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_64_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_64_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: 1.5041
- F1: {'f1': 0.796440489432703}
- Accuracy: {'accuracy': 0.7804}

## 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    | 0.6982          | {'f1': 0.004784688995215311} | {'accuracy': 0.5008} |
| No log        | 2.0   | 14   | 0.6885          | {'f1': 0.655367231638418}    | {'accuracy': 0.5364} |
| No log        | 3.0   | 21   | 0.6874          | {'f1': 0.6617354196301565}   | {'accuracy': 0.5244} |
| No log        | 4.0   | 28   | 0.6822          | {'f1': 0.6497193793331132}   | {'accuracy': 0.5756} |
| No log        | 5.0   | 35   | 0.6786          | {'f1': 0.5570291777188329}   | {'accuracy': 0.5992} |
| No log        | 6.0   | 42   | 0.6741          | {'f1': 0.6100355590675621}   | {'accuracy': 0.6052} |
| No log        | 7.0   | 49   | 0.6706          | {'f1': 0.4816700610997964}   | {'accuracy': 0.5928} |
| No log        | 8.0   | 56   | 0.6654          | {'f1': 0.48136645962732916}  | {'accuracy': 0.5992} |
| No log        | 9.0   | 63   | 0.6520          | {'f1': 0.564531104921077}    | {'accuracy': 0.6248} |
| No log        | 10.0  | 70   | 0.6316          | {'f1': 0.669652855543113}    | {'accuracy': 0.646}  |
| No log        | 11.0  | 77   | 0.6364          | {'f1': 0.5811885821244736}   | {'accuracy': 0.642}  |
| No log        | 12.0  | 84   | 0.5995          | {'f1': 0.6873545384018619}   | {'accuracy': 0.6776} |
| No log        | 13.0  | 91   | 0.5920          | {'f1': 0.6943784639746634}   | {'accuracy': 0.6912} |
| No log        | 14.0  | 98   | 0.6104          | {'f1': 0.673913043478261}    | {'accuracy': 0.688}  |
| No log        | 15.0  | 105  | 0.5986          | {'f1': 0.7101621194147885}   | {'accuracy': 0.7068} |
| No log        | 16.0  | 112  | 0.6088          | {'f1': 0.7119205298013244}   | {'accuracy': 0.7216} |
| No log        | 17.0  | 119  | 0.6098          | {'f1': 0.7373776908023484}   | {'accuracy': 0.7316} |
| No log        | 18.0  | 126  | 0.6355          | {'f1': 0.7393403057119871}   | {'accuracy': 0.7408} |
| No log        | 19.0  | 133  | 0.6611          | {'f1': 0.7576766555678875}   | {'accuracy': 0.738}  |
| No log        | 20.0  | 140  | 0.6914          | {'f1': 0.7586469023185101}   | {'accuracy': 0.746}  |
| No log        | 21.0  | 147  | 0.7386          | {'f1': 0.7356042173560423}   | {'accuracy': 0.7392} |
| No log        | 22.0  | 154  | 0.7983          | {'f1': 0.7291054178916423}   | {'accuracy': 0.742}  |
| No log        | 23.0  | 161  | 0.7992          | {'f1': 0.7565485362095531}   | {'accuracy': 0.7472} |
| No log        | 24.0  | 168  | 0.8528          | {'f1': 0.7316455696202532}   | {'accuracy': 0.7456} |
| No log        | 25.0  | 175  | 0.8415          | {'f1': 0.759592795614722}    | {'accuracy': 0.7544} |
| No log        | 26.0  | 182  | 0.8850          | {'f1': 0.770764119601329}    | {'accuracy': 0.7516} |
| No log        | 27.0  | 189  | 0.8879          | {'f1': 0.7490759753593429}   | {'accuracy': 0.7556} |
| No log        | 28.0  | 196  | 0.9013          | {'f1': 0.7703533026113671}   | {'accuracy': 0.7608} |
| No log        | 29.0  | 203  | 1.0318          | {'f1': 0.7750791974656812}   | {'accuracy': 0.7444} |
| No log        | 30.0  | 210  | 0.9493          | {'f1': 0.7475165562913907}   | {'accuracy': 0.756}  |
| No log        | 31.0  | 217  | 0.9683          | {'f1': 0.7755102040816327}   | {'accuracy': 0.7624} |
| No log        | 32.0  | 224  | 1.0889          | {'f1': 0.7715091678420309}   | {'accuracy': 0.7408} |
| No log        | 33.0  | 231  | 1.0272          | {'f1': 0.7374631268436579}   | {'accuracy': 0.7508} |
| No log        | 34.0  | 238  | 1.0058          | {'f1': 0.7601121345614739}   | {'accuracy': 0.7604} |
| No log        | 35.0  | 245  | 1.0153          | {'f1': 0.7748165314793356}   | {'accuracy': 0.7668} |
| No log        | 36.0  | 252  | 1.0568          | {'f1': 0.7759197324414715}   | {'accuracy': 0.7588} |
| No log        | 37.0  | 259  | 1.1076          | {'f1': 0.7738910926794085}   | {'accuracy': 0.7492} |
| No log        | 38.0  | 266  | 1.0427          | {'f1': 0.7558666117743927}   | {'accuracy': 0.7628} |
| No log        | 39.0  | 273  | 1.0863          | {'f1': 0.7808269301134284}   | {'accuracy': 0.7604} |
| No log        | 40.0  | 280  | 1.1665          | {'f1': 0.7790738776952988}   | {'accuracy': 0.75}   |
| No log        | 41.0  | 287  | 1.0454          | {'f1': 0.7766692248656946}   | {'accuracy': 0.7672} |
| No log        | 42.0  | 294  | 1.0836          | {'f1': 0.7832840236686389}   | {'accuracy': 0.7656} |
| No log        | 43.0  | 301  | 1.1531          | {'f1': 0.7792486583184258}   | {'accuracy': 0.7532} |
| No log        | 44.0  | 308  | 1.0566          | {'f1': 0.773688332028191}    | {'accuracy': 0.7688} |
| No log        | 45.0  | 315  | 1.3225          | {'f1': 0.7732971873941037}   | {'accuracy': 0.7324} |
| No log        | 46.0  | 322  | 1.1126          | {'f1': 0.7831192660550459}   | {'accuracy': 0.7636} |
| No log        | 47.0  | 329  | 1.0526          | {'f1': 0.7771653543307088}   | {'accuracy': 0.7736} |
| No log        | 48.0  | 336  | 1.0584          | {'f1': 0.7826777910210567}   | {'accuracy': 0.7812} |
| No log        | 49.0  | 343  | 1.0694          | {'f1': 0.7797527047913447}   | {'accuracy': 0.772}  |
| No log        | 50.0  | 350  | 1.1168          | {'f1': 0.7819940476190476}   | {'accuracy': 0.7656} |
| No log        | 51.0  | 357  | 1.0804          | {'f1': 0.7815028901734103}   | {'accuracy': 0.7732} |
| No log        | 52.0  | 364  | 1.2250          | {'f1': 0.7811280595956013}   | {'accuracy': 0.7532} |
| No log        | 53.0  | 371  | 1.1277          | {'f1': 0.7861356932153392}   | {'accuracy': 0.768}  |
| No log        | 54.0  | 378  | 1.0646          | {'f1': 0.7837190742218675}   | {'accuracy': 0.7832} |
| No log        | 55.0  | 385  | 1.1001          | {'f1': 0.7902439024390244}   | {'accuracy': 0.7764} |
| No log        | 56.0  | 392  | 1.2776          | {'f1': 0.7834907310248339}   | {'accuracy': 0.7524} |
| No log        | 57.0  | 399  | 1.2173          | {'f1': 0.7844118698605649}   | {'accuracy': 0.7588} |
| No log        | 58.0  | 406  | 1.0998          | {'f1': 0.7883880825057296}   | {'accuracy': 0.7784} |
| No log        | 59.0  | 413  | 1.0903          | {'f1': 0.7832730197024528}   | {'accuracy': 0.7844} |
| No log        | 60.0  | 420  | 1.0943          | {'f1': 0.7891050583657588}   | {'accuracy': 0.7832} |
| No log        | 61.0  | 427  | 1.1423          | {'f1': 0.7883971736705095}   | {'accuracy': 0.7724} |
| No log        | 62.0  | 434  | 1.1620          | {'f1': 0.7876106194690266}   | {'accuracy': 0.7696} |
| No log        | 63.0  | 441  | 1.1627          | {'f1': 0.7887740029542099}   | {'accuracy': 0.7712} |
| No log        | 64.0  | 448  | 1.1474          | {'f1': 0.7914798206278026}   | {'accuracy': 0.7768} |
| No log        | 65.0  | 455  | 1.1109          | {'f1': 0.7910447761194029}   | {'accuracy': 0.7872} |
| No log        | 66.0  | 462  | 1.1295          | {'f1': 0.7908221797323136}   | {'accuracy': 0.7812} |
| No log        | 67.0  | 469  | 1.1479          | {'f1': 0.7931947069943289}   | {'accuracy': 0.7812} |
| No log        | 68.0  | 476  | 1.1624          | {'f1': 0.7941397445529677}   | {'accuracy': 0.7808} |
| No log        | 69.0  | 483  | 1.1639          | {'f1': 0.7942835652500941}   | {'accuracy': 0.7812} |
| No log        | 70.0  | 490  | 1.1614          | {'f1': 0.7933509633547412}   | {'accuracy': 0.7812} |
| No log        | 71.0  | 497  | 1.1656          | {'f1': 0.7939622641509434}   | {'accuracy': 0.7816} |
| 0.1405        | 72.0  | 504  | 1.1664          | {'f1': 0.7933509633547412}   | {'accuracy': 0.7812} |
| 0.1405        | 73.0  | 511  | 1.1431          | {'f1': 0.7895760404511865}   | {'accuracy': 0.7836} |
| 0.1405        | 74.0  | 518  | 1.1435          | {'f1': 0.7889763779527559}   | {'accuracy': 0.7856} |
| 0.1405        | 75.0  | 525  | 1.1507          | {'f1': 0.7900852052672346}   | {'accuracy': 0.7832} |
| 0.1405        | 76.0  | 532  | 1.1787          | {'f1': 0.7936627687665032}   | {'accuracy': 0.7812} |
| 0.1405        | 77.0  | 539  | 1.2244          | {'f1': 0.7876561351947098}   | {'accuracy': 0.7688} |
| 0.1405        | 78.0  | 546  | 1.2429          | {'f1': 0.7886297376093294}   | {'accuracy': 0.768}  |
| 0.1405        | 79.0  | 553  | 1.2167          | {'f1': 0.7912495365220615}   | {'accuracy': 0.7748} |
| 0.1405        | 80.0  | 560  | 1.1840          | {'f1': 0.7912087912087912}   | {'accuracy': 0.7796} |
| 0.1405        | 81.0  | 567  | 1.1756          | {'f1': 0.7903963414634146}   | {'accuracy': 0.78}   |
| 0.1405        | 82.0  | 574  | 1.1744          | {'f1': 0.7900383141762451}   | {'accuracy': 0.7808} |
| 0.1405        | 83.0  | 581  | 1.1755          | {'f1': 0.7894131185270427}   | {'accuracy': 0.7804} |
| 0.1405        | 84.0  | 588  | 1.1790          | {'f1': 0.7898966704936855}   | {'accuracy': 0.7804} |
| 0.1405        | 85.0  | 595  | 1.1849          | {'f1': 0.7897943640517898}   | {'accuracy': 0.7792} |
| 0.1405        | 86.0  | 602  | 1.1950          | {'f1': 0.7901328273244782}   | {'accuracy': 0.7788} |
| 0.1405        | 87.0  | 609  | 1.2082          | {'f1': 0.79155672823219}     | {'accuracy': 0.7788} |
| 0.1405        | 88.0  | 616  | 1.2207          | {'f1': 0.7940074906367041}   | {'accuracy': 0.78}   |
| 0.1405        | 89.0  | 623  | 1.2201          | {'f1': 0.7935435435435436}   | {'accuracy': 0.78}   |
| 0.1405        | 90.0  | 630  | 1.2179          | {'f1': 0.7930775018811136}   | {'accuracy': 0.78}   |
| 0.1405        | 91.0  | 637  | 1.2169          | {'f1': 0.7918552036199096}   | {'accuracy': 0.7792} |
| 0.1405        | 92.0  | 644  | 1.2162          | {'f1': 0.7916981132075471}   | {'accuracy': 0.7792} |
| 0.1405        | 93.0  | 651  | 1.2158          | {'f1': 0.791981845688351}    | {'accuracy': 0.78}   |
| 0.1405        | 94.0  | 658  | 1.2570          | {'f1': 0.7619453924914678}   | {'accuracy': 0.7768} |
| 0.1405        | 95.0  | 665  | 1.2645          | {'f1': 0.7930780559646539}   | {'accuracy': 0.7752} |
| 0.1405        | 96.0  | 672  | 1.3050          | {'f1': 0.7886710239651417}   | {'accuracy': 0.7672} |
| 0.1405        | 97.0  | 679  | 1.2435          | {'f1': 0.7745713090757006}   | {'accuracy': 0.7844} |
| 0.1405        | 98.0  | 686  | 1.2083          | {'f1': 0.7878548895899053}   | {'accuracy': 0.7848} |
| 0.1405        | 99.0  | 693  | 1.2364          | {'f1': 0.7959028831562974}   | {'accuracy': 0.7848} |
| 0.1405        | 100.0 | 700  | 1.2611          | {'f1': 0.7940074906367041}   | {'accuracy': 0.78}   |
| 0.1405        | 101.0 | 707  | 1.2721          | {'f1': 0.7926920208799404}   | {'accuracy': 0.7776} |
| 0.1405        | 102.0 | 714  | 1.2760          | {'f1': 0.7919762258543834}   | {'accuracy': 0.776}  |
| 0.1405        | 103.0 | 721  | 1.2535          | {'f1': 0.7950263752825923}   | {'accuracy': 0.7824} |
| 0.1405        | 104.0 | 728  | 1.2403          | {'f1': 0.7968036529680366}   | {'accuracy': 0.7864} |
| 0.1405        | 105.0 | 735  | 1.2373          | {'f1': 0.7934200459066564}   | {'accuracy': 0.784}  |
| 0.1405        | 106.0 | 742  | 1.2427          | {'f1': 0.7963456414160639}   | {'accuracy': 0.786}  |
| 0.1405        | 107.0 | 749  | 1.2564          | {'f1': 0.7965269913174783}   | {'accuracy': 0.7844} |
| 0.1405        | 108.0 | 756  | 1.2666          | {'f1': 0.7950450450450449}   | {'accuracy': 0.7816} |
| 0.1405        | 109.0 | 763  | 1.2703          | {'f1': 0.7944486121530383}   | {'accuracy': 0.7808} |
| 0.1405        | 110.0 | 770  | 1.2737          | {'f1': 0.7946026986506746}   | {'accuracy': 0.7808} |
| 0.1405        | 111.0 | 777  | 1.2735          | {'f1': 0.7944486121530383}   | {'accuracy': 0.7808} |
| 0.1405        | 112.0 | 784  | 1.2749          | {'f1': 0.7944486121530383}   | {'accuracy': 0.7808} |
| 0.1405        | 113.0 | 791  | 1.2706          | {'f1': 0.7959413754227733}   | {'accuracy': 0.7828} |
| 0.1405        | 114.0 | 798  | 1.2579          | {'f1': 0.7962049335863377}   | {'accuracy': 0.7852} |
| 0.1405        | 115.0 | 805  | 1.2497          | {'f1': 0.7955589586523738}   | {'accuracy': 0.7864} |
| 0.1405        | 116.0 | 812  | 1.2481          | {'f1': 0.79293123319247}     | {'accuracy': 0.7844} |
| 0.1405        | 117.0 | 819  | 1.2496          | {'f1': 0.7785069729286301}   | {'accuracy': 0.784}  |
| 0.1405        | 118.0 | 826  | 1.2386          | {'f1': 0.7910447761194029}   | {'accuracy': 0.7872} |
| 0.1405        | 119.0 | 833  | 1.3391          | {'f1': 0.7925493060628196}   | {'accuracy': 0.7728} |
| 0.1405        | 120.0 | 840  | 1.4218          | {'f1': 0.7887424296401851}   | {'accuracy': 0.7628} |
| 0.1405        | 121.0 | 847  | 1.2557          | {'f1': 0.79155260070395}     | {'accuracy': 0.7868} |
| 0.1405        | 122.0 | 854  | 1.2889          | {'f1': 0.7707032875572202}   | {'accuracy': 0.7796} |
| 0.1405        | 123.0 | 861  | 1.3041          | {'f1': 0.7664570230607967}   | {'accuracy': 0.7772} |
| 0.1405        | 124.0 | 868  | 1.4518          | {'f1': 0.7878359264497878}   | {'accuracy': 0.76}   |
| 0.1405        | 125.0 | 875  | 1.3888          | {'f1': 0.7893792608539649}   | {'accuracy': 0.7652} |
| 0.1405        | 126.0 | 882  | 1.2520          | {'f1': 0.793196752995748}    | {'accuracy': 0.786}  |
| 0.1405        | 127.0 | 889  | 1.2419          | {'f1': 0.7889245585874799}   | {'accuracy': 0.7896} |
| 0.1405        | 128.0 | 896  | 1.2470          | {'f1': 0.7842660178426601}   | {'accuracy': 0.7872} |
| 0.1405        | 129.0 | 903  | 1.2449          | {'f1': 0.7887323943661971}   | {'accuracy': 0.79}   |
| 0.1405        | 130.0 | 910  | 1.2444          | {'f1': 0.7938021454112039}   | {'accuracy': 0.7924} |
| 0.1405        | 131.0 | 917  | 1.2492          | {'f1': 0.795133437990581}    | {'accuracy': 0.7912} |
| 0.1405        | 132.0 | 924  | 1.2570          | {'f1': 0.7928765001935733}   | {'accuracy': 0.786}  |
| 0.1405        | 133.0 | 931  | 1.2660          | {'f1': 0.7923224568138196}   | {'accuracy': 0.7836} |
| 0.1405        | 134.0 | 938  | 1.2749          | {'f1': 0.7928271652041207}   | {'accuracy': 0.7828} |
| 0.1405        | 135.0 | 945  | 1.2832          | {'f1': 0.7934700075930143}   | {'accuracy': 0.7824} |
| 0.1405        | 136.0 | 952  | 1.2702          | {'f1': 0.7940161104718065}   | {'accuracy': 0.7852} |
| 0.1405        | 137.0 | 959  | 1.2620          | {'f1': 0.7939464493597206}   | {'accuracy': 0.7876} |
| 0.1405        | 138.0 | 966  | 1.2597          | {'f1': 0.7929549902152642}   | {'accuracy': 0.7884} |
| 0.1405        | 139.0 | 973  | 1.3074          | {'f1': 0.7920270778488154}   | {'accuracy': 0.7788} |
| 0.1405        | 140.0 | 980  | 1.3511          | {'f1': 0.7921742340346991}   | {'accuracy': 0.7748} |
| 0.1405        | 141.0 | 987  | 1.4323          | {'f1': 0.7901146131805157}   | {'accuracy': 0.7656} |
| 0.1405        | 142.0 | 994  | 1.5756          | {'f1': 0.7842866988283942}   | {'accuracy': 0.7496} |
| 0.0009        | 143.0 | 1001 | 1.5489          | {'f1': 0.7862595419847328}   | {'accuracy': 0.7536} |
| 0.0009        | 144.0 | 1008 | 1.3006          | {'f1': 0.7898187427689936}   | {'accuracy': 0.782}  |
| 0.0009        | 145.0 | 1015 | 1.5527          | {'f1': 0.7151348879743941}   | {'accuracy': 0.7508} |
| 0.0009        | 146.0 | 1022 | 1.3876          | {'f1': 0.751592356687898}    | {'accuracy': 0.766}  |
| 0.0009        | 147.0 | 1029 | 1.3456          | {'f1': 0.7812752219531881}   | {'accuracy': 0.7832} |
| 0.0009        | 148.0 | 1036 | 1.3554          | {'f1': 0.7858255451713395}   | {'accuracy': 0.78}   |
| 0.0009        | 149.0 | 1043 | 1.3710          | {'f1': 0.787201233616037}    | {'accuracy': 0.7792} |
| 0.0009        | 150.0 | 1050 | 1.3786          | {'f1': 0.7864823348694318}   | {'accuracy': 0.7776} |
| 0.0009        | 151.0 | 1057 | 1.3805          | {'f1': 0.7863444572305331}   | {'accuracy': 0.7772} |
| 0.0009        | 152.0 | 1064 | 1.3809          | {'f1': 0.7869481765834931}   | {'accuracy': 0.778}  |
| 0.0009        | 153.0 | 1071 | 1.3814          | {'f1': 0.7869481765834931}   | {'accuracy': 0.778}  |
| 0.0009        | 154.0 | 1078 | 1.3823          | {'f1': 0.7869481765834931}   | {'accuracy': 0.778}  |
| 0.0009        | 155.0 | 1085 | 1.3839          | {'f1': 0.7866462010744435}   | {'accuracy': 0.7776} |
| 0.0009        | 156.0 | 1092 | 1.3770          | {'f1': 0.787037037037037}    | {'accuracy': 0.7792} |
| 0.0009        | 157.0 | 1099 | 1.3703          | {'f1': 0.7863777089783281}   | {'accuracy': 0.7792} |
| 0.0009        | 158.0 | 1106 | 1.3701          | {'f1': 0.7862122385747482}   | {'accuracy': 0.7792} |
| 0.0009        | 159.0 | 1113 | 1.3721          | {'f1': 0.7862122385747482}   | {'accuracy': 0.7792} |
| 0.0009        | 160.0 | 1120 | 1.3742          | {'f1': 0.7856037151702787}   | {'accuracy': 0.7784} |
| 0.0009        | 161.0 | 1127 | 1.3755          | {'f1': 0.786073500967118}    | {'accuracy': 0.7788} |
| 0.0009        | 162.0 | 1134 | 1.3754          | {'f1': 0.785907859078591}    | {'accuracy': 0.7788} |
| 0.0009        | 163.0 | 1141 | 1.3756          | {'f1': 0.785907859078591}    | {'accuracy': 0.7788} |
| 0.0009        | 164.0 | 1148 | 1.3778          | {'f1': 0.785907859078591}    | {'accuracy': 0.7788} |
| 0.0009        | 165.0 | 1155 | 1.3824          | {'f1': 0.7868725868725869}   | {'accuracy': 0.7792} |
| 0.0009        | 166.0 | 1162 | 1.4059          | {'f1': 0.7896930655551344}   | {'accuracy': 0.778}  |
| 0.0009        | 167.0 | 1169 | 1.4486          | {'f1': 0.7876534027519524}   | {'accuracy': 0.7716} |
| 0.0009        | 168.0 | 1176 | 1.4664          | {'f1': 0.787878787878788}    | {'accuracy': 0.7704} |
| 0.0009        | 169.0 | 1183 | 1.4689          | {'f1': 0.7880354505169868}   | {'accuracy': 0.7704} |
| 0.0009        | 170.0 | 1190 | 1.4654          | {'f1': 0.7881700554528651}   | {'accuracy': 0.7708} |
| 0.0009        | 171.0 | 1197 | 1.4576          | {'f1': 0.7882832777159807}   | {'accuracy': 0.7716} |
| 0.0009        | 172.0 | 1204 | 1.4436          | {'f1': 0.7855277881387541}   | {'accuracy': 0.77}   |
| 0.0009        | 173.0 | 1211 | 1.4326          | {'f1': 0.7857410881801125}   | {'accuracy': 0.7716} |
| 0.0009        | 174.0 | 1218 | 1.4210          | {'f1': 0.7891361750282913}   | {'accuracy': 0.7764} |
| 0.0009        | 175.0 | 1225 | 1.4110          | {'f1': 0.790909090909091}    | {'accuracy': 0.7792} |
| 0.0009        | 176.0 | 1232 | 1.4059          | {'f1': 0.7894937190711839}   | {'accuracy': 0.7788} |
| 0.0009        | 177.0 | 1239 | 1.4015          | {'f1': 0.7909992372234935}   | {'accuracy': 0.7808} |
| 0.0009        | 178.0 | 1246 | 1.3992          | {'f1': 0.7900763358778626}   | {'accuracy': 0.78}   |
| 0.0009        | 179.0 | 1253 | 1.3985          | {'f1': 0.7892925430210325}   | {'accuracy': 0.7796} |
| 0.0009        | 180.0 | 1260 | 1.3968          | {'f1': 0.7905017234775948}   | {'accuracy': 0.7812} |
| 0.0009        | 181.0 | 1267 | 1.4007          | {'f1': 0.7900763358778626}   | {'accuracy': 0.78}   |
| 0.0009        | 182.0 | 1274 | 1.4019          | {'f1': 0.7900763358778626}   | {'accuracy': 0.78}   |
| 0.0009        | 183.0 | 1281 | 1.3990          | {'f1': 0.7918898240244836}   | {'accuracy': 0.7824} |
| 0.0009        | 184.0 | 1288 | 1.3984          | {'f1': 0.7921928817451205}   | {'accuracy': 0.7828} |
| 0.0009        | 185.0 | 1295 | 1.3986          | {'f1': 0.7915708812260537}   | {'accuracy': 0.7824} |
| 0.0009        | 186.0 | 1302 | 1.3988          | {'f1': 0.7917146144994246}   | {'accuracy': 0.7828} |
| 0.0009        | 187.0 | 1309 | 1.4010          | {'f1': 0.7918898240244836}   | {'accuracy': 0.7824} |
| 0.0009        | 188.0 | 1316 | 1.4036          | {'f1': 0.7923518164435946}   | {'accuracy': 0.7828} |
| 0.0009        | 189.0 | 1323 | 1.3966          | {'f1': 0.7923076923076923}   | {'accuracy': 0.784}  |
| 0.0009        | 190.0 | 1330 | 1.3964          | {'f1': 0.7926125432858792}   | {'accuracy': 0.7844} |
| 0.0009        | 191.0 | 1337 | 1.3972          | {'f1': 0.7926125432858792}   | {'accuracy': 0.7844} |
| 0.0009        | 192.0 | 1344 | 1.3977          | {'f1': 0.7926125432858792}   | {'accuracy': 0.7844} |
| 0.0009        | 193.0 | 1351 | 1.3970          | {'f1': 0.792758089368259}    | {'accuracy': 0.7848} |
| 0.0009        | 194.0 | 1358 | 1.3968          | {'f1': 0.792758089368259}    | {'accuracy': 0.7848} |
| 0.0009        | 195.0 | 1365 | 1.3972          | {'f1': 0.7922928709055876}   | {'accuracy': 0.7844} |
| 0.0009        | 196.0 | 1372 | 1.3985          | {'f1': 0.792758089368259}    | {'accuracy': 0.7848} |
| 0.0009        | 197.0 | 1379 | 1.4008          | {'f1': 0.7932229495571813}   | {'accuracy': 0.7852} |
| 0.0009        | 198.0 | 1386 | 1.4017          | {'f1': 0.7932229495571813}   | {'accuracy': 0.7852} |
| 0.0009        | 199.0 | 1393 | 1.4018          | {'f1': 0.7932229495571813}   | {'accuracy': 0.7852} |
| 0.0009        | 200.0 | 1400 | 1.4011          | {'f1': 0.7922928709055876}   | {'accuracy': 0.7844} |
| 0.0009        | 201.0 | 1407 | 1.4041          | {'f1': 0.7941515967679877}   | {'accuracy': 0.786}  |
| 0.0009        | 202.0 | 1414 | 1.4072          | {'f1': 0.7929447852760737}   | {'accuracy': 0.784}  |
| 0.0009        | 203.0 | 1421 | 1.4697          | {'f1': 0.7874953479717157}   | {'accuracy': 0.7716} |
| 0.0009        | 204.0 | 1428 | 1.5064          | {'f1': 0.7891256429096254}   | {'accuracy': 0.7704} |
| 0.0009        | 205.0 | 1435 | 1.5113          | {'f1': 0.788546255506608}    | {'accuracy': 0.7696} |
| 0.0009        | 206.0 | 1442 | 1.4517          | {'f1': 0.7872420262664164}   | {'accuracy': 0.7732} |
| 0.0009        | 207.0 | 1449 | 1.4151          | {'f1': 0.7929447852760737}   | {'accuracy': 0.784}  |
| 0.0009        | 208.0 | 1456 | 1.4060          | {'f1': 0.7896365042536735}   | {'accuracy': 0.7824} |
| 0.0009        | 209.0 | 1463 | 1.4032          | {'f1': 0.7895760404511865}   | {'accuracy': 0.7836} |
| 0.0009        | 210.0 | 1470 | 1.4043          | {'f1': 0.7895760404511865}   | {'accuracy': 0.7836} |
| 0.0009        | 211.0 | 1477 | 1.4061          | {'f1': 0.7889837083010085}   | {'accuracy': 0.7824} |
| 0.0009        | 212.0 | 1484 | 1.4080          | {'f1': 0.7900852052672346}   | {'accuracy': 0.7832} |
| 0.0009        | 213.0 | 1491 | 1.4099          | {'f1': 0.7896365042536735}   | {'accuracy': 0.7824} |
| 0.0009        | 214.0 | 1498 | 1.4116          | {'f1': 0.7902665121668598}   | {'accuracy': 0.7828} |
| 0.0001        | 215.0 | 1505 | 1.4136          | {'f1': 0.7918272937548188}   | {'accuracy': 0.784}  |
| 0.0001        | 216.0 | 1512 | 1.4155          | {'f1': 0.7918272937548188}   | {'accuracy': 0.784}  |
| 0.0001        | 217.0 | 1519 | 1.4240          | {'f1': 0.7643097643097643}   | {'accuracy': 0.776}  |
| 0.0001        | 218.0 | 1526 | 1.5173          | {'f1': 0.7425786442179884}   | {'accuracy': 0.7676} |
| 0.0001        | 219.0 | 1533 | 1.3915          | {'f1': 0.7912677135197241}   | {'accuracy': 0.782}  |
| 0.0001        | 220.0 | 1540 | 1.7768          | {'f1': 0.7734056987788331}   | {'accuracy': 0.7328} |
| 0.0001        | 221.0 | 1547 | 1.4188          | {'f1': 0.7886148007590134}   | {'accuracy': 0.7772} |
| 0.0001        | 222.0 | 1554 | 1.4241          | {'f1': 0.7668350168350168}   | {'accuracy': 0.7784} |
| 0.0001        | 223.0 | 1561 | 1.4845          | {'f1': 0.7491289198606271}   | {'accuracy': 0.7696} |
| 0.0001        | 224.0 | 1568 | 1.3685          | {'f1': 0.7857432158768731}   | {'accuracy': 0.7884} |
| 0.0001        | 225.0 | 1575 | 1.5106          | {'f1': 0.7936736161035227}   | {'accuracy': 0.7704} |
| 0.0001        | 226.0 | 1582 | 1.7115          | {'f1': 0.7832024581768523}   | {'accuracy': 0.746}  |
| 0.0001        | 227.0 | 1589 | 1.5283          | {'f1': 0.7951376474794423}   | {'accuracy': 0.7708} |
| 0.0001        | 228.0 | 1596 | 1.4008          | {'f1': 0.8002969561989607}   | {'accuracy': 0.7848} |
| 0.0001        | 229.0 | 1603 | 1.3623          | {'f1': 0.8021228203184231}   | {'accuracy': 0.7912} |
| 0.0001        | 230.0 | 1610 | 1.3496          | {'f1': 0.8012255840674071}   | {'accuracy': 0.7924} |
| 0.0001        | 231.0 | 1617 | 1.3492          | {'f1': 0.8012279355333844}   | {'accuracy': 0.7928} |
| 0.0001        | 232.0 | 1624 | 1.3606          | {'f1': 0.8007604562737642}   | {'accuracy': 0.7904} |
| 0.0001        | 233.0 | 1631 | 1.3691          | {'f1': 0.801818870784388}    | {'accuracy': 0.7908} |
| 0.0001        | 234.0 | 1638 | 1.3740          | {'f1': 0.8012093726379441}   | {'accuracy': 0.7896} |
| 0.0001        | 235.0 | 1645 | 1.3771          | {'f1': 0.7999999999999999}   | {'accuracy': 0.788}  |
| 0.0001        | 236.0 | 1652 | 1.3781          | {'f1': 0.7999999999999999}   | {'accuracy': 0.788}  |
| 0.0001        | 237.0 | 1659 | 1.3830          | {'f1': 0.8009032743695896}   | {'accuracy': 0.7884} |
| 0.0001        | 238.0 | 1666 | 1.3903          | {'f1': 0.800599700149925}    | {'accuracy': 0.7872} |
| 0.0001        | 239.0 | 1673 | 1.3953          | {'f1': 0.8004492699363533}   | {'accuracy': 0.7868} |
| 0.0001        | 240.0 | 1680 | 1.3986          | {'f1': 0.8002991772625281}   | {'accuracy': 0.7864} |
| 0.0001        | 241.0 | 1687 | 1.4014          | {'f1': 0.7994023160254016}   | {'accuracy': 0.7852} |
| 0.0001        | 242.0 | 1694 | 1.4058          | {'f1': 0.8002980625931445}   | {'accuracy': 0.7856} |
| 0.0001        | 243.0 | 1701 | 1.4101          | {'f1': 0.8007448789571695}   | {'accuracy': 0.786}  |
| 0.0001        | 244.0 | 1708 | 1.4127          | {'f1': 0.8001485884101041}   | {'accuracy': 0.7848} |
| 0.0001        | 245.0 | 1715 | 1.4152          | {'f1': 0.8005941329372447}   | {'accuracy': 0.7852} |
| 0.0001        | 246.0 | 1722 | 1.4152          | {'f1': 0.8001485884101041}   | {'accuracy': 0.7848} |
| 0.0001        | 247.0 | 1729 | 1.4150          | {'f1': 0.8004459308807135}   | {'accuracy': 0.7852} |
| 0.0001        | 248.0 | 1736 | 1.4153          | {'f1': 0.8004459308807135}   | {'accuracy': 0.7852} |
| 0.0001        | 249.0 | 1743 | 1.4170          | {'f1': 0.8004459308807135}   | {'accuracy': 0.7852} |
| 0.0001        | 250.0 | 1750 | 1.4173          | {'f1': 0.8004459308807135}   | {'accuracy': 0.7852} |
| 0.0001        | 251.0 | 1757 | 1.4181          | {'f1': 0.8004459308807135}   | {'accuracy': 0.7852} |
| 0.0001        | 252.0 | 1764 | 1.4187          | {'f1': 0.8004459308807135}   | {'accuracy': 0.7852} |
| 0.0001        | 253.0 | 1771 | 1.4193          | {'f1': 0.8004459308807135}   | {'accuracy': 0.7852} |
| 0.0001        | 254.0 | 1778 | 1.4205          | {'f1': 0.8008915304606241}   | {'accuracy': 0.7856} |
| 0.0001        | 255.0 | 1785 | 1.4215          | {'f1': 0.8008915304606241}   | {'accuracy': 0.7856} |
| 0.0001        | 256.0 | 1792 | 1.4207          | {'f1': 0.8004459308807135}   | {'accuracy': 0.7852} |
| 0.0001        | 257.0 | 1799 | 1.4206          | {'f1': 0.8004459308807135}   | {'accuracy': 0.7852} |
| 0.0001        | 258.0 | 1806 | 1.4306          | {'f1': 0.7999999999999999}   | {'accuracy': 0.784}  |
| 0.0001        | 259.0 | 1813 | 1.4348          | {'f1': 0.7994078460399704}   | {'accuracy': 0.7832} |
| 0.0001        | 260.0 | 1820 | 1.4273          | {'f1': 0.8005941329372447}   | {'accuracy': 0.7852} |
| 0.0001        | 261.0 | 1827 | 1.4258          | {'f1': 0.7995537374488658}   | {'accuracy': 0.7844} |
| 0.0001        | 262.0 | 1834 | 1.4261          | {'f1': 0.7995537374488658}   | {'accuracy': 0.7844} |
| 0.0001        | 263.0 | 1841 | 1.4266          | {'f1': 0.7991071428571429}   | {'accuracy': 0.784}  |
| 0.0001        | 264.0 | 1848 | 1.4270          | {'f1': 0.7991071428571429}   | {'accuracy': 0.784}  |
| 0.0001        | 265.0 | 1855 | 1.4266          | {'f1': 0.7986602158541125}   | {'accuracy': 0.7836} |
| 0.0001        | 266.0 | 1862 | 1.4246          | {'f1': 0.7986577181208054}   | {'accuracy': 0.784}  |
| 0.0001        | 267.0 | 1869 | 1.4248          | {'f1': 0.7986577181208054}   | {'accuracy': 0.784}  |
| 0.0001        | 268.0 | 1876 | 1.4256          | {'f1': 0.7986577181208054}   | {'accuracy': 0.784}  |
| 0.0001        | 269.0 | 1883 | 1.4268          | {'f1': 0.7985102420856611}   | {'accuracy': 0.7836} |
| 0.0001        | 270.0 | 1890 | 1.4295          | {'f1': 0.7986602158541125}   | {'accuracy': 0.7836} |
| 0.0001        | 271.0 | 1897 | 1.4313          | {'f1': 0.7991071428571429}   | {'accuracy': 0.784}  |
| 0.0001        | 272.0 | 1904 | 1.4335          | {'f1': 0.7992565055762082}   | {'accuracy': 0.784}  |
| 0.0001        | 273.0 | 1911 | 1.4373          | {'f1': 0.7998514667656889}   | {'accuracy': 0.7844} |
| 0.0001        | 274.0 | 1918 | 1.4406          | {'f1': 0.8000000000000002}   | {'accuracy': 0.7844} |
| 0.0001        | 275.0 | 1925 | 1.4433          | {'f1': 0.799110452186805}    | {'accuracy': 0.7832} |
| 0.0001        | 276.0 | 1932 | 1.4454          | {'f1': 0.7997038134024435}   | {'accuracy': 0.7836} |
| 0.0001        | 277.0 | 1939 | 1.4466          | {'f1': 0.7997038134024435}   | {'accuracy': 0.7836} |
| 0.0001        | 278.0 | 1946 | 1.4425          | {'f1': 0.7995545657015591}   | {'accuracy': 0.784}  |
| 0.0001        | 279.0 | 1953 | 1.4293          | {'f1': 0.7991038088125467}   | {'accuracy': 0.7848} |
| 0.0001        | 280.0 | 1960 | 1.4180          | {'f1': 0.7995495495495496}   | {'accuracy': 0.7864} |
| 0.0001        | 281.0 | 1967 | 1.4141          | {'f1': 0.8004518072289157}   | {'accuracy': 0.788}  |
| 0.0001        | 282.0 | 1974 | 1.4138          | {'f1': 0.8}                  | {'accuracy': 0.7876} |
| 0.0001        | 283.0 | 1981 | 1.4172          | {'f1': 0.7999999999999999}   | {'accuracy': 0.7872} |
| 0.0001        | 284.0 | 1988 | 1.4209          | {'f1': 0.7995495495495496}   | {'accuracy': 0.7864} |
| 0.0001        | 285.0 | 1995 | 1.4232          | {'f1': 0.7996999249812453}   | {'accuracy': 0.7864} |
| 0.0009        | 286.0 | 2002 | 1.4226          | {'f1': 0.8}                  | {'accuracy': 0.7868} |
| 0.0009        | 287.0 | 2009 | 1.4226          | {'f1': 0.8}                  | {'accuracy': 0.7868} |
| 0.0009        | 288.0 | 2016 | 1.4258          | {'f1': 0.7994000749906262}   | {'accuracy': 0.786}  |
| 0.0009        | 289.0 | 2023 | 1.4286          | {'f1': 0.7998500749625188}   | {'accuracy': 0.7864} |
| 0.0009        | 290.0 | 2030 | 1.4308          | {'f1': 0.8002997377294866}   | {'accuracy': 0.7868} |
| 0.0009        | 291.0 | 2037 | 1.4325          | {'f1': 0.7994011976047903}   | {'accuracy': 0.7856} |
| 0.0009        | 292.0 | 2044 | 1.4336          | {'f1': 0.7991021324354658}   | {'accuracy': 0.7852} |
| 0.0009        | 293.0 | 2051 | 1.4340          | {'f1': 0.7991021324354658}   | {'accuracy': 0.7852} |
| 0.0009        | 294.0 | 2058 | 1.4326          | {'f1': 0.8002997377294866}   | {'accuracy': 0.7868} |
| 0.0009        | 295.0 | 2065 | 1.4325          | {'f1': 0.7998500749625188}   | {'accuracy': 0.7864} |
| 0.0009        | 296.0 | 2072 | 1.4124          | {'f1': 0.8012093726379441}   | {'accuracy': 0.7896} |
| 0.0009        | 297.0 | 2079 | 1.3959          | {'f1': 0.80168776371308}     | {'accuracy': 0.7932} |
| 0.0009        | 298.0 | 2086 | 1.6002          | {'f1': 0.794762915782024}    | {'accuracy': 0.768}  |
| 0.0009        | 299.0 | 2093 | 1.7138          | {'f1': 0.7907458563535912}   | {'accuracy': 0.7576} |
| 0.0009        | 300.0 | 2100 | 1.4257          | {'f1': 0.7976011994002997}   | {'accuracy': 0.784}  |
| 0.0009        | 301.0 | 2107 | 1.3683          | {'f1': 0.8032850997262417}   | {'accuracy': 0.7988} |
| 0.0009        | 302.0 | 2114 | 1.3620          | {'f1': 0.8046068308181096}   | {'accuracy': 0.8032} |
| 0.0009        | 303.0 | 2121 | 1.3630          | {'f1': 0.8009592326139089}   | {'accuracy': 0.8008} |
| 0.0009        | 304.0 | 2128 | 1.3633          | {'f1': 0.8030242737763629}   | {'accuracy': 0.802}  |
| 0.0009        | 305.0 | 2135 | 1.3670          | {'f1': 0.8050314465408804}   | {'accuracy': 0.8016} |
| 0.0009        | 306.0 | 2142 | 1.3740          | {'f1': 0.8032786885245903}   | {'accuracy': 0.7984} |
| 0.0009        | 307.0 | 2149 | 1.3820          | {'f1': 0.8024835079549866}   | {'accuracy': 0.7964} |
| 0.0009        | 308.0 | 2156 | 1.3875          | {'f1': 0.802773497688752}    | {'accuracy': 0.7952} |
| 0.0009        | 309.0 | 2163 | 1.3918          | {'f1': 0.8024596464258262}   | {'accuracy': 0.7944} |
| 0.0009        | 310.0 | 2170 | 1.3969          | {'f1': 0.8021390374331552}   | {'accuracy': 0.7928} |
| 0.0009        | 311.0 | 2177 | 1.4012          | {'f1': 0.8006099885627145}   | {'accuracy': 0.7908} |
| 0.0009        | 312.0 | 2184 | 1.4041          | {'f1': 0.8015209125475284}   | {'accuracy': 0.7912} |
| 0.0009        | 313.0 | 2191 | 1.4076          | {'f1': 0.8016717325227963}   | {'accuracy': 0.7912} |
| 0.0009        | 314.0 | 2198 | 1.4100          | {'f1': 0.8010610079575597}   | {'accuracy': 0.79}   |
| 0.0009        | 315.0 | 2205 | 1.4108          | {'f1': 0.8010610079575597}   | {'accuracy': 0.79}   |
| 0.0009        | 316.0 | 2212 | 1.4119          | {'f1': 0.8007575757575758}   | {'accuracy': 0.7896} |
| 0.0009        | 317.0 | 2219 | 1.4135          | {'f1': 0.8006053726825577}   | {'accuracy': 0.7892} |
| 0.0009        | 318.0 | 2226 | 1.4155          | {'f1': 0.8006053726825577}   | {'accuracy': 0.7892} |
| 0.0009        | 319.0 | 2233 | 1.4184          | {'f1': 0.8007561436672966}   | {'accuracy': 0.7892} |
| 0.0009        | 320.0 | 2240 | 1.4205          | {'f1': 0.8001511144692104}   | {'accuracy': 0.7884} |
| 0.0009        | 321.0 | 2247 | 1.4229          | {'f1': 0.7999999999999999}   | {'accuracy': 0.788}  |
| 0.0009        | 322.0 | 2254 | 1.4248          | {'f1': 0.7999999999999999}   | {'accuracy': 0.788}  |
| 0.0009        | 323.0 | 2261 | 1.4236          | {'f1': 0.7999999999999999}   | {'accuracy': 0.788}  |
| 0.0009        | 324.0 | 2268 | 1.4248          | {'f1': 0.7999999999999999}   | {'accuracy': 0.788}  |
| 0.0009        | 325.0 | 2275 | 1.4261          | {'f1': 0.7999999999999999}   | {'accuracy': 0.788}  |
| 0.0009        | 326.0 | 2282 | 1.4265          | {'f1': 0.7999999999999999}   | {'accuracy': 0.788}  |
| 0.0009        | 327.0 | 2289 | 1.4301          | {'f1': 0.7998492272898605}   | {'accuracy': 0.7876} |
| 0.0009        | 328.0 | 2296 | 1.4330          | {'f1': 0.7989457831325301}   | {'accuracy': 0.7864} |
| 0.0009        | 329.0 | 2303 | 1.4356          | {'f1': 0.7980443775855585}   | {'accuracy': 0.7852} |
| 0.0009        | 330.0 | 2310 | 1.4369          | {'f1': 0.7971450037565742}   | {'accuracy': 0.784}  |
| 0.0009        | 331.0 | 2317 | 1.4376          | {'f1': 0.7971450037565742}   | {'accuracy': 0.784}  |
| 0.0009        | 332.0 | 2324 | 1.4397          | {'f1': 0.7966991747936983}   | {'accuracy': 0.7832} |
| 0.0009        | 333.0 | 2331 | 1.4411          | {'f1': 0.7971503562054744}   | {'accuracy': 0.7836} |
| 0.0009        | 334.0 | 2338 | 1.4427          | {'f1': 0.7968515742128937}   | {'accuracy': 0.7832} |
| 0.0009        | 335.0 | 2345 | 1.4436          | {'f1': 0.796553016110903}    | {'accuracy': 0.7828} |
| 0.0009        | 336.0 | 2352 | 1.4445          | {'f1': 0.7959565705728191}   | {'accuracy': 0.782}  |
| 0.0009        | 337.0 | 2359 | 1.4456          | {'f1': 0.7959565705728191}   | {'accuracy': 0.782}  |
| 0.0009        | 338.0 | 2366 | 1.4478          | {'f1': 0.7961092405536849}   | {'accuracy': 0.782}  |
| 0.0009        | 339.0 | 2373 | 1.4502          | {'f1': 0.7959641255605382}   | {'accuracy': 0.7816} |
| 0.0009        | 340.0 | 2380 | 1.4524          | {'f1': 0.7965658827920866}   | {'accuracy': 0.782}  |
| 0.0009        | 341.0 | 2387 | 1.4543          | {'f1': 0.7965658827920866}   | {'accuracy': 0.782}  |
| 0.0009        | 342.0 | 2394 | 1.4566          | {'f1': 0.7971662938105891}   | {'accuracy': 0.7824} |
| 0.0009        | 343.0 | 2401 | 1.4584          | {'f1': 0.7985102420856611}   | {'accuracy': 0.7836} |
| 0.0009        | 344.0 | 2408 | 1.4614          | {'f1': 0.7982129560685035}   | {'accuracy': 0.7832} |
| 0.0009        | 345.0 | 2415 | 1.4634          | {'f1': 0.7982129560685035}   | {'accuracy': 0.7832} |
| 0.0009        | 346.0 | 2422 | 1.4718          | {'f1': 0.796440489432703}    | {'accuracy': 0.7804} |
| 0.0009        | 347.0 | 2429 | 1.4867          | {'f1': 0.7945407598672077}   | {'accuracy': 0.7772} |
| 0.0009        | 348.0 | 2436 | 1.4923          | {'f1': 0.7939661515820456}   | {'accuracy': 0.776}  |
| 0.0009        | 349.0 | 2443 | 1.4946          | {'f1': 0.7944097094520043}   | {'accuracy': 0.7764} |
| 0.0009        | 350.0 | 2450 | 1.4963          | {'f1': 0.7938257993384784}   | {'accuracy': 0.7756} |
| 0.0009        | 351.0 | 2457 | 1.4789          | {'f1': 0.7957068837897854}   | {'accuracy': 0.7792} |
| 0.0009        | 352.0 | 2464 | 1.4684          | {'f1': 0.7973224246931945}   | {'accuracy': 0.782}  |
| 0.0009        | 353.0 | 2471 | 1.4638          | {'f1': 0.7977653631284917}   | {'accuracy': 0.7828} |
| 0.0009        | 354.0 | 2478 | 1.4617          | {'f1': 0.7979120059656973}   | {'accuracy': 0.7832} |
| 0.0009        | 355.0 | 2485 | 1.4615          | {'f1': 0.7979120059656973}   | {'accuracy': 0.7832} |
| 0.0009        | 356.0 | 2492 | 1.4620          | {'f1': 0.7979120059656973}   | {'accuracy': 0.7832} |
| 0.0009        | 357.0 | 2499 | 1.4626          | {'f1': 0.7976146105106224}   | {'accuracy': 0.7828} |
| 0.0003        | 358.0 | 2506 | 1.4612          | {'f1': 0.7974636329727713}   | {'accuracy': 0.7828} |
| 0.0003        | 359.0 | 2513 | 1.4588          | {'f1': 0.7961165048543689}   | {'accuracy': 0.7816} |
| 0.0003        | 360.0 | 2520 | 1.4585          | {'f1': 0.7961165048543689}   | {'accuracy': 0.7816} |
| 0.0003        | 361.0 | 2527 | 1.4592          | {'f1': 0.7961165048543689}   | {'accuracy': 0.7816} |
| 0.0003        | 362.0 | 2534 | 1.4602          | {'f1': 0.7961165048543689}   | {'accuracy': 0.7816} |
| 0.0003        | 363.0 | 2541 | 1.4613          | {'f1': 0.7961165048543689}   | {'accuracy': 0.7816} |
| 0.0003        | 364.0 | 2548 | 1.4631          | {'f1': 0.7974636329727713}   | {'accuracy': 0.7828} |
| 0.0003        | 365.0 | 2555 | 1.4650          | {'f1': 0.7976146105106224}   | {'accuracy': 0.7828} |
| 0.0003        | 366.0 | 2562 | 1.4658          | {'f1': 0.7976146105106224}   | {'accuracy': 0.7828} |
| 0.0003        | 367.0 | 2569 | 1.4660          | {'f1': 0.7976146105106224}   | {'accuracy': 0.7828} |
| 0.0003        | 368.0 | 2576 | 1.4670          | {'f1': 0.797317436661699}    | {'accuracy': 0.7824} |
| 0.0003        | 369.0 | 2583 | 1.4687          | {'f1': 0.7977653631284917}   | {'accuracy': 0.7828} |
| 0.0003        | 370.0 | 2590 | 1.4696          | {'f1': 0.7977653631284917}   | {'accuracy': 0.7828} |
| 0.0003        | 371.0 | 2597 | 1.4700          | {'f1': 0.7977653631284917}   | {'accuracy': 0.7828} |
| 0.0003        | 372.0 | 2604 | 1.4706          | {'f1': 0.7977653631284917}   | {'accuracy': 0.7828} |
| 0.0003        | 373.0 | 2611 | 1.4709          | {'f1': 0.7974683544303798}   | {'accuracy': 0.7824} |
| 0.0003        | 374.0 | 2618 | 1.4711          | {'f1': 0.7977653631284917}   | {'accuracy': 0.7828} |
| 0.0003        | 375.0 | 2625 | 1.4710          | {'f1': 0.7977653631284917}   | {'accuracy': 0.7828} |
| 0.0003        | 376.0 | 2632 | 1.4713          | {'f1': 0.7977653631284917}   | {'accuracy': 0.7828} |
| 0.0003        | 377.0 | 2639 | 1.4730          | {'f1': 0.7974683544303798}   | {'accuracy': 0.7824} |
| 0.0003        | 378.0 | 2646 | 1.4732          | {'f1': 0.7974683544303798}   | {'accuracy': 0.7824} |
| 0.0003        | 379.0 | 2653 | 1.4746          | {'f1': 0.7974683544303798}   | {'accuracy': 0.7824} |
| 0.0003        | 380.0 | 2660 | 1.4789          | {'f1': 0.7965786537746373}   | {'accuracy': 0.7812} |
| 0.0003        | 381.0 | 2667 | 1.4810          | {'f1': 0.7967298402081011}   | {'accuracy': 0.7812} |
| 0.0003        | 382.0 | 2674 | 1.4821          | {'f1': 0.7971768202080238}   | {'accuracy': 0.7816} |
| 0.0003        | 383.0 | 2681 | 1.4820          | {'f1': 0.7971768202080238}   | {'accuracy': 0.7816} |
| 0.0003        | 384.0 | 2688 | 1.4843          | {'f1': 0.7959940652818991}   | {'accuracy': 0.78}   |
| 0.0003        | 385.0 | 2695 | 1.4862          | {'f1': 0.7959940652818991}   | {'accuracy': 0.78}   |
| 0.0003        | 386.0 | 2702 | 1.4866          | {'f1': 0.7956989247311829}   | {'accuracy': 0.7796} |
| 0.0003        | 387.0 | 2709 | 1.4868          | {'f1': 0.7956989247311829}   | {'accuracy': 0.7796} |
| 0.0003        | 388.0 | 2716 | 1.4878          | {'f1': 0.7961452928094884}   | {'accuracy': 0.78}   |
| 0.0003        | 389.0 | 2723 | 1.4885          | {'f1': 0.7958503149314561}   | {'accuracy': 0.7796} |
| 0.0003        | 390.0 | 2730 | 1.4889          | {'f1': 0.7958503149314561}   | {'accuracy': 0.7796} |
| 0.0003        | 391.0 | 2737 | 1.4888          | {'f1': 0.7956989247311829}   | {'accuracy': 0.7796} |
| 0.0003        | 392.0 | 2744 | 1.4904          | {'f1': 0.7957068837897854}   | {'accuracy': 0.7792} |
| 0.0003        | 393.0 | 2751 | 1.4930          | {'f1': 0.7954125046244912}   | {'accuracy': 0.7788} |
| 0.0003        | 394.0 | 2758 | 1.4942          | {'f1': 0.7954125046244912}   | {'accuracy': 0.7788} |
| 0.0003        | 395.0 | 2765 | 1.4946          | {'f1': 0.7954125046244912}   | {'accuracy': 0.7788} |
| 0.0003        | 396.0 | 2772 | 1.4941          | {'f1': 0.7954125046244912}   | {'accuracy': 0.7788} |
| 0.0003        | 397.0 | 2779 | 1.4940          | {'f1': 0.7954125046244912}   | {'accuracy': 0.7788} |
| 0.0003        | 398.0 | 2786 | 1.4942          | {'f1': 0.7954125046244912}   | {'accuracy': 0.7788} |
| 0.0003        | 399.0 | 2793 | 1.4822          | {'f1': 0.7973224246931945}   | {'accuracy': 0.782}  |
| 0.0003        | 400.0 | 2800 | 1.4770          | {'f1': 0.797317436661699}    | {'accuracy': 0.7824} |
| 0.0003        | 401.0 | 2807 | 1.4748          | {'f1': 0.7965658827920866}   | {'accuracy': 0.782}  |
| 0.0003        | 402.0 | 2814 | 1.4739          | {'f1': 0.7961165048543689}   | {'accuracy': 0.7816} |
| 0.0003        | 403.0 | 2821 | 1.4738          | {'f1': 0.7961165048543689}   | {'accuracy': 0.7816} |
| 0.0003        | 404.0 | 2828 | 1.4735          | {'f1': 0.7964138961524094}   | {'accuracy': 0.782}  |
| 0.0003        | 405.0 | 2835 | 1.4730          | {'f1': 0.7964138961524094}   | {'accuracy': 0.782}  |
| 0.0003        | 406.0 | 2842 | 1.4736          | {'f1': 0.7964138961524094}   | {'accuracy': 0.782}  |
| 0.0003        | 407.0 | 2849 | 1.4725          | {'f1': 0.7967115097159939}   | {'accuracy': 0.7824} |
| 0.0003        | 408.0 | 2856 | 1.4748          | {'f1': 0.7961165048543689}   | {'accuracy': 0.7816} |
| 0.0003        | 409.0 | 2863 | 1.4769          | {'f1': 0.7970149253731343}   | {'accuracy': 0.7824} |
| 0.0003        | 410.0 | 2870 | 1.4782          | {'f1': 0.7974636329727713}   | {'accuracy': 0.7828} |
| 0.0003        | 411.0 | 2877 | 1.4788          | {'f1': 0.7971662938105891}   | {'accuracy': 0.7824} |
| 0.0003        | 412.0 | 2884 | 1.4792          | {'f1': 0.7971662938105891}   | {'accuracy': 0.7824} |
| 0.0003        | 413.0 | 2891 | 1.4871          | {'f1': 0.7974730583426236}   | {'accuracy': 0.782}  |
| 0.0003        | 414.0 | 2898 | 1.4949          | {'f1': 0.7959940652818991}   | {'accuracy': 0.78}   |
| 0.0003        | 415.0 | 2905 | 1.4969          | {'f1': 0.7958503149314561}   | {'accuracy': 0.7796} |
| 0.0003        | 416.0 | 2912 | 1.4979          | {'f1': 0.7955555555555556}   | {'accuracy': 0.7792} |
| 0.0003        | 417.0 | 2919 | 1.4989          | {'f1': 0.7949666913397484}   | {'accuracy': 0.7784} |
| 0.0003        | 418.0 | 2926 | 1.4976          | {'f1': 0.7955555555555556}   | {'accuracy': 0.7792} |
| 0.0003        | 419.0 | 2933 | 1.4964          | {'f1': 0.7956989247311829}   | {'accuracy': 0.7796} |
| 0.0003        | 420.0 | 2940 | 1.4958          | {'f1': 0.7959940652818991}   | {'accuracy': 0.78}   |
| 0.0003        | 421.0 | 2947 | 1.4959          | {'f1': 0.7959940652818991}   | {'accuracy': 0.78}   |
| 0.0003        | 422.0 | 2954 | 1.4963          | {'f1': 0.7959940652818991}   | {'accuracy': 0.78}   |
| 0.0003        | 423.0 | 2961 | 1.4968          | {'f1': 0.7956989247311829}   | {'accuracy': 0.7796} |
| 0.0003        | 424.0 | 2968 | 1.4971          | {'f1': 0.7956989247311829}   | {'accuracy': 0.7796} |
| 0.0003        | 425.0 | 2975 | 1.4971          | {'f1': 0.7956989247311829}   | {'accuracy': 0.7796} |
| 0.0003        | 426.0 | 2982 | 1.4980          | {'f1': 0.7961452928094884}   | {'accuracy': 0.78}   |
| 0.0003        | 427.0 | 2989 | 1.4986          | {'f1': 0.7961452928094884}   | {'accuracy': 0.78}   |
| 0.0003        | 428.0 | 2996 | 1.4990          | {'f1': 0.7961452928094884}   | {'accuracy': 0.78}   |
| 0.0           | 429.0 | 3003 | 1.4993          | {'f1': 0.7955555555555556}   | {'accuracy': 0.7792} |
| 0.0           | 430.0 | 3010 | 1.4997          | {'f1': 0.7955555555555556}   | {'accuracy': 0.7792} |
| 0.0           | 431.0 | 3017 | 1.5001          | {'f1': 0.7955555555555556}   | {'accuracy': 0.7792} |
| 0.0           | 432.0 | 3024 | 1.5005          | {'f1': 0.7955555555555556}   | {'accuracy': 0.7792} |
| 0.0           | 433.0 | 3031 | 1.5009          | {'f1': 0.7955555555555556}   | {'accuracy': 0.7792} |
| 0.0           | 434.0 | 3038 | 1.5007          | {'f1': 0.7955555555555556}   | {'accuracy': 0.7792} |
| 0.0           | 435.0 | 3045 | 1.4997          | {'f1': 0.7961452928094884}   | {'accuracy': 0.78}   |
| 0.0           | 436.0 | 3052 | 1.4990          | {'f1': 0.7961452928094884}   | {'accuracy': 0.78}   |
| 0.0           | 437.0 | 3059 | 1.4991          | {'f1': 0.7961452928094884}   | {'accuracy': 0.78}   |
| 0.0           | 438.0 | 3066 | 1.4995          | {'f1': 0.7961452928094884}   | {'accuracy': 0.78}   |
| 0.0           | 439.0 | 3073 | 1.4997          | {'f1': 0.7961452928094884}   | {'accuracy': 0.78}   |
| 0.0           | 440.0 | 3080 | 1.4998          | {'f1': 0.7961452928094884}   | {'accuracy': 0.78}   |
| 0.0           | 441.0 | 3087 | 1.4999          | {'f1': 0.7961452928094884}   | {'accuracy': 0.78}   |
| 0.0           | 442.0 | 3094 | 1.5000          | {'f1': 0.7961452928094884}   | {'accuracy': 0.78}   |
| 0.0           | 443.0 | 3101 | 1.5003          | {'f1': 0.7961452928094884}   | {'accuracy': 0.78}   |
| 0.0           | 444.0 | 3108 | 1.5005          | {'f1': 0.7961452928094884}   | {'accuracy': 0.78}   |
| 0.0           | 445.0 | 3115 | 1.5005          | {'f1': 0.7961452928094884}   | {'accuracy': 0.78}   |
| 0.0           | 446.0 | 3122 | 1.5002          | {'f1': 0.796440489432703}    | {'accuracy': 0.7804} |
| 0.0           | 447.0 | 3129 | 1.5000          | {'f1': 0.796440489432703}    | {'accuracy': 0.7804} |
| 0.0           | 448.0 | 3136 | 1.4999          | {'f1': 0.796440489432703}    | {'accuracy': 0.7804} |
| 0.0           | 449.0 | 3143 | 1.4999          | {'f1': 0.796440489432703}    | {'accuracy': 0.7804} |
| 0.0           | 450.0 | 3150 | 1.5001          | {'f1': 0.796440489432703}    | {'accuracy': 0.7804} |
| 0.0           | 451.0 | 3157 | 1.5003          | {'f1': 0.796440489432703}    | {'accuracy': 0.7804} |
| 0.0           | 452.0 | 3164 | 1.5006          | {'f1': 0.796440489432703}    | {'accuracy': 0.7804} |
| 0.0           | 453.0 | 3171 | 1.5007          | {'f1': 0.796440489432703}    | {'accuracy': 0.7804} |
| 0.0           | 454.0 | 3178 | 1.5007          | {'f1': 0.796440489432703}    | {'accuracy': 0.7804} |
| 0.0           | 455.0 | 3185 | 1.5007          | {'f1': 0.796440489432703}    | {'accuracy': 0.7804} |
| 0.0           | 456.0 | 3192 | 1.4999          | {'f1': 0.7962894248608535}   | {'accuracy': 0.7804} |
| 0.0           | 457.0 | 3199 | 1.4997          | {'f1': 0.7968808020794653}   | {'accuracy': 0.7812} |
| 0.0           | 458.0 | 3206 | 1.4995          | {'f1': 0.7968808020794653}   | {'accuracy': 0.7812} |
| 0.0           | 459.0 | 3213 | 1.4996          | {'f1': 0.7971768202080238}   | {'accuracy': 0.7816} |
| 0.0           | 460.0 | 3220 | 1.4997          | {'f1': 0.7968808020794653}   | {'accuracy': 0.7812} |
| 0.0           | 461.0 | 3227 | 1.4999          | {'f1': 0.7968808020794653}   | {'accuracy': 0.7812} |
| 0.0           | 462.0 | 3234 | 1.5001          | {'f1': 0.7968808020794653}   | {'accuracy': 0.7812} |
| 0.0           | 463.0 | 3241 | 1.5006          | {'f1': 0.7962894248608535}   | {'accuracy': 0.7804} |
| 0.0           | 464.0 | 3248 | 1.5008          | {'f1': 0.7962894248608535}   | {'accuracy': 0.7804} |
| 0.0           | 465.0 | 3255 | 1.5010          | {'f1': 0.7962894248608535}   | {'accuracy': 0.7804} |
| 0.0           | 466.0 | 3262 | 1.5010          | {'f1': 0.7962894248608535}   | {'accuracy': 0.7804} |
| 0.0           | 467.0 | 3269 | 1.5012          | {'f1': 0.7962894248608535}   | {'accuracy': 0.7804} |
| 0.0           | 468.0 | 3276 | 1.5014          | {'f1': 0.7967359050445103}   | {'accuracy': 0.7808} |
| 0.0           | 469.0 | 3283 | 1.5015          | {'f1': 0.7967359050445103}   | {'accuracy': 0.7808} |
| 0.0           | 470.0 | 3290 | 1.5017          | {'f1': 0.7967359050445103}   | {'accuracy': 0.7808} |
| 0.0           | 471.0 | 3297 | 1.5020          | {'f1': 0.7967359050445103}   | {'accuracy': 0.7808} |
| 0.0           | 472.0 | 3304 | 1.5022          | {'f1': 0.7967359050445103}   | {'accuracy': 0.7808} |
| 0.0           | 473.0 | 3311 | 1.5023          | {'f1': 0.796440489432703}    | {'accuracy': 0.7804} |
| 0.0           | 474.0 | 3318 | 1.5020          | {'f1': 0.7967359050445103}   | {'accuracy': 0.7808} |
| 0.0           | 475.0 | 3325 | 1.5020          | {'f1': 0.7967359050445103}   | {'accuracy': 0.7808} |
| 0.0           | 476.0 | 3332 | 1.5021          | {'f1': 0.7967359050445103}   | {'accuracy': 0.7808} |
| 0.0           | 477.0 | 3339 | 1.5020          | {'f1': 0.7967359050445103}   | {'accuracy': 0.7808} |
| 0.0           | 478.0 | 3346 | 1.5025          | {'f1': 0.7967359050445103}   | {'accuracy': 0.7808} |
| 0.0           | 479.0 | 3353 | 1.5029          | {'f1': 0.796440489432703}    | {'accuracy': 0.7804} |
| 0.0           | 480.0 | 3360 | 1.5032          | {'f1': 0.796440489432703}    | {'accuracy': 0.7804} |
| 0.0           | 481.0 | 3367 | 1.5035          | {'f1': 0.796440489432703}    | {'accuracy': 0.7804} |
| 0.0           | 482.0 | 3374 | 1.5036          | {'f1': 0.796440489432703}    | {'accuracy': 0.7804} |
| 0.0           | 483.0 | 3381 | 1.5036          | {'f1': 0.796440489432703}    | {'accuracy': 0.7804} |
| 0.0           | 484.0 | 3388 | 1.5037          | {'f1': 0.796440489432703}    | {'accuracy': 0.7804} |
| 0.0           | 485.0 | 3395 | 1.5037          | {'f1': 0.796440489432703}    | {'accuracy': 0.7804} |
| 0.0           | 486.0 | 3402 | 1.5037          | {'f1': 0.796440489432703}    | {'accuracy': 0.7804} |
| 0.0           | 487.0 | 3409 | 1.5036          | {'f1': 0.796440489432703}    | {'accuracy': 0.7804} |
| 0.0           | 488.0 | 3416 | 1.5036          | {'f1': 0.796440489432703}    | {'accuracy': 0.7804} |
| 0.0           | 489.0 | 3423 | 1.5030          | {'f1': 0.7967359050445103}   | {'accuracy': 0.7808} |
| 0.0           | 490.0 | 3430 | 1.5028          | {'f1': 0.7967359050445103}   | {'accuracy': 0.7808} |
| 0.0           | 491.0 | 3437 | 1.5027          | {'f1': 0.7967359050445103}   | {'accuracy': 0.7808} |
| 0.0           | 492.0 | 3444 | 1.5026          | {'f1': 0.7967359050445103}   | {'accuracy': 0.7808} |
| 0.0           | 493.0 | 3451 | 1.5026          | {'f1': 0.7967359050445103}   | {'accuracy': 0.7808} |
| 0.0           | 494.0 | 3458 | 1.5033          | {'f1': 0.796440489432703}    | {'accuracy': 0.7804} |
| 0.0           | 495.0 | 3465 | 1.5041          | {'f1': 0.796440489432703}    | {'accuracy': 0.7804} |
| 0.0           | 496.0 | 3472 | 1.5042          | {'f1': 0.796440489432703}    | {'accuracy': 0.7804} |
| 0.0           | 497.0 | 3479 | 1.5041          | {'f1': 0.796440489432703}    | {'accuracy': 0.7804} |
| 0.0           | 498.0 | 3486 | 1.5041          | {'f1': 0.796440489432703}    | {'accuracy': 0.7804} |
| 0.0           | 499.0 | 3493 | 1.5041          | {'f1': 0.796440489432703}    | {'accuracy': 0.7804} |
| 0.0           | 500.0 | 3500 | 1.5041          | {'f1': 0.796440489432703}    | {'accuracy': 0.7804} |


### Framework versions

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