': 0.7885496183206105}  | {'accuracy': 0.7784} |
| 0.0011        | 154.0 | 1078 | 1.3017          | {'f1': 0.7890118275467379}  | {'accuracy': 0.7788} |
| 0.0011        | 155.0 | 1085 | 1.3029          | {'f1': 0.7890118275467379}  | {'accuracy': 0.7788} |
| 0.0011        | 156.0 | 1092 | 1.3046          | {'f1': 0.7896341463414634}  | {'accuracy': 0.7792} |
| 0.0011        | 157.0 | 1099 | 1.3024          | {'f1': 0.7894535727932748}  | {'accuracy': 0.7796} |
| 0.0011        | 158.0 | 1106 | 1.3025          | {'f1': 0.7895944912012243}  | {'accuracy': 0.78}   |
| 0.0011        | 159.0 | 1113 | 1.3031          | {'f1': 0.7895944912012243}  | {'accuracy': 0.78}   |
| 0.0011        | 160.0 | 1120 | 1.3056          | {'f1': 0.7902364607170099}  | {'accuracy': 0.78}   |
| 0.0011        | 161.0 | 1127 | 1.3088          | {'f1': 0.7913340935005702}  | {'accuracy': 0.7804} |
| 0.0011        | 162.0 | 1134 | 1.3108          | {'f1': 0.7904328018223236}  | {'accuracy': 0.7792} |
| 0.0011        | 163.0 | 1141 | 1.3081          | {'f1': 0.7902364607170099}  | {'accuracy': 0.78}   |
| 0.0011        | 164.0 | 1148 | 1.3071          | {'f1': 0.7888507063764795}  | {'accuracy': 0.7788} |
| 0.0011        | 165.0 | 1155 | 1.3060          | {'f1': 0.7891104294478529}  | {'accuracy': 0.78}   |
| 0.0011        | 166.0 | 1162 | 1.3071          | {'f1': 0.7888079724032196}  | {'accuracy': 0.7796} |
| 0.0011        | 167.0 | 1169 | 1.3099          | {'f1': 0.7888507063764795}  | {'accuracy': 0.7788} |
| 0.0011        | 168.0 | 1176 | 1.3124          | {'f1': 0.7897748950782144}  | {'accuracy': 0.7796} |
| 0.0011        | 169.0 | 1183 | 1.3143          | {'f1': 0.791158536585366}   | {'accuracy': 0.7808} |
| 0.0011        | 170.0 | 1190 | 1.3156          | {'f1': 0.7905559786747907}  | {'accuracy': 0.78}   |
| 0.0011        | 171.0 | 1197 | 1.3233          | {'f1': 0.7895335608646189}  | {'accuracy': 0.778}  |
| 0.0011        | 172.0 | 1204 | 1.3404          | {'f1': 0.7885843034171987}  | {'accuracy': 0.7748} |
| 0.0011        | 173.0 | 1211 | 1.3476          | {'f1': 0.789689951438177}   | {'accuracy': 0.7748} |
| 0.0011        | 174.0 | 1218 | 1.3488          | {'f1': 0.7717842323651453}  | {'accuracy': 0.78}   |
| 0.0011        | 175.0 | 1225 | 1.5156          | {'f1': 0.7329469460543914}  | {'accuracy': 0.7604} |
| 0.0011        | 176.0 | 1232 | 1.4279          | {'f1': 0.7597097737942808}  | {'accuracy': 0.7748} |
| 0.0011        | 177.0 | 1239 | 1.3662          | {'f1': 0.7785493827160495}  | {'accuracy': 0.7704} |
| 0.0011        | 178.0 | 1246 | 1.4237          | {'f1': 0.7834135505368381}  | {'accuracy': 0.766}  |
| 0.0011        | 179.0 | 1253 | 1.4623          | {'f1': 0.7840991976659373}  | {'accuracy': 0.7632} |
| 0.0011        | 180.0 | 1260 | 1.4648          | {'f1': 0.7838133430550492}  | {'accuracy': 0.7628} |
| 0.0011        | 181.0 | 1267 | 1.4449          | {'f1': 0.7849779086892489}  | {'accuracy': 0.7664} |
| 0.0011        | 182.0 | 1274 | 1.4326          | {'f1': 0.7832530566876621}  | {'accuracy': 0.766}  |
| 0.0011        | 183.0 | 1281 | 1.4211          | {'f1': 0.7855007473841554}  | {'accuracy': 0.7704} |
| 0.0011        | 184.0 | 1288 | 1.4065          | {'f1': 0.7847719562759141}  | {'accuracy': 0.7716} |
| 0.0011        | 185.0 | 1295 | 1.3939          | {'f1': 0.7822458270106222}  | {'accuracy': 0.7704} |
| 0.0011        | 186.0 | 1302 | 1.3858          | {'f1': 0.782375478927203}   | {'accuracy': 0.7728} |
| 0.0011        | 187.0 | 1309 | 1.3835          | {'f1': 0.7807692307692309}  | {'accuracy': 0.772}  |
| 0.0011        | 188.0 | 1316 | 1.3836          | {'f1': 0.7813702848344881}  | {'accuracy': 0.7728} |
| 0.0011        | 189.0 | 1323 | 1.3812          | {'f1': 0.7786790266512167}  | {'accuracy': 0.7708} |
| 0.0011        | 190.0 | 1330 | 1.3815          | {'f1': 0.7805630543771693}  | {'accuracy': 0.7724} |
| 0.0011        | 191.0 | 1337 | 1.3819          | {'f1': 0.7810331534309947}  | {'accuracy': 0.7728} |
| 0.0011        | 192.0 | 1344 | 1.3820          | {'f1': 0.7810331534309947}  | {'accuracy': 0.7728} |
| 0.0011        | 193.0 | 1351 | 1.3816          | {'f1': 0.7805630543771693}  | {'accuracy': 0.7724} |
| 0.0011        | 194.0 | 1358 | 1.3819          | {'f1': 0.7810331534309947}  | {'accuracy': 0.7728} |
| 0.0011        | 195.0 | 1365 | 1.3824          | {'f1': 0.7810331534309947}  | {'accuracy': 0.7728} |
| 0.0011        | 196.0 | 1372 | 1.3828          | {'f1': 0.7810331534309947}  | {'accuracy': 0.7728} |
| 0.0011        | 197.0 | 1379 | 1.3831          | {'f1': 0.7815028901734103}  | {'accuracy': 0.7732} |
| 0.0011        | 198.0 | 1386 | 1.3838          | {'f1': 0.7815028901734103}  | {'accuracy': 0.7732} |
| 0.0011        | 199.0 | 1393 | 1.3842          | {'f1': 0.7815028901734103}  | {'accuracy': 0.7732} |
| 0.0011        | 200.0 | 1400 | 1.3841          | {'f1': 0.7799227799227799}  | {'accuracy': 0.772}  |
| 0.0011        | 201.0 | 1407 | 1.3854          | {'f1': 0.7815028901734103}  | {'accuracy': 0.7732} |
| 0.0011        | 202.0 | 1414 | 1.3869          | {'f1': 0.7824412783981518}  | {'accuracy': 0.774}  |
| 0.0011        | 203.0 | 1421 | 1.3891          | {'f1': 0.7821744141375336}  | {'accuracy': 0.7732} |
| 0.0011        | 204.0 | 1428 | 1.3911          | {'f1': 0.7822085889570553}  | {'accuracy': 0.7728} |
| 0.0011        | 205.0 | 1435 | 1.3919          | {'f1': 0.7828418230563002}  | {'accuracy': 0.7732} |
| 0.0011        | 206.0 | 1442 | 1.3930          | {'f1': 0.7833078101071975}  | {'accuracy': 0.7736} |
| 0.0011        | 207.0 | 1449 | 1.3940          | {'f1': 0.784238714613619}   | {'accuracy': 0.7744} |
| 0.0011        | 208.0 | 1456 | 1.3946          | {'f1': 0.7839388145315488}  | {'accuracy': 0.774}  |
| 0.0011        | 209.0 | 1463 | 1.3936          | {'f1': 0.7833078101071975}  | {'accuracy': 0.7736} |
| 0.0011        | 210.0 | 1470 | 1.3952          | {'f1': 0.784868169659916}   | {'accuracy': 0.7748} |
| 0.0011        | 211.0 | 1477 | 1.3972          | {'f1': 0.7844334223578787}  | {'accuracy': 0.774}  |
| 0.0011        | 212.0 | 1484 | 1.3983          | {'f1': 0.7847619047619048}  | {'accuracy': 0.774}  |
| 0.0011        | 213.0 | 1491 | 1.3995          | {'f1': 0.7847619047619048}  | {'accuracy': 0.774}  |
| 0.0011        | 214.0 | 1498 | 1.4000          | {'f1': 0.7852246763137853}  | {'accuracy': 0.7744} |
| 0.0001        | 215.0 | 1505 | 1.4006          | {'f1': 0.7852246763137853}  | {'accuracy': 0.7744} |
| 0.0001        | 216.0 | 1512 | 1.4018          | {'f1': 0.7858501331304678}  | {'accuracy': 0.7748} |
| 0.0001        | 217.0 | 1519 | 1.3886          | {'f1': 0.7771381578947368}  | {'accuracy': 0.7832} |
| 0.0001        | 218.0 | 1526 | 1.4134          | {'f1': 0.7666243117323168}  | {'accuracy': 0.7796} |
| 0.0001        | 219.0 | 1533 | 1.3959          | {'f1': 0.7732435843500212}  | {'accuracy': 0.7844} |
| 0.0001        | 220.0 | 1540 | 1.3611          | {'f1': 0.7795632468067573}  | {'accuracy': 0.786}  |
| 0.0001        | 221.0 | 1547 | 1.3446          | {'f1': 0.7798946088366437}  | {'accuracy': 0.7828} |
| 0.0001        | 222.0 | 1554 | 1.3378          | {'f1': 0.7845786963434022}  | {'accuracy': 0.7832} |
| 0.0001        | 223.0 | 1561 | 1.3382          | {'f1': 0.7891637220259128}  | {'accuracy': 0.7852} |
| 0.0001        | 224.0 | 1568 | 1.3406          | {'f1': 0.7892271662763466}  | {'accuracy': 0.784}  |
| 0.0001        | 225.0 | 1575 | 1.3434          | {'f1': 0.7894327894327895}  | {'accuracy': 0.7832} |
| 0.0001        | 226.0 | 1582 | 1.3461          | {'f1': 0.7894736842105263}  | {'accuracy': 0.7824} |
| 0.0001        | 227.0 | 1589 | 1.3489          | {'f1': 0.7901234567901235}  | {'accuracy': 0.7824} |
| 0.0001        | 228.0 | 1596 | 1.3511          | {'f1': 0.79}                | {'accuracy': 0.7816} |
| 0.0001        | 229.0 | 1603 | 1.3536          | {'f1': 0.7910906298003072}  | {'accuracy': 0.7824} |
| 0.0001        | 230.0 | 1610 | 1.3557          | {'f1': 0.7900383141762451}  | {'accuracy': 0.7808} |
| 0.0001        | 231.0 | 1617 | 1.3575          | {'f1': 0.7901990811638592}  | {'accuracy': 0.7808} |
| 0.0001        | 232.0 | 1624 | 1.3600          | {'f1': 0.7916030534351144}  | {'accuracy': 0.7816} |
| 0.0001        | 233.0 | 1631 | 1.3606          | {'f1': 0.792064097672644}   | {'accuracy': 0.782}  |
| 0.0001        | 234.0 | 1638 | 1.3590          | {'f1': 0.7901990811638592}  | {'accuracy': 0.7808} |
| 0.0001        | 235.0 | 1645 | 1.3640          | {'f1': 0.7908571428571428}  | {'accuracy': 0.7804} |
| 0.0001        | 236.0 | 1652 | 1.4906          | {'f1': 0.7496700395952485}  | {'accuracy': 0.7724} |
| 0.0001        | 237.0 | 1659 | 1.4214          | {'f1': 0.763745704467354}   | {'accuracy': 0.78}   |
| 0.0001        | 238.0 | 1666 | 1.3359          | {'f1': 0.79293123319247}    | {'accuracy': 0.7844} |
| 0.0001        | 239.0 | 1673 | 1.4193          | {'f1': 0.7922457937088515}  | {'accuracy': 0.7728} |
| 0.0001        | 240.0 | 1680 | 1.3986          | {'f1': 0.7937800814513144}  | {'accuracy': 0.7772} |
| 0.0001        | 241.0 | 1687 | 1.3507          | {'f1': 0.7939814814814814}  | {'accuracy': 0.7864} |
| 0.0001        | 242.0 | 1694 | 1.3463          | {'f1': 0.7911915060951632}  | {'accuracy': 0.7876} |
| 0.0001        | 243.0 | 1701 | 1.3898          | {'f1': 0.770649895178197}   | {'accuracy': 0.7812} |
| 0.0001        | 244.0 | 1708 | 1.5725          | {'f1': 0.7329417080885677}  | {'accuracy': 0.7636} |
| 0.0001        | 245.0 | 1715 | 1.4878          | {'f1': 0.7962630255120373}  | {'accuracy': 0.7732} |
| 0.0001        | 246.0 | 1722 | 1.7124          | {'f1': 0.784688995215311}   | {'accuracy': 0.748}  |
| 0.0001        | 247.0 | 1729 | 1.6537          | {'f1': 0.7892190739460953}  | {'accuracy': 0.756}  |
| 0.0001        | 248.0 | 1736 | 1.4905          | {'f1': 0.7985585585585585}  | {'accuracy': 0.7764} |
| 0.0001        | 249.0 | 1743 | 1.4141          | {'f1': 0.7965722801788375}  | {'accuracy': 0.7816} |
| 0.0001        | 250.0 | 1750 | 1.3872          | {'f1': 0.7936387731919727}  | {'accuracy': 0.782}  |
| 0.0001        | 251.0 | 1757 | 1.3772          | {'f1': 0.7917620137299771}  | {'accuracy': 0.7816} |
| 0.0001        | 252.0 | 1764 | 1.3735          | {'f1': 0.7914274779946421}  | {'accuracy': 0.782}  |
| 0.0001        | 253.0 | 1771 | 1.3733          | {'f1': 0.7908045977011494}  | {'accuracy': 0.7816} |
| 0.0001        | 254.0 | 1778 | 1.3737          | {'f1': 0.790341126868532}   | {'accuracy': 0.7812} |
| 0.0001        | 255.0 | 1785 | 1.3743          | {'f1': 0.790341126868532}   | {'accuracy': 0.7812} |
| 0.0001        | 256.0 | 1792 | 1.3745          | {'f1': 0.790341126868532}   | {'accuracy': 0.7812} |
| 0.0001        | 257.0 | 1799 | 1.3748          | {'f1': 0.790341126868532}   | {'accuracy': 0.7812} |
| 0.0001        | 258.0 | 1806 | 1.4268          | {'f1': 0.7959791511541325}  | {'accuracy': 0.7808} |
| 0.0001        | 259.0 | 1813 | 1.5076          | {'f1': 0.7963898916967509}  | {'accuracy': 0.7744} |
| 0.0001        | 260.0 | 1820 | 1.5107          | {'f1': 0.7939372067845544}  | {'accuracy': 0.7716} |
| 0.0001        | 261.0 | 1827 | 1.4823          | {'f1': 0.7975236707938821}  | {'accuracy': 0.7776} |
| 0.0001        | 262.0 | 1834 | 1.4623          | {'f1': 0.7969151670951157}  | {'accuracy': 0.7788} |
| 0.0001        | 263.0 | 1841 | 1.4505          | {'f1': 0.7948243992606286}  | {'accuracy': 0.778}  |
| 0.0001        | 264.0 | 1848 | 1.4385          | {'f1': 0.7959866220735785}  | {'accuracy': 0.7804} |
| 0.0001        | 265.0 | 1855 | 1.4309          | {'f1': 0.7955223880597015}  | {'accuracy': 0.7808} |
| 0.0001        | 266.0 | 1862 | 1.4251          | {'f1': 0.7934008248968879}  | {'accuracy': 0.7796} |
| 0.0001        | 267.0 | 1869 | 1.4218          | {'f1': 0.7921833897031192}  | {'accuracy': 0.7788} |
| 0.0001        | 268.0 | 1876 | 1.4193          | {'f1': 0.79155672823219}    | {'accuracy': 0.7788} |
| 0.0001        | 269.0 | 1883 | 1.4154          | {'f1': 0.7924528301886793}  | {'accuracy': 0.78}   |
| 0.0001        | 270.0 | 1890 | 1.4131          | {'f1': 0.7922960725075529}  | {'accuracy': 0.78}   |
| 0.0001        | 271.0 | 1897 | 1.4115          | {'f1': 0.7928949357520786}  | {'accuracy': 0.7808} |
| 0.0001        | 272.0 | 1904 | 1.4094          | {'f1': 0.791981845688351}   | {'accuracy': 0.78}   |
| 0.0001        | 273.0 | 1911 | 1.4077          | {'f1': 0.7924242424242425}  | {'accuracy': 0.7808} |
| 0.0001        | 274.0 | 1918 | 1.4073          | {'f1': 0.7924242424242425}  | {'accuracy': 0.7808} |
| 0.0001        | 275.0 | 1925 | 1.4076          | {'f1': 0.7924242424242425}  | {'accuracy': 0.7808} |
| 0.0001        | 276.0 | 1932 | 1.4057          | {'f1': 0.7933257489571482}  | {'accuracy': 0.782}  |
| 0.0001        | 277.0 | 1939 | 1.4048          | {'f1': 0.7937713634637297}  | {'accuracy': 0.7828} |
| 0.0001        | 278.0 | 1946 | 1.4038          | {'f1': 0.7937713634637297}  | {'accuracy': 0.7828} |
| 0.0001        | 279.0 | 1953 | 1.4018          | {'f1': 0.7929984779299847}  | {'accuracy': 0.7824} |
| 0.0001        | 280.0 | 1960 | 1.3990          | {'f1': 0.7932875667429442}  | {'accuracy': 0.7832} |
| 0.0001        | 281.0 | 1967 | 1.3975          | {'f1': 0.7929717341482048}  | {'accuracy': 0.7832} |
| 0.0001        | 282.0 | 1974 | 1.3984          | {'f1': 0.7926689576174113}  | {'accuracy': 0.7828} |
| 0.0001        | 283.0 | 1981 | 1.4018          | {'f1': 0.7931428571428571}  | {'accuracy': 0.7828} |
| 0.0001        | 284.0 | 1988 | 1.4044          | {'f1': 0.7926968429060479}  | {'accuracy': 0.782}  |
| 0.0001        | 285.0 | 1995 | 1.4058          | {'f1': 0.7923954372623574}  | {'accuracy': 0.7816} |
| 0.0007        | 286.0 | 2002 | 1.4061          | {'f1': 0.7923954372623574}  | {'accuracy': 0.7816} |
| 0.0007        | 287.0 | 2009 | 1.4036          | {'f1': 0.7933003425961174}  | {'accuracy': 0.7828} |
| 0.0007        | 288.0 | 2016 | 1.4021          | {'f1': 0.7932875667429442}  | {'accuracy': 0.7832} |
| 0.0007        | 289.0 | 2023 | 1.4016          | {'f1': 0.7932875667429442}  | {'accuracy': 0.7832} |
| 0.0007        | 290.0 | 2030 | 1.4016          | {'f1': 0.7928271652041207}  | {'accuracy': 0.7828} |
| 0.0007        | 291.0 | 2037 | 1.4012          | {'f1': 0.7929717341482048}  | {'accuracy': 0.7832} |
| 0.0007        | 292.0 | 2044 | 1.4013          | {'f1': 0.7929717341482048}  | {'accuracy': 0.7832} |
| 0.0007        | 293.0 | 2051 | 1.4023          | {'f1': 0.7928271652041207}  | {'accuracy': 0.7828} |
| 0.0007        | 294.0 | 2058 | 1.4030          | {'f1': 0.7928271652041207}  | {'accuracy': 0.7828} |
| 0.0007        | 295.0 | 2065 | 1.4028          | {'f1': 0.7923664122137405}  | {'accuracy': 0.7824} |
| 0.0007        | 296.0 | 2072 | 1.4024          | {'f1': 0.7929717341482048}  | {'accuracy': 0.7832} |
| 0.0007        | 297.0 | 2079 | 1.4017          | {'f1': 0.7920489296636085}  | {'accuracy': 0.7824} |
| 0.0007        | 298.0 | 2086 | 1.4032          | {'f1': 0.7926689576174113}  | {'accuracy': 0.7828} |
| 0.0007        | 299.0 | 2093 | 1.4049          | {'f1': 0.7932875667429442}  | {'accuracy': 0.7832} |
| 0.0007        | 300.0 | 2100 | 1.4070          | {'f1': 0.7942073170731707}  | {'accuracy': 0.784}  |
| 0.0007        | 301.0 | 2107 | 1.4084          | {'f1': 0.7933003425961174}  | {'accuracy': 0.7828} |
| 0.0007        | 302.0 | 2114 | 1.4103          | {'f1': 0.7929984779299847}  | {'accuracy': 0.7824} |
| 0.0007        | 303.0 | 2121 | 1.4113          | {'f1': 0.7926968429060479}  | {'accuracy': 0.782}  |
| 0.0007        | 304.0 | 2128 | 1.4121          | {'f1': 0.7931558935361217}  | {'accuracy': 0.7824} |
| 0.0007        | 305.0 | 2135 | 1.4132          | {'f1': 0.7933130699088147}  | {'accuracy': 0.7824} |
| 0.0007        | 306.0 | 2142 | 1.4138          | {'f1': 0.7933130699088147}  | {'accuracy': 0.7824} |
| 0.0007        | 307.0 | 2149 | 1.4149          | {'f1': 0.7934700075930143}  | {'accuracy': 0.7824} |
| 0.0007        | 308.0 | 2156 | 1.4146          | {'f1': 0.7933130699088147}  | {'accuracy': 0.7824} |
| 0.0007        | 309.0 | 2163 | 1.4145          | {'f1': 0.7933130699088147}  | {'accuracy': 0.7824} |
| 0.0007        | 310.0 | 2170 | 1.4145          | {'f1': 0.7931558935361217}  | {'accuracy': 0.7824} |
| 0.0007        | 311.0 | 2177 | 1.4146          | {'f1': 0.7931558935361217}  | {'accuracy': 0.7824} |
| 0.0007        | 312.0 | 2184 | 1.4136          | {'f1': 0.7926968429060479}  | {'accuracy': 0.782}  |
| 0.0007        | 313.0 | 2191 | 1.4138          | {'f1': 0.7929984779299847}  | {'accuracy': 0.7824} |
| 0.0007        | 314.0 | 2198 | 1.4132          | {'f1': 0.7933003425961174}  | {'accuracy': 0.7828} |
| 0.0007        | 315.0 | 2205 | 1.3997          | {'f1': 0.7903039630627166}  | {'accuracy': 0.782}  |
| 0.0007        | 316.0 | 2212 | 1.3935          | {'f1': 0.7934908950019373}  | {'accuracy': 0.7868} |
| 0.0007        | 317.0 | 2219 | 1.3914          | {'f1': 0.79423226812159}    | {'accuracy': 0.7888} |
| 0.0007        | 318.0 | 2226 | 1.3912          | {'f1': 0.7943815840811549}  | {'accuracy': 0.7892} |
| 0.0007        | 319.0 | 2233 | 1.3916          | {'f1': 0.7943815840811549}  | {'accuracy': 0.7892} |
| 0.0007        | 320.0 | 2240 | 1.3921          | {'f1': 0.7940717628705148}  | {'accuracy': 0.7888} |
| 0.0007        | 321.0 | 2247 | 1.3930          | {'f1': 0.79423226812159}    | {'accuracy': 0.7888} |
| 0.0007        | 322.0 | 2254 | 1.3940          | {'f1': 0.7948618139353834}  | {'accuracy': 0.7892} |
| 0.0007        | 323.0 | 2261 | 1.3951          | {'f1': 0.7939464493597206}  | {'accuracy': 0.7876} |
| 0.0007        | 324.0 | 2268 | 1.3963          | {'f1': 0.7937984496124032}  | {'accuracy': 0.7872} |
| 0.0007        | 325.0 | 2275 | 1.3971          | {'f1': 0.7939581719597211}  | {'accuracy': 0.7872} |
| 0.0007        | 326.0 | 2282 | 1.3976          | {'f1': 0.7939581719597211}  | {'accuracy': 0.7872} |
| 0.0007        | 327.0 | 2289 | 1.3986          | {'f1': 0.7927300850734724}  | {'accuracy': 0.7856} |
| 0.0007        | 328.0 | 2296 | 1.3996          | {'f1': 0.7924236567452647}  | {'accuracy': 0.7852} |
| 0.0007        | 329.0 | 2303 | 1.4009          | {'f1': 0.7918115102356122}  | {'accuracy': 0.7844} |
| 0.0007        | 330.0 | 2310 | 1.3936          | {'f1': 0.7940717628705148}  | {'accuracy': 0.7888} |
| 0.0007        | 331.0 | 2317 | 1.3906          | {'f1': 0.7943262411347518}  | {'accuracy': 0.7912} |
| 0.0007        | 332.0 | 2324 | 1.4082          | {'f1': 0.7843942505133472}  | {'accuracy': 0.79}   |
| 0.0007        | 333.0 | 2331 | 1.4965          | {'f1': 0.7654427645788336}  | {'accuracy': 0.7828} |
| 0.0007        | 334.0 | 2338 | 1.4472          | {'f1': 0.7962756052141526}  | {'accuracy': 0.7812} |
| 0.0007        | 335.0 | 2345 | 1.8246          | {'f1': 0.7844594594594595}  | {'accuracy': 0.7448} |
| 0.0007        | 336.0 | 2352 | 1.4729          | {'f1': 0.7955637707948244}  | {'accuracy': 0.7788} |
| 0.0007        | 337.0 | 2359 | 1.4028          | {'f1': 0.7921662669864109}  | {'accuracy': 0.792}  |
| 0.0007        | 338.0 | 2366 | 1.4316          | {'f1': 0.7816377171215881}  | {'accuracy': 0.7888} |
| 0.0007        | 339.0 | 2373 | 1.4526          | {'f1': 0.776006711409396}   | {'accuracy': 0.7864} |
| 0.0007        | 340.0 | 2380 | 1.4467          | {'f1': 0.7761567319716548}  | {'accuracy': 0.7852} |
| 0.0007        | 341.0 | 2387 | 1.4355          | {'f1': 0.7806291390728477}  | {'accuracy': 0.788}  |
| 0.0007        | 342.0 | 2394 | 1.4260          | {'f1': 0.7837505129257283}  | {'accuracy': 0.7892} |
| 0.0007        | 343.0 | 2401 | 1.4213          | {'f1': 0.7861224489795918}  | {'accuracy': 0.7904} |
| 0.0007        | 344.0 | 2408 | 1.4110          | {'f1': 0.7934609250398725}  | {'accuracy': 0.7928} |
| 0.0007        | 345.0 | 2415 | 1.4141          | {'f1': 0.7943485086342229}  | {'accuracy': 0.7904} |
| 0.0007        | 346.0 | 2422 | 1.4232          | {'f1': 0.7927300850734724}  | {'accuracy': 0.7856} |
| 0.0007        | 347.0 | 2429 | 1.4409          | {'f1': 0.7940841865756542}  | {'accuracy': 0.7828} |
| 0.0007        | 348.0 | 2436 | 1.4519          | {'f1': 0.7929083364768013}  | {'accuracy': 0.7804} |
| 0.0007        | 349.0 | 2443 | 1.4572          | {'f1': 0.7923394667668042}  | {'accuracy': 0.7788} |
| 0.0007        | 350.0 | 2450 | 1.4591          | {'f1': 0.7929482370592649}  | {'accuracy': 0.7792} |
| 0.0007        | 351.0 | 2457 | 1.4579          | {'f1': 0.7923394667668042}  | {'accuracy': 0.7788} |
| 0.0007        | 352.0 | 2464 | 1.4567          | {'f1': 0.7926232593150169}  | {'accuracy': 0.7796} |
| 0.0007        | 353.0 | 2471 | 1.4555          | {'f1': 0.7927656367746798}  | {'accuracy': 0.78}   |
| 0.0007        | 354.0 | 2478 | 1.4544          | {'f1': 0.7930644553335846}  | {'accuracy': 0.7804} |
| 0.0007        | 355.0 | 2485 | 1.4542          | {'f1': 0.7926093514328808}  | {'accuracy': 0.78}   |
| 0.0007        | 356.0 | 2492 | 1.4542          | {'f1': 0.7926093514328808}  | {'accuracy': 0.78}   |
| 0.0007        | 357.0 | 2499 | 1.4540          | {'f1': 0.7926093514328808}  | {'accuracy': 0.78}   |
| 0.0007        | 358.0 | 2506 | 1.4528          | {'f1': 0.7929083364768013}  | {'accuracy': 0.7804} |
| 0.0007        | 359.0 | 2513 | 1.4517          | {'f1': 0.7935069837674594}  | {'accuracy': 0.7812} |
| 0.0007        | 360.0 | 2520 | 1.4514          | {'f1': 0.7930513595166163}  | {'accuracy': 0.7808} |
| 0.0007        | 361.0 | 2527 | 1.4512          | {'f1': 0.7933509633547412}  | {'accuracy': 0.7812} |
| 0.0007        | 362.0 | 2534 | 1.4511          | {'f1': 0.7933509633547412}  | {'accuracy': 0.7812} |
| 0.0007        | 363.0 | 2541 | 1.4511          | {'f1': 0.7933509633547412}  | {'accuracy': 0.7812} |
| 0.0007        | 364.0 | 2548 | 1.4509          | {'f1': 0.7931947069943289}  | {'accuracy': 0.7812} |
| 0.0007        | 365.0 | 2555 | 1.4510          | {'f1': 0.7931947069943289}  | {'accuracy': 0.7812} |
| 0.0007        | 366.0 | 2562 | 1.4512          | {'f1': 0.7931947069943289}  | {'accuracy': 0.7812} |
| 0.0007        | 367.0 | 2569 | 1.4513          | {'f1': 0.7931947069943289}  | {'accuracy': 0.7812} |
| 0.0007        | 368.0 | 2576 | 1.4521          | {'f1': 0.7936507936507937}  | {'accuracy': 0.7816} |
| 0.0007        | 369.0 | 2583 | 1.4525          | {'f1': 0.7933509633547412}  | {'accuracy': 0.7812} |
| 0.0007        | 370.0 | 2590 | 1.4527          | {'f1': 0.7933509633547412}  | {'accuracy': 0.7812} |
| 0.0007        | 371.0 | 2597 | 1.4526          | {'f1': 0.7931947069943289}  | {'accuracy': 0.7812} |
| 0.0007        | 372.0 | 2604 | 1.4527          | {'f1': 0.7931947069943289}  | {'accuracy': 0.7812} |
| 0.0007        | 373.0 | 2611 | 1.4523          | {'f1': 0.7931947069943289}  | {'accuracy': 0.7812} |
| 0.0007        | 374.0 | 2618 | 1.4521          | {'f1': 0.7934947049924357}  | {'accuracy': 0.7816} |
| 0.0007        | 375.0 | 2625 | 1.4521          | {'f1': 0.7934947049924357}  | {'accuracy': 0.7816} |
| 0.0007        | 376.0 | 2632 | 1.4522          | {'f1': 0.7934947049924357}  | {'accuracy': 0.7816} |
| 0.0007        | 377.0 | 2639 | 1.4522          | {'f1': 0.7937949300037835}  | {'accuracy': 0.782}  |
| 0.0007        | 378.0 | 2646 | 1.4500          | {'f1': 0.7936387731919727}  | {'accuracy': 0.782}  |
| 0.0007        | 379.0 | 2653 | 1.4484          | {'f1': 0.7943854324734447}  | {'accuracy': 0.7832} |
| 0.0007        | 380.0 | 2660 | 1.4490          | {'f1': 0.7940841865756542}  | {'accuracy': 0.7828} |
| 0.0007        | 381.0 | 2667 | 1.4501          | {'f1': 0.7937831690674755}  | {'accuracy': 0.7824} |
| 0.0007        | 382.0 | 2674 | 1.4526          | {'f1': 0.7933383800151401}  | {'accuracy': 0.7816} |
| 0.0007        | 383.0 | 2681 | 1.4539          | {'f1': 0.7937949300037835}  | {'accuracy': 0.782}  |
| 0.0007        | 384.0 | 2688 | 1.4547          | {'f1': 0.7934947049924357}  | {'accuracy': 0.7816} |
| 0.0007        | 385.0 | 2695 | 1.4551          | {'f1': 0.7934947049924357}  | {'accuracy': 0.7816} |
| 0.0007        | 386.0 | 2702 | 1.4548          | {'f1': 0.7934947049924357}  | {'accuracy': 0.7816} |
| 0.0007        | 387.0 | 2709 | 1.4544          | {'f1': 0.7937949300037835}  | {'accuracy': 0.782}  |
| 0.0007        | 388.0 | 2716 | 1.4573          | {'f1': 0.7933509633547412}  | {'accuracy': 0.7812} |
| 0.0007        | 389.0 | 2723 | 1.4598          | {'f1': 0.7935069837674594}  | {'accuracy': 0.7812} |
| 0.0007        | 390.0 | 2730 | 1.4606          | {'f1': 0.7935069837674594}  | {'accuracy': 0.7812} |
| 0.0007        | 391.0 | 2737 | 1.4607          | {'f1': 0.7935069837674594}  | {'accuracy': 0.7812} |
| 0.0007        | 392.0 | 2744 | 1.4618          | {'f1': 0.7929083364768013}  | {'accuracy': 0.7804} |
| 0.0007        | 393.0 | 2751 | 1.4636          | {'f1': 0.7923105917828872}  | {'accuracy': 0.7796} |
| 0.0007        | 394.0 | 2758 | 1.4640          | {'f1': 0.792467043314501}   | {'accuracy': 0.7796} |
| 0.0007        | 395.0 | 2765 | 1.4590          | {'f1': 0.7933509633547412}  | {'accuracy': 0.7812} |
| 0.0007        | 396.0 | 2772 | 1.4491          | {'f1': 0.796952380952381}   | {'accuracy': 0.7868} |
| 0.0007        | 397.0 | 2779 | 1.4451          | {'f1': 0.7954022988505747}  | {'accuracy': 0.7864} |
| 0.0007        | 398.0 | 2786 | 1.4437          | {'f1': 0.794783275795934}   | {'accuracy': 0.786}  |
| 0.0007        | 399.0 | 2793 | 1.4396          | {'f1': 0.7935285053929122}  | {'accuracy': 0.7856} |
| 0.0007        | 400.0 | 2800 | 1.4382          | {'f1': 0.7916505604947817}  | {'accuracy': 0.7844} |
| 0.0007        | 401.0 | 2807 | 1.4377          | {'f1': 0.7922630560928433}  | {'accuracy': 0.7852} |
| 0.0007        | 402.0 | 2814 | 1.4373          | {'f1': 0.7922630560928433}  | {'accuracy': 0.7852} |
| 0.0007        | 403.0 | 2821 | 1.4371          | {'f1': 0.7922630560928433}  | {'accuracy': 0.7852} |
| 0.0007        | 404.0 | 2828 | 1.4372          | {'f1': 0.7922630560928433}  | {'accuracy': 0.7852} |
| 0.0007        | 405.0 | 2835 | 1.4374          | {'f1': 0.7922630560928433}  | {'accuracy': 0.7852} |
| 0.0007        | 406.0 | 2842 | 1.4376          | {'f1': 0.7922630560928433}  | {'accuracy': 0.7852} |
| 0.0007        | 407.0 | 2849 | 1.4377          | {'f1': 0.7922630560928433}  | {'accuracy': 0.7852} |
| 0.0007        | 408.0 | 2856 | 1.4381          | {'f1': 0.7922630560928433}  | {'accuracy': 0.7852} |
| 0.0007        | 409.0 | 2863 | 1.4385          | {'f1': 0.7922630560928433}  | {'accuracy': 0.7852} |
| 0.0007        | 410.0 | 2870 | 1.4388          | {'f1': 0.7922630560928433}  | {'accuracy': 0.7852} |
| 0.0007        | 411.0 | 2877 | 1.4389          | {'f1': 0.7922630560928433}  | {'accuracy': 0.7852} |
| 0.0007        | 412.0 | 2884 | 1.4395          | {'f1': 0.7922630560928433}  | {'accuracy': 0.7852} |
| 0.0007        | 413.0 | 2891 | 1.4408          | {'f1': 0.7919722115013508}  | {'accuracy': 0.7844} |
| 0.0007        | 414.0 | 2898 | 1.4419          | {'f1': 0.7938342967244703}  | {'accuracy': 0.786}  |
| 0.0007        | 415.0 | 2905 | 1.4401          | {'f1': 0.7919566898685229}  | {'accuracy': 0.7848} |
| 0.0007        | 416.0 | 2912 | 1.4395          | {'f1': 0.7922630560928433}  | {'accuracy': 0.7852} |
| 0.0007        | 417.0 | 2919 | 1.4393          | {'f1': 0.7925696594427244}  | {'accuracy': 0.7856} |
| 0.0007        | 418.0 | 2926 | 1.4393          | {'f1': 0.7925696594427244}  | {'accuracy': 0.7856} |
| 0.0007        | 419.0 | 2933 | 1.4396          | {'f1': 0.7925696594427244}  | {'accuracy': 0.7856} |
| 0.0007        | 420.0 | 2940 | 1.4398          | {'f1': 0.7925696594427244}  | {'accuracy': 0.7856} |
| 0.0007        | 421.0 | 2947 | 1.4401          | {'f1': 0.7925696594427244}  | {'accuracy': 0.7856} |
| 0.0007        | 422.0 | 2954 | 1.4404          | {'f1': 0.7922630560928433}  | {'accuracy': 0.7852} |
| 0.0007        | 423.0 | 2961 | 1.4410          | {'f1': 0.7919566898685229}  | {'accuracy': 0.7848} |
| 0.0007        | 424.0 | 2968 | 1.4415          | {'f1': 0.7919566898685229}  | {'accuracy': 0.7848} |
| 0.0007        | 425.0 | 2975 | 1.4417          | {'f1': 0.7919566898685229}  | {'accuracy': 0.7848} |
| 0.0007        | 426.0 | 2982 | 1.4419          | {'f1': 0.7919566898685229}  | {'accuracy': 0.7848} |
| 0.0007        | 427.0 | 2989 | 1.4422          | {'f1': 0.7916505604947817}  | {'accuracy': 0.7844} |
| 0.0007        | 428.0 | 2996 | 1.4425          | {'f1': 0.7921174652241112}  | {'accuracy': 0.7848} |
| 0.0           | 429.0 | 3003 | 1.4428          | {'f1': 0.7921174652241112}  | {'accuracy': 0.7848} |
| 0.0           | 430.0 | 3010 | 1.4430          | {'f1': 0.7921174652241112}  | {'accuracy': 0.7848} |
| 0.0           | 431.0 | 3017 | 1.4432          | {'f1': 0.7925840092699883}  | {'accuracy': 0.7852} |
| 0.0           | 432.0 | 3024 | 1.4434          | {'f1': 0.793050193050193}   | {'accuracy': 0.7856} |
| 0.0           | 433.0 | 3031 | 1.4435          | {'f1': 0.793050193050193}   | {'accuracy': 0.7856} |
| 0.0           | 434.0 | 3038 | 1.4435          | {'f1': 0.7925840092699883}  | {'accuracy': 0.7852} |
| 0.0           | 435.0 | 3045 | 1.4412          | {'f1': 0.7903225806451615}  | {'accuracy': 0.792}  |
| 0.0           | 436.0 | 3052 | 1.5055          | {'f1': 0.7695560253699789}  | {'accuracy': 0.782}  |
| 0.0           | 437.0 | 3059 | 1.5542          | {'f1': 0.7638709677419356}  | {'accuracy': 0.7804} |
| 0.0           | 438.0 | 3066 | 1.5717          | {'f1': 0.7592190889370932}  | {'accuracy': 0.778}  |
| 0.0           | 439.0 | 3073 | 1.5722          | {'f1': 0.7586805555555556}  | {'accuracy': 0.7776} |
| 0.0           | 440.0 | 3080 | 1.5614          | {'f1': 0.7627264883520276}  | {'accuracy': 0.78}   |
| 0.0           | 441.0 | 3087 | 1.5519          | {'f1': 0.7642765135251182}  | {'accuracy': 0.7804} |
| 0.0           | 442.0 | 3094 | 1.5332          | {'f1': 0.7669365146996164}  | {'accuracy': 0.7812} |
| 0.0           | 443.0 | 3101 | 1.5032          | {'f1': 0.7716933445661331}  | {'accuracy': 0.7832} |
| 0.0           | 444.0 | 3108 | 1.4862          | {'f1': 0.7756463719766471}  | {'accuracy': 0.7848} |
| 0.0           | 445.0 | 3115 | 1.4768          | {'f1': 0.7759336099585062}  | {'accuracy': 0.784}  |
| 0.0           | 446.0 | 3122 | 1.4716          | {'f1': 0.77819083023544}    | {'accuracy': 0.7852} |
| 0.0           | 447.0 | 3129 | 1.4686          | {'f1': 0.7778695293146161}  | {'accuracy': 0.7848} |
| 0.0           | 448.0 | 3136 | 1.4661          | {'f1': 0.7782357790601815}  | {'accuracy': 0.7848} |
| 0.0           | 449.0 | 3143 | 1.4639          | {'f1': 0.7829298317603612}  | {'accuracy': 0.7884} |
| 0.0           | 450.0 | 3150 | 1.4625          | {'f1': 0.7824662023760756}  | {'accuracy': 0.7876} |
| 0.0           | 451.0 | 3157 | 1.4611          | {'f1': 0.7828220858895706}  | {'accuracy': 0.7876} |
| 0.0           | 452.0 | 3164 | 1.4597          | {'f1': 0.7834967320261439}  | {'accuracy': 0.788}  |
| 0.0           | 453.0 | 3171 | 1.4576          | {'f1': 0.7853360488798371}  | {'accuracy': 0.7892} |
| 0.0           | 454.0 | 3178 | 1.4564          | {'f1': 0.7881493506493508}  | {'accuracy': 0.7912} |
| 0.0           | 455.0 | 3185 | 1.4556          | {'f1': 0.7888123226591002}  | {'accuracy': 0.7916} |
| 0.0           | 456.0 | 3192 | 1.4550          | {'f1': 0.7894736842105263}  | {'accuracy': 0.792}  |
| 0.0           | 457.0 | 3199 | 1.4543          | {'f1': 0.7894736842105263}  | {'accuracy': 0.792}  |
| 0.0           | 458.0 | 3206 | 1.4537          | {'f1': 0.7909421754953497}  | {'accuracy': 0.7932} |
| 0.0           | 459.0 | 3213 | 1.4532          | {'f1': 0.7920872022607993}  | {'accuracy': 0.794}  |
| 0.0           | 460.0 | 3220 | 1.4524          | {'f1': 0.7919354838709676}  | {'accuracy': 0.7936} |
| 0.0           | 461.0 | 3227 | 1.4515          | {'f1': 0.7914653784219002}  | {'accuracy': 0.7928} |
| 0.0           | 462.0 | 3234 | 1.4510          | {'f1': 0.7918006430868169}  | {'accuracy': 0.7928} |
| 0.0           | 463.0 | 3241 | 1.4507          | {'f1': 0.7924528301886792}  | {'accuracy': 0.7932} |
| 0.0           | 464.0 | 3248 | 1.4506          | {'f1': 0.7921348314606741}  | {'accuracy': 0.7928} |
| 0.0           | 465.0 | 3255 | 1.4504          | {'f1': 0.7931034482758622}  | {'accuracy': 0.7936} |
| 0.0           | 466.0 | 3262 | 1.4502          | {'f1': 0.7931034482758622}  | {'accuracy': 0.7936} |
| 0.0           | 467.0 | 3269 | 1.4501          | {'f1': 0.7929515418502203}  | {'accuracy': 0.7932} |
| 0.0           | 468.0 | 3276 | 1.4499          | {'f1': 0.7931172468987595}  | {'accuracy': 0.7932} |
| 0.0           | 469.0 | 3283 | 1.4498          | {'f1': 0.7936}              | {'accuracy': 0.7936} |
| 0.0           | 470.0 | 3290 | 1.4497          | {'f1': 0.7937649880095924}  | {'accuracy': 0.7936} |
| 0.0           | 471.0 | 3297 | 1.4497          | {'f1': 0.7937649880095924}  | {'accuracy': 0.7936} |
| 0.0           | 472.0 | 3304 | 1.4495          | {'f1': 0.7937649880095924}  | {'accuracy': 0.7936} |
| 0.0           | 473.0 | 3311 | 1.4494          | {'f1': 0.7936127744510977}  | {'accuracy': 0.7932} |
| 0.0           | 474.0 | 3318 | 1.4486          | {'f1': 0.7937774232149979}  | {'accuracy': 0.7932} |
| 0.0           | 475.0 | 3325 | 1.4479          | {'f1': 0.7931446791550419}  | {'accuracy': 0.7924} |
| 0.0           | 476.0 | 3332 | 1.4476          | {'f1': 0.7937898089171975}  | {'accuracy': 0.7928} |
| 0.0           | 477.0 | 3339 | 1.4475          | {'f1': 0.7934739355352168}  | {'accuracy': 0.7924} |
| 0.0           | 478.0 | 3346 | 1.4475          | {'f1': 0.7934739355352168}  | {'accuracy': 0.7924} |
| 0.0           | 479.0 | 3353 | 1.4475          | {'f1': 0.7931583134447096}  | {'accuracy': 0.792}  |
| 0.0           | 480.0 | 3360 | 1.4475          | {'f1': 0.793322734499205}   | {'accuracy': 0.792}  |
| 0.0           | 481.0 | 3367 | 1.4475          | {'f1': 0.7930075486690504}  | {'accuracy': 0.7916} |
| 0.0           | 482.0 | 3374 | 1.4475          | {'f1': 0.7930075486690504}  | {'accuracy': 0.7916} |
| 0.0           | 483.0 | 3381 | 1.4476          | {'f1': 0.7934868943606036}  | {'accuracy': 0.792}  |
| 0.0           | 484.0 | 3388 | 1.4476          | {'f1': 0.7934868943606036}  | {'accuracy': 0.792}  |
| 0.0           | 485.0 | 3395 | 1.4476          | {'f1': 0.7934868943606036}  | {'accuracy': 0.792}  |
| 0.0           | 486.0 | 3402 | 1.4477          | {'f1': 0.7931718936085749}  | {'accuracy': 0.7916} |
| 0.0           | 487.0 | 3409 | 1.4477          | {'f1': 0.7931718936085749}  | {'accuracy': 0.7916} |
| 0.0           | 488.0 | 3416 | 1.4477          | {'f1': 0.7925426418088061}  | {'accuracy': 0.7908} |
| 0.0           | 489.0 | 3423 | 1.4478          | {'f1': 0.7925426418088061}  | {'accuracy': 0.7908} |
| 0.0           | 490.0 | 3430 | 1.4478          | {'f1': 0.7925426418088061}  | {'accuracy': 0.7908} |
| 0.0           | 491.0 | 3437 | 1.4478          | {'f1': 0.7930214115781127}  | {'accuracy': 0.7912} |
| 0.0           | 492.0 | 3444 | 1.4478          | {'f1': 0.7930214115781127}  | {'accuracy': 0.7912} |
| 0.0           | 493.0 | 3451 | 1.4479          | {'f1': 0.7930214115781127}  | {'accuracy': 0.7912} |
| 0.0           | 494.0 | 3458 | 1.4483          | {'f1': 0.7941640378548895}  | {'accuracy': 0.7912} |
| 0.0           | 495.0 | 3465 | 1.4496          | {'f1': 0.7930899096976836}  | {'accuracy': 0.7892} |
| 0.0           | 496.0 | 3472 | 1.4504          | {'f1': 0.7935761848805327}  | {'accuracy': 0.7892} |
| 0.0           | 497.0 | 3479 | 1.4507          | {'f1': 0.7951524628616107}  | {'accuracy': 0.7904} |
| 0.0           | 498.0 | 3486 | 1.4508          | {'f1': 0.795623290347792}   | {'accuracy': 0.7908} |
| 0.0           | 499.0 | 3493 | 1.4509          | {'f1': 0.795623290347792}   | {'accuracy': 0.7908} |
| 0.0001        | 500.0 | 3500 | 1.4509          | {'f1': 0.795623290347792}   | {'accuracy': 0.7908} |


### Framework versions

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