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_200
  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_200

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: 1.2900
- F1: {'f1': 0.8454581203303184}
- Accuracy: {'accuracy': 0.8428}

## 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   | 13   | 0.6838          | {'f1': 0.4936336924583742} | {'accuracy': 0.5864} |
| No log        | 2.0   | 26   | 0.6797          | {'f1': 0.6062630480167014} | {'accuracy': 0.6228} |
| No log        | 3.0   | 39   | 0.6750          | {'f1': 0.6275320380322448} | {'accuracy': 0.6396} |
| No log        | 4.0   | 52   | 0.6665          | {'f1': 0.5731764705882353} | {'accuracy': 0.6372} |
| No log        | 5.0   | 65   | 0.6516          | {'f1': 0.6677165354330709} | {'accuracy': 0.6624} |
| No log        | 6.0   | 78   | 0.6311          | {'f1': 0.6467304625199363} | {'accuracy': 0.6456} |
| No log        | 7.0   | 91   | 0.6141          | {'f1': 0.6289969338589575} | {'accuracy': 0.6612} |
| No log        | 8.0   | 104  | 0.6083          | {'f1': 0.7377521613832855} | {'accuracy': 0.6724} |
| No log        | 9.0   | 117  | 0.5541          | {'f1': 0.7028571428571428} | {'accuracy': 0.7088} |
| No log        | 10.0  | 130  | 0.5549          | {'f1': 0.7053223712678496} | {'accuracy': 0.7276} |
| No log        | 11.0  | 143  | 0.5078          | {'f1': 0.7664205207928487} | {'accuracy': 0.7596} |
| No log        | 12.0  | 156  | 0.5045          | {'f1': 0.7668179942220389} | {'accuracy': 0.774}  |
| No log        | 13.0  | 169  | 0.6035          | {'f1': 0.7178538390379279} | {'accuracy': 0.756}  |
| No log        | 14.0  | 182  | 0.4684          | {'f1': 0.8066090874953061} | {'accuracy': 0.794}  |
| No log        | 15.0  | 195  | 0.5285          | {'f1': 0.8026826685492411} | {'accuracy': 0.7764} |
| No log        | 16.0  | 208  | 0.5310          | {'f1': 0.7957166392092258} | {'accuracy': 0.8016} |
| No log        | 17.0  | 221  | 0.5379          | {'f1': 0.804374240583232}  | {'accuracy': 0.8068} |
| No log        | 18.0  | 234  | 0.5588          | {'f1': 0.8113509192645884} | {'accuracy': 0.8112} |
| No log        | 19.0  | 247  | 0.6324          | {'f1': 0.8022118247554233} | {'accuracy': 0.814}  |
| No log        | 20.0  | 260  | 0.6471          | {'f1': 0.8049090139652983} | {'accuracy': 0.8156} |
| No log        | 21.0  | 273  | 0.6830          | {'f1': 0.8250180766449747} | {'accuracy': 0.8064} |
| No log        | 22.0  | 286  | 0.6541          | {'f1': 0.8073541167066347} | {'accuracy': 0.8072} |
| No log        | 23.0  | 299  | 0.7929          | {'f1': 0.7772887323943662} | {'accuracy': 0.7976} |
| No log        | 24.0  | 312  | 0.7272          | {'f1': 0.8254558987718645} | {'accuracy': 0.8124} |
| No log        | 25.0  | 325  | 0.7526          | {'f1': 0.8225205070842654} | {'accuracy': 0.8096} |
| No log        | 26.0  | 338  | 0.7777          | {'f1': 0.8013245033112583} | {'accuracy': 0.808}  |
| No log        | 27.0  | 351  | 0.7733          | {'f1': 0.8103025347506132} | {'accuracy': 0.8144} |
| No log        | 28.0  | 364  | 0.7493          | {'f1': 0.8281733746130031} | {'accuracy': 0.8224} |
| No log        | 29.0  | 377  | 0.7909          | {'f1': 0.8305524657026326} | {'accuracy': 0.8172} |
| No log        | 30.0  | 390  | 0.8281          | {'f1': 0.8091797705057374} | {'accuracy': 0.8204} |
| No log        | 31.0  | 403  | 0.7747          | {'f1': 0.8305214723926382} | {'accuracy': 0.8232} |
| No log        | 32.0  | 416  | 0.7940          | {'f1': 0.8261904761904763} | {'accuracy': 0.8248} |
| No log        | 33.0  | 429  | 0.8295          | {'f1': 0.8210101010101011} | {'accuracy': 0.8228} |
| No log        | 34.0  | 442  | 0.8768          | {'f1': 0.8304832713754647} | {'accuracy': 0.8176} |
| No log        | 35.0  | 455  | 0.8526          | {'f1': 0.8249902987970508} | {'accuracy': 0.8196} |
| No log        | 36.0  | 468  | 0.8708          | {'f1': 0.8272692454998085} | {'accuracy': 0.8196} |
| No log        | 37.0  | 481  | 0.9140          | {'f1': 0.8084929225645296} | {'accuracy': 0.816}  |
| No log        | 38.0  | 494  | 0.9014          | {'f1': 0.8198903680501174} | {'accuracy': 0.816}  |
| 0.2225        | 39.0  | 507  | 0.9189          | {'f1': 0.8225806451612904} | {'accuracy': 0.8152} |
| 0.2225        | 40.0  | 520  | 0.9125          | {'f1': 0.8178528347406514} | {'accuracy': 0.8188} |
| 0.2225        | 41.0  | 533  | 0.9240          | {'f1': 0.8292867981790591} | {'accuracy': 0.82}   |
| 0.2225        | 42.0  | 546  | 1.0189          | {'f1': 0.8013757523645744} | {'accuracy': 0.8152} |
| 0.2225        | 43.0  | 559  | 0.9304          | {'f1': 0.8307341194370484} | {'accuracy': 0.822}  |
| 0.2225        | 44.0  | 572  | 0.9441          | {'f1': 0.8154541718043566} | {'accuracy': 0.8204} |
| 0.2225        | 45.0  | 585  | 0.9274          | {'f1': 0.8325652841781874} | {'accuracy': 0.8256} |
| 0.2225        | 46.0  | 598  | 0.9291          | {'f1': 0.820859872611465}  | {'accuracy': 0.82}   |
| 0.2225        | 47.0  | 611  | 0.9480          | {'f1': 0.8347826086956521} | {'accuracy': 0.8252} |
| 0.2225        | 48.0  | 624  | 0.9415          | {'f1': 0.8215999999999999} | {'accuracy': 0.8216} |
| 0.2225        | 49.0  | 637  | 0.9453          | {'f1': 0.8219395866454692} | {'accuracy': 0.8208} |
| 0.2225        | 50.0  | 650  | 0.9554          | {'f1': 0.8202247191011236} | {'accuracy': 0.8208} |
| 0.2225        | 51.0  | 663  | 0.9543          | {'f1': 0.8288499025341132} | {'accuracy': 0.8244} |
| 0.2225        | 52.0  | 676  | 0.9627          | {'f1': 0.8257605689450809} | {'accuracy': 0.8236} |
| 0.2225        | 53.0  | 689  | 0.9995          | {'f1': 0.8353955755530559} | {'accuracy': 0.8244} |
| 0.2225        | 54.0  | 702  | 1.0324          | {'f1': 0.8162411050648808} | {'accuracy': 0.8244} |
| 0.2225        | 55.0  | 715  | 0.9892          | {'f1': 0.8340360291299349} | {'accuracy': 0.8268} |
| 0.2225        | 56.0  | 728  | 1.0115          | {'f1': 0.8368421052631578} | {'accuracy': 0.8264} |
| 0.2225        | 57.0  | 741  | 0.9859          | {'f1': 0.8211284513805521} | {'accuracy': 0.8212} |
| 0.2225        | 58.0  | 754  | 0.9863          | {'f1': 0.8229208117787505} | {'accuracy': 0.822}  |
| 0.2225        | 59.0  | 767  | 0.9881          | {'f1': 0.8242760809202697} | {'accuracy': 0.8228} |
| 0.2225        | 60.0  | 780  | 1.0011          | {'f1': 0.8231017770597738} | {'accuracy': 0.8248} |
| 0.2225        | 61.0  | 793  | 1.0023          | {'f1': 0.8230088495575221} | {'accuracy': 0.824}  |
| 0.2225        | 62.0  | 806  | 1.0396          | {'f1': 0.8376768428890543} | {'accuracy': 0.8256} |
| 0.2225        | 63.0  | 819  | 1.0426          | {'f1': 0.8186314921681782} | {'accuracy': 0.824}  |
| 0.2225        | 64.0  | 832  | 1.0070          | {'f1': 0.8289368505195842} | {'accuracy': 0.8288} |
| 0.2225        | 65.0  | 845  | 1.0800          | {'f1': 0.8133445945945947} | {'accuracy': 0.8232} |
| 0.2225        | 66.0  | 858  | 1.0260          | {'f1': 0.8400000000000001} | {'accuracy': 0.8304} |
| 0.2225        | 67.0  | 871  | 0.9988          | {'f1': 0.8431975403535741} | {'accuracy': 0.8368} |
| 0.2225        | 68.0  | 884  | 0.9941          | {'f1': 0.8359157727453318} | {'accuracy': 0.8348} |
| 0.2225        | 69.0  | 897  | 0.9941          | {'f1': 0.8361045130641329} | {'accuracy': 0.8344} |
| 0.2225        | 70.0  | 910  | 0.9947          | {'f1': 0.8414872798434442} | {'accuracy': 0.838}  |
| 0.2225        | 71.0  | 923  | 0.9967          | {'f1': 0.8386336866902239} | {'accuracy': 0.8356} |
| 0.2225        | 72.0  | 936  | 0.9986          | {'f1': 0.8368794326241136} | {'accuracy': 0.8344} |
| 0.2225        | 73.0  | 949  | 0.9997          | {'f1': 0.8405797101449276} | {'accuracy': 0.8372} |
| 0.2225        | 74.0  | 962  | 1.0061          | {'f1': 0.843484965304549}  | {'accuracy': 0.8376} |
| 0.2225        | 75.0  | 975  | 1.0038          | {'f1': 0.8365498227648681} | {'accuracy': 0.834}  |
| 0.2225        | 76.0  | 988  | 1.0058          | {'f1': 0.8421875}          | {'accuracy': 0.8384} |
| 0.0026        | 77.0  | 1001 | 1.0094          | {'f1': 0.8420644159875824} | {'accuracy': 0.8372} |
| 0.0026        | 78.0  | 1014 | 1.0182          | {'f1': 0.8348660535785687} | {'accuracy': 0.8348} |
| 0.0026        | 79.0  | 1027 | 1.0331          | {'f1': 0.8284789644012945} | {'accuracy': 0.8304} |
| 0.0026        | 80.0  | 1040 | 1.0148          | {'f1': 0.8374851720047448} | {'accuracy': 0.8356} |
| 0.0026        | 81.0  | 1053 | 1.0145          | {'f1': 0.8407843137254902} | {'accuracy': 0.8376} |
| 0.0026        | 82.0  | 1066 | 1.0158          | {'f1': 0.8442014837953924} | {'accuracy': 0.8404} |
| 0.0026        | 83.0  | 1079 | 1.0175          | {'f1': 0.8450155763239875} | {'accuracy': 0.8408} |
| 0.0026        | 84.0  | 1092 | 1.0210          | {'f1': 0.8445475638051044} | {'accuracy': 0.8392} |
| 0.0026        | 85.0  | 1105 | 1.0216          | {'f1': 0.8375394321766562} | {'accuracy': 0.8352} |
| 0.0026        | 86.0  | 1118 | 1.0259          | {'f1': 0.8445998445998446} | {'accuracy': 0.84}   |
| 0.0026        | 87.0  | 1131 | 1.0277          | {'f1': 0.8435797665369649} | {'accuracy': 0.8392} |
| 0.0026        | 88.0  | 1144 | 1.0295          | {'f1': 0.8370808678500985} | {'accuracy': 0.8348} |
| 0.0026        | 89.0  | 1157 | 1.0533          | {'f1': 0.8439393939393939} | {'accuracy': 0.8352} |
| 0.0026        | 90.0  | 1170 | 1.0387          | {'f1': 0.8324022346368716} | {'accuracy': 0.832}  |
| 0.0026        | 91.0  | 1183 | 1.0292          | {'f1': 0.8400469299960892} | {'accuracy': 0.8364} |
| 0.0026        | 92.0  | 1196 | 1.0678          | {'f1': 0.8426966292134832} | {'accuracy': 0.832}  |
| 0.0026        | 93.0  | 1209 | 1.1813          | {'f1': 0.8108340498710231} | {'accuracy': 0.824}  |
| 0.0026        | 94.0  | 1222 | 1.0600          | {'f1': 0.8343848580441642} | {'accuracy': 0.832}  |
| 0.0026        | 95.0  | 1235 | 1.0988          | {'f1': 0.8407978923598042} | {'accuracy': 0.8308} |
| 0.0026        | 96.0  | 1248 | 1.0773          | {'f1': 0.8406020841373987} | {'accuracy': 0.8348} |
| 0.0026        | 97.0  | 1261 | 1.0753          | {'f1': 0.8380803745610613} | {'accuracy': 0.834}  |
| 0.0026        | 98.0  | 1274 | 1.0759          | {'f1': 0.8375}             | {'accuracy': 0.8336} |
| 0.0026        | 99.0  | 1287 | 1.0779          | {'f1': 0.8406359053896859} | {'accuracy': 0.8356} |
| 0.0026        | 100.0 | 1300 | 1.0779          | {'f1': 0.8404669260700389} | {'accuracy': 0.836}  |
| 0.0026        | 101.0 | 1313 | 1.0856          | {'f1': 0.830488289003573}  | {'accuracy': 0.8292} |
| 0.0026        | 102.0 | 1326 | 1.1032          | {'f1': 0.8284789644012945} | {'accuracy': 0.8304} |
| 0.0026        | 103.0 | 1339 | 1.0956          | {'f1': 0.8302788844621515} | {'accuracy': 0.8296} |
| 0.0026        | 104.0 | 1352 | 1.0922          | {'f1': 0.8408385093167702} | {'accuracy': 0.836}  |
| 0.0026        | 105.0 | 1365 | 1.1688          | {'f1': 0.823185988323603}  | {'accuracy': 0.8304} |
| 0.0026        | 106.0 | 1378 | 1.1361          | {'f1': 0.8336579664978575} | {'accuracy': 0.8292} |
| 0.0026        | 107.0 | 1391 | 1.1736          | {'f1': 0.8191489361702128} | {'accuracy': 0.8232} |
| 0.0026        | 108.0 | 1404 | 1.1447          | {'f1': 0.8337273443656423} | {'accuracy': 0.8312} |
| 0.0026        | 109.0 | 1417 | 1.1207          | {'f1': 0.8367906066536203} | {'accuracy': 0.8332} |
| 0.0026        | 110.0 | 1430 | 1.1612          | {'f1': 0.8235782482357824} | {'accuracy': 0.83}   |
| 0.0026        | 111.0 | 1443 | 1.1338          | {'f1': 0.82429677945373}   | {'accuracy': 0.8276} |
| 0.0026        | 112.0 | 1456 | 1.1216          | {'f1': 0.8268921095008052} | {'accuracy': 0.828}  |
| 0.0026        | 113.0 | 1469 | 1.1147          | {'f1': 0.8370078740157479} | {'accuracy': 0.8344} |
| 0.0026        | 114.0 | 1482 | 1.1215          | {'f1': 0.8283881315156376} | {'accuracy': 0.8288} |
| 0.0026        | 115.0 | 1495 | 1.1465          | {'f1': 0.8249282492824928} | {'accuracy': 0.8292} |
| 0.0011        | 116.0 | 1508 | 1.1374          | {'f1': 0.8260692464358452} | {'accuracy': 0.8292} |
| 0.0011        | 117.0 | 1521 | 1.1196          | {'f1': 0.8351042896497441} | {'accuracy': 0.8324} |
| 0.0011        | 118.0 | 1534 | 1.1283          | {'f1': 0.8363496341932999} | {'accuracy': 0.83}   |
| 0.0011        | 119.0 | 1547 | 1.1356          | {'f1': 0.8367658276125095} | {'accuracy': 0.8288} |
| 0.0011        | 120.0 | 1560 | 1.1272          | {'f1': 0.8368684920940996} | {'accuracy': 0.8308} |
| 0.0011        | 121.0 | 1573 | 1.1234          | {'f1': 0.8345834978286616} | {'accuracy': 0.8324} |
| 0.0011        | 122.0 | 1586 | 1.1260          | {'f1': 0.8347826086956521} | {'accuracy': 0.8328} |
| 0.0011        | 123.0 | 1599 | 1.1276          | {'f1': 0.8333333333333333} | {'accuracy': 0.832}  |
| 0.0011        | 124.0 | 1612 | 1.1281          | {'f1': 0.8341907400079145} | {'accuracy': 0.8324} |
| 0.0011        | 125.0 | 1625 | 1.1284          | {'f1': 0.8352429869616753} | {'accuracy': 0.8332} |
| 0.0011        | 126.0 | 1638 | 1.1284          | {'f1': 0.838407494145199}  | {'accuracy': 0.8344} |
| 0.0011        | 127.0 | 1651 | 1.1387          | {'f1': 0.8358208955223881} | {'accuracy': 0.8284} |
| 0.0011        | 128.0 | 1664 | 1.1407          | {'f1': 0.8376003056935423} | {'accuracy': 0.83}   |
| 0.0011        | 129.0 | 1677 | 1.1373          | {'f1': 0.83531669865643}   | {'accuracy': 0.8284} |
| 0.0011        | 130.0 | 1690 | 1.1350          | {'f1': 0.837962962962963}  | {'accuracy': 0.832}  |
| 0.0011        | 131.0 | 1703 | 1.2047          | {'f1': 0.8214585079631181} | {'accuracy': 0.8296} |
| 0.0011        | 132.0 | 1716 | 1.2042          | {'f1': 0.8209205020920501} | {'accuracy': 0.8288} |
| 0.0011        | 133.0 | 1729 | 1.1449          | {'f1': 0.8341232227488151} | {'accuracy': 0.832}  |
| 0.0011        | 134.0 | 1742 | 1.1475          | {'f1': 0.8383326840670042} | {'accuracy': 0.834}  |
| 0.0011        | 135.0 | 1755 | 1.1501          | {'f1': 0.8391608391608392} | {'accuracy': 0.8344} |
| 0.0011        | 136.0 | 1768 | 1.1523          | {'f1': 0.8395348837209303} | {'accuracy': 0.8344} |
| 0.0011        | 137.0 | 1781 | 1.1525          | {'f1': 0.8389600310438494} | {'accuracy': 0.834}  |
| 0.0011        | 138.0 | 1794 | 1.1521          | {'f1': 0.8387096774193549} | {'accuracy': 0.834}  |
| 0.0011        | 139.0 | 1807 | 1.1515          | {'f1': 0.8324066719618745} | {'accuracy': 0.8312} |
| 0.0011        | 140.0 | 1820 | 1.1557          | {'f1': 0.8304609218436874} | {'accuracy': 0.8308} |
| 0.0011        | 141.0 | 1833 | 1.1555          | {'f1': 0.8302642113690952} | {'accuracy': 0.8304} |
| 0.0011        | 142.0 | 1846 | 1.1542          | {'f1': 0.8335310399367338} | {'accuracy': 0.8316} |
| 0.0011        | 143.0 | 1859 | 1.1551          | {'f1': 0.8344527854602923} | {'accuracy': 0.8324} |
| 0.0011        | 144.0 | 1872 | 1.1559          | {'f1': 0.8345834978286616} | {'accuracy': 0.8324} |
| 0.0011        | 145.0 | 1885 | 1.1564          | {'f1': 0.8349743993698308} | {'accuracy': 0.8324} |
| 0.0011        | 146.0 | 1898 | 1.1570          | {'f1': 0.8343171979535616} | {'accuracy': 0.8316} |
| 0.0011        | 147.0 | 1911 | 1.1580          | {'f1': 0.8363351605324981} | {'accuracy': 0.8328} |
| 0.0011        | 148.0 | 1924 | 1.1590          | {'f1': 0.836591086786552}  | {'accuracy': 0.8328} |
| 0.0011        | 149.0 | 1937 | 1.1954          | {'f1': 0.8246406570841888} | {'accuracy': 0.8292} |
| 0.0011        | 150.0 | 1950 | 1.1790          | {'f1': 0.8298217179902755} | {'accuracy': 0.832}  |
| 0.0011        | 151.0 | 1963 | 1.1656          | {'f1': 0.8391337973704562} | {'accuracy': 0.8336} |
| 0.0011        | 152.0 | 1976 | 1.1879          | {'f1': 0.8270248270248269} | {'accuracy': 0.83}   |
| 0.0011        | 153.0 | 1989 | 1.2103          | {'f1': 0.8394216133942161} | {'accuracy': 0.8312} |
| 0.0001        | 154.0 | 2002 | 1.2977          | {'f1': 0.8091216216216216} | {'accuracy': 0.8192} |
| 0.0001        | 155.0 | 2015 | 1.3165          | {'f1': 0.8057675996607293} | {'accuracy': 0.8168} |
| 0.0001        | 156.0 | 2028 | 1.2406          | {'f1': 0.8365019011406845} | {'accuracy': 0.828}  |
| 0.0001        | 157.0 | 2041 | 1.3378          | {'f1': 0.7991360691144708} | {'accuracy': 0.814}  |
| 0.0001        | 158.0 | 2054 | 1.2219          | {'f1': 0.8351987649556156} | {'accuracy': 0.8292} |
| 0.0001        | 159.0 | 2067 | 1.2792          | {'f1': 0.8146605581007913} | {'accuracy': 0.822}  |
| 0.0001        | 160.0 | 2080 | 1.2839          | {'f1': 0.8284765769088898} | {'accuracy': 0.814}  |
| 0.0001        | 161.0 | 2093 | 1.1911          | {'f1': 0.8387841477491342} | {'accuracy': 0.8324} |
| 0.0001        | 162.0 | 2106 | 1.1718          | {'f1': 0.8349056603773586} | {'accuracy': 0.832}  |
| 0.0001        | 163.0 | 2119 | 1.2825          | {'f1': 0.8401323042998898} | {'accuracy': 0.826}  |
| 0.0001        | 164.0 | 2132 | 1.1686          | {'f1': 0.838785046728972}  | {'accuracy': 0.8344} |
| 0.0001        | 165.0 | 2145 | 1.2342          | {'f1': 0.8240200166805671} | {'accuracy': 0.8312} |
| 0.0001        | 166.0 | 2158 | 1.1921          | {'f1': 0.8321108394458028} | {'accuracy': 0.8352} |
| 0.0001        | 167.0 | 2171 | 1.1739          | {'f1': 0.838375796178344}  | {'accuracy': 0.8376} |
| 0.0001        | 168.0 | 2184 | 1.1728          | {'f1': 0.8421468034727704} | {'accuracy': 0.84}   |
| 0.0001        | 169.0 | 2197 | 1.1747          | {'f1': 0.8401253918495297} | {'accuracy': 0.8368} |
| 0.0001        | 170.0 | 2210 | 1.1757          | {'f1': 0.8410777040218664} | {'accuracy': 0.8372} |
| 0.0001        | 171.0 | 2223 | 1.1773          | {'f1': 0.8403426791277258} | {'accuracy': 0.836}  |
| 0.0001        | 172.0 | 2236 | 1.1820          | {'f1': 0.8403100775193799} | {'accuracy': 0.8352} |
| 0.0001        | 173.0 | 2249 | 1.1857          | {'f1': 0.8406805877803558} | {'accuracy': 0.8352} |
| 0.0001        | 174.0 | 2262 | 1.1852          | {'f1': 0.8405572755417957} | {'accuracy': 0.8352} |
| 0.0001        | 175.0 | 2275 | 1.2516          | {'f1': 0.8230383973288814} | {'accuracy': 0.8304} |
| 0.0001        | 176.0 | 2288 | 1.2024          | {'f1': 0.8402321083172147} | {'accuracy': 0.8348} |
| 0.0001        | 177.0 | 2301 | 1.2116          | {'f1': 0.8333999200958849} | {'accuracy': 0.8332} |
| 0.0001        | 178.0 | 2314 | 1.4179          | {'f1': 0.8014028934677773} | {'accuracy': 0.8188} |
| 0.0001        | 179.0 | 2327 | 2.1209          | {'f1': 0.7948051948051948} | {'accuracy': 0.7472} |
| 0.0001        | 180.0 | 2340 | 1.2614          | {'f1': 0.8272425249169434} | {'accuracy': 0.8336} |
| 0.0001        | 181.0 | 2353 | 1.4028          | {'f1': 0.8334529791816224} | {'accuracy': 0.8144} |
| 0.0001        | 182.0 | 2366 | 1.2493          | {'f1': 0.8324324324324325} | {'accuracy': 0.8264} |
| 0.0001        | 183.0 | 2379 | 1.2906          | {'f1': 0.8196319018404908} | {'accuracy': 0.8236} |
| 0.0001        | 184.0 | 2392 | 1.4300          | {'f1': 0.7944492627927148} | {'accuracy': 0.8104} |
| 0.0001        | 185.0 | 2405 | 1.3032          | {'f1': 0.8229208117787505} | {'accuracy': 0.822}  |
| 0.0001        | 186.0 | 2418 | 1.3187          | {'f1': 0.829754601226994}  | {'accuracy': 0.8224} |
| 0.0001        | 187.0 | 2431 | 1.3279          | {'f1': 0.83015993907083}   | {'accuracy': 0.8216} |
| 0.0001        | 188.0 | 2444 | 1.3209          | {'f1': 0.8294365657339977} | {'accuracy': 0.822}  |
| 0.0001        | 189.0 | 2457 | 1.3296          | {'f1': 0.8148760330578513} | {'accuracy': 0.8208} |
| 0.0001        | 190.0 | 2470 | 1.3729          | {'f1': 0.8358764421287683} | {'accuracy': 0.8236} |
| 0.0001        | 191.0 | 2483 | 1.3415          | {'f1': 0.8309433962264152} | {'accuracy': 0.8208} |
| 0.0001        | 192.0 | 2496 | 1.3709          | {'f1': 0.8090452261306532} | {'accuracy': 0.8176} |
| 0.0023        | 193.0 | 2509 | 1.3308          | {'f1': 0.8313161875945537} | {'accuracy': 0.8216} |
| 0.0023        | 194.0 | 2522 | 1.3586          | {'f1': 0.8300898203592814} | {'accuracy': 0.8184} |
| 0.0023        | 195.0 | 2535 | 1.3053          | {'f1': 0.8317289179822872} | {'accuracy': 0.8252} |
| 0.0023        | 196.0 | 2548 | 1.2996          | {'f1': 0.8333333333333333} | {'accuracy': 0.828}  |
| 0.0023        | 197.0 | 2561 | 1.2937          | {'f1': 0.8280204643841007} | {'accuracy': 0.8252} |
| 0.0023        | 198.0 | 2574 | 1.2966          | {'f1': 0.8264}             | {'accuracy': 0.8264} |
| 0.0023        | 199.0 | 2587 | 1.3215          | {'f1': 0.8180698151950719} | {'accuracy': 0.8228} |
| 0.0023        | 200.0 | 2600 | 1.3029          | {'f1': 0.8233387358184764} | {'accuracy': 0.8256} |
| 0.0023        | 201.0 | 2613 | 1.2937          | {'f1': 0.8262085497403115} | {'accuracy': 0.826}  |
| 0.0023        | 202.0 | 2626 | 1.2919          | {'f1': 0.8265712012728721} | {'accuracy': 0.8256} |
| 0.0023        | 203.0 | 2639 | 1.2917          | {'f1': 0.8267934998018234} | {'accuracy': 0.8252} |
| 0.0023        | 204.0 | 2652 | 1.4967          | {'f1': 0.8278074866310161} | {'accuracy': 0.8068} |
| 0.0023        | 205.0 | 2665 | 1.3007          | {'f1': 0.8278688524590164} | {'accuracy': 0.832}  |
| 0.0023        | 206.0 | 2678 | 1.3728          | {'f1': 0.8125530110262935} | {'accuracy': 0.8232} |
| 0.0023        | 207.0 | 2691 | 1.4707          | {'f1': 0.8339906776622446} | {'accuracy': 0.8148} |
| 0.0023        | 208.0 | 2704 | 1.2701          | {'f1': 0.8403883495145631} | {'accuracy': 0.8356} |
| 0.0023        | 209.0 | 2717 | 1.2717          | {'f1': 0.8389129578574241} | {'accuracy': 0.8364} |
| 0.0023        | 210.0 | 2730 | 1.3918          | {'f1': 0.8415660446395903} | {'accuracy': 0.8268} |
| 0.0023        | 211.0 | 2743 | 1.3395          | {'f1': 0.8439821693907876} | {'accuracy': 0.832}  |
| 0.0023        | 212.0 | 2756 | 1.2888          | {'f1': 0.8312958435207823} | {'accuracy': 0.8344} |
| 0.0023        | 213.0 | 2769 | 1.3092          | {'f1': 0.8277571251548947} | {'accuracy': 0.8332} |
| 0.0023        | 214.0 | 2782 | 1.2824          | {'f1': 0.8316430020283976} | {'accuracy': 0.834}  |
| 0.0023        | 215.0 | 2795 | 1.2763          | {'f1': 0.8331990330378727} | {'accuracy': 0.8344} |
| 0.0023        | 216.0 | 2808 | 1.2747          | {'f1': 0.8347406513872137} | {'accuracy': 0.8356} |
| 0.0023        | 217.0 | 2821 | 1.2736          | {'f1': 0.8350060216780408} | {'accuracy': 0.8356} |
| 0.0023        | 218.0 | 2834 | 1.2728          | {'f1': 0.8364073777064956} | {'accuracy': 0.8368} |
| 0.0023        | 219.0 | 2847 | 1.2727          | {'f1': 0.8368737474949901} | {'accuracy': 0.8372} |
| 0.0023        | 220.0 | 2860 | 1.2721          | {'f1': 0.8374699759807845} | {'accuracy': 0.8376} |
| 0.0023        | 221.0 | 2873 | 1.2705          | {'f1': 0.8377298161470824} | {'accuracy': 0.8376} |
| 0.0023        | 222.0 | 2886 | 1.2672          | {'f1': 0.8392219134577213} | {'accuracy': 0.838}  |
| 0.0023        | 223.0 | 2899 | 1.2669          | {'f1': 0.8399366085578447} | {'accuracy': 0.8384} |
| 0.0023        | 224.0 | 2912 | 1.2671          | {'f1': 0.8399366085578447} | {'accuracy': 0.8384} |
| 0.0023        | 225.0 | 2925 | 1.2675          | {'f1': 0.8402695204122076} | {'accuracy': 0.8388} |
| 0.0023        | 226.0 | 2938 | 1.2674          | {'f1': 0.8399366085578447} | {'accuracy': 0.8384} |
| 0.0023        | 227.0 | 2951 | 1.2678          | {'f1': 0.8402695204122076} | {'accuracy': 0.8388} |
| 0.0023        | 228.0 | 2964 | 1.2684          | {'f1': 0.8402695204122076} | {'accuracy': 0.8388} |
| 0.0023        | 229.0 | 2977 | 1.2686          | {'f1': 0.8402695204122076} | {'accuracy': 0.8388} |
| 0.0023        | 230.0 | 2990 | 1.2702          | {'f1': 0.8382995629717919} | {'accuracy': 0.8372} |
| 0.0006        | 231.0 | 3003 | 1.2737          | {'f1': 0.8377298161470824} | {'accuracy': 0.8376} |
| 0.0006        | 232.0 | 3016 | 1.2754          | {'f1': 0.8362034441329597} | {'accuracy': 0.8364} |
| 0.0006        | 233.0 | 3029 | 1.2757          | {'f1': 0.8357371794871796} | {'accuracy': 0.836}  |
| 0.0006        | 234.0 | 3042 | 1.4517          | {'f1': 0.8036729339746392} | {'accuracy': 0.8204} |
| 0.0006        | 235.0 | 3055 | 1.2382          | {'f1': 0.8369868473495417} | {'accuracy': 0.8364} |
| 0.0006        | 236.0 | 3068 | 1.2389          | {'f1': 0.8454404945904174} | {'accuracy': 0.84}   |
| 0.0006        | 237.0 | 3081 | 1.2386          | {'f1': 0.8464506172839507} | {'accuracy': 0.8408} |
| 0.0006        | 238.0 | 3094 | 1.2367          | {'f1': 0.844100580270793}  | {'accuracy': 0.8388} |
| 0.0006        | 239.0 | 3107 | 1.2364          | {'f1': 0.844100580270793}  | {'accuracy': 0.8388} |
| 0.0006        | 240.0 | 3120 | 1.2361          | {'f1': 0.8447541618273327} | {'accuracy': 0.8396} |
| 0.0006        | 241.0 | 3133 | 1.2362          | {'f1': 0.8447541618273327} | {'accuracy': 0.8396} |
| 0.0006        | 242.0 | 3146 | 1.2354          | {'f1': 0.844633862843859}  | {'accuracy': 0.8396} |
| 0.0006        | 243.0 | 3159 | 1.2342          | {'f1': 0.843289371605896}  | {'accuracy': 0.8384} |
| 0.0006        | 244.0 | 3172 | 1.2329          | {'f1': 0.8450155763239875} | {'accuracy': 0.8408} |
| 0.0006        | 245.0 | 3185 | 1.2312          | {'f1': 0.8428515163450178} | {'accuracy': 0.8404} |
| 0.0006        | 246.0 | 3198 | 1.2323          | {'f1': 0.841897233201581}  | {'accuracy': 0.84}   |
| 0.0006        | 247.0 | 3211 | 1.2360          | {'f1': 0.8388380421806606} | {'accuracy': 0.838}  |
| 0.0006        | 248.0 | 3224 | 1.2378          | {'f1': 0.8379131819992035} | {'accuracy': 0.8372} |
| 0.0006        | 249.0 | 3237 | 1.2475          | {'f1': 0.8354838709677419} | {'accuracy': 0.8368} |
| 0.0006        | 250.0 | 3250 | 1.2463          | {'f1': 0.8360128617363344} | {'accuracy': 0.8368} |
| 0.0006        | 251.0 | 3263 | 1.2423          | {'f1': 0.836465413834466}  | {'accuracy': 0.8364} |
| 0.0006        | 252.0 | 3276 | 1.2393          | {'f1': 0.8388380421806606} | {'accuracy': 0.838}  |
| 0.0006        | 253.0 | 3289 | 1.2369          | {'f1': 0.8409001184366365} | {'accuracy': 0.8388} |
| 0.0006        | 254.0 | 3302 | 1.2366          | {'f1': 0.8419392983839181} | {'accuracy': 0.8396} |
| 0.0006        | 255.0 | 3315 | 1.2369          | {'f1': 0.8419392983839181} | {'accuracy': 0.8396} |
| 0.0006        | 256.0 | 3328 | 1.2368          | {'f1': 0.8434303697875689} | {'accuracy': 0.8408} |
| 0.0006        | 257.0 | 3341 | 1.2369          | {'f1': 0.8437990580847723} | {'accuracy': 0.8408} |
| 0.0006        | 258.0 | 3354 | 1.2374          | {'f1': 0.8447058823529412} | {'accuracy': 0.8416} |
| 0.0006        | 259.0 | 3367 | 1.2378          | {'f1': 0.84437475499804}   | {'accuracy': 0.8412} |
| 0.0006        | 260.0 | 3380 | 1.2381          | {'f1': 0.84437475499804}   | {'accuracy': 0.8412} |
| 0.0006        | 261.0 | 3393 | 1.2381          | {'f1': 0.8441303494307029} | {'accuracy': 0.8412} |
| 0.0006        | 262.0 | 3406 | 1.2384          | {'f1': 0.8440078585461689} | {'accuracy': 0.8412} |
| 0.0006        | 263.0 | 3419 | 1.3680          | {'f1': 0.8204690831556503} | {'accuracy': 0.8316} |
| 0.0006        | 264.0 | 3432 | 1.3926          | {'f1': 0.8161859664227292} | {'accuracy': 0.8292} |
| 0.0006        | 265.0 | 3445 | 1.4283          | {'f1': 0.8403908794788273} | {'accuracy': 0.8236} |
| 0.0006        | 266.0 | 3458 | 1.2505          | {'f1': 0.8489764387794515} | {'accuracy': 0.8436} |
| 0.0006        | 267.0 | 3471 | 1.2826          | {'f1': 0.8363192182410425} | {'accuracy': 0.8392} |
| 0.0006        | 268.0 | 3484 | 1.2917          | {'f1': 0.8342202210397054} | {'accuracy': 0.838}  |
| 0.0006        | 269.0 | 3497 | 1.2881          | {'f1': 0.835577315381477}  | {'accuracy': 0.8388} |
| 0.0009        | 270.0 | 3510 | 1.2855          | {'f1': 0.8363192182410425} | {'accuracy': 0.8392} |
| 0.0009        | 271.0 | 3523 | 1.2836          | {'f1': 0.8365853658536585} | {'accuracy': 0.8392} |
| 0.0009        | 272.0 | 3536 | 1.2814          | {'f1': 0.83779399837794}   | {'accuracy': 0.84}   |
| 0.0009        | 273.0 | 3549 | 1.2785          | {'f1': 0.8380566801619432} | {'accuracy': 0.84}   |
| 0.0009        | 274.0 | 3562 | 1.2739          | {'f1': 0.8387096774193549} | {'accuracy': 0.84}   |
| 0.0009        | 275.0 | 3575 | 1.2695          | {'f1': 0.8408360128617364} | {'accuracy': 0.8416} |
| 0.0009        | 276.0 | 3588 | 1.2658          | {'f1': 0.8401278976818545} | {'accuracy': 0.84}   |
| 0.0009        | 277.0 | 3601 | 1.2643          | {'f1': 0.8407185628742515} | {'accuracy': 0.8404} |
| 0.0009        | 278.0 | 3614 | 1.2618          | {'f1': 0.8407643312101911} | {'accuracy': 0.84}   |
| 0.0009        | 279.0 | 3627 | 1.2608          | {'f1': 0.8418124006359301} | {'accuracy': 0.8408} |
| 0.0009        | 280.0 | 3640 | 1.2602          | {'f1': 0.8425228084093613} | {'accuracy': 0.8412} |
| 0.0009        | 281.0 | 3653 | 1.2602          | {'f1': 0.8419801980198021} | {'accuracy': 0.8404} |
| 0.0009        | 282.0 | 3666 | 1.2602          | {'f1': 0.8424386381631037} | {'accuracy': 0.8408} |
| 0.0009        | 283.0 | 3679 | 1.2602          | {'f1': 0.8424386381631037} | {'accuracy': 0.8408} |
| 0.0009        | 284.0 | 3692 | 1.2604          | {'f1': 0.8428967154728927} | {'accuracy': 0.8412} |
| 0.0009        | 285.0 | 3705 | 1.2602          | {'f1': 0.8426877470355731} | {'accuracy': 0.8408} |
| 0.0009        | 286.0 | 3718 | 1.2599          | {'f1': 0.8428120063191155} | {'accuracy': 0.8408} |
| 0.0009        | 287.0 | 3731 | 1.2599          | {'f1': 0.8432688511646269} | {'accuracy': 0.8412} |
| 0.0009        | 288.0 | 3744 | 1.2600          | {'f1': 0.8432688511646269} | {'accuracy': 0.8412} |
| 0.0009        | 289.0 | 3757 | 1.2600          | {'f1': 0.8437253354380425} | {'accuracy': 0.8416} |
| 0.0009        | 290.0 | 3770 | 1.2600          | {'f1': 0.8433925049309664} | {'accuracy': 0.8412} |
| 0.0009        | 291.0 | 3783 | 1.2601          | {'f1': 0.8431836091410561} | {'accuracy': 0.8408} |
| 0.0009        | 292.0 | 3796 | 1.2602          | {'f1': 0.8431836091410561} | {'accuracy': 0.8408} |
| 0.0009        | 293.0 | 3809 | 1.2603          | {'f1': 0.843762298307753}  | {'accuracy': 0.8412} |
| 0.0009        | 294.0 | 3822 | 1.2605          | {'f1': 0.8442171518489379} | {'accuracy': 0.8416} |
| 0.0009        | 295.0 | 3835 | 1.2607          | {'f1': 0.8442171518489379} | {'accuracy': 0.8416} |
| 0.0009        | 296.0 | 3848 | 1.2608          | {'f1': 0.8442171518489379} | {'accuracy': 0.8416} |
| 0.0009        | 297.0 | 3861 | 1.2610          | {'f1': 0.8435534591194969} | {'accuracy': 0.8408} |
| 0.0009        | 298.0 | 3874 | 1.2612          | {'f1': 0.8435534591194969} | {'accuracy': 0.8408} |
| 0.0009        | 299.0 | 3887 | 1.2618          | {'f1': 0.8442171518489379} | {'accuracy': 0.8416} |
| 0.0009        | 300.0 | 3900 | 1.2620          | {'f1': 0.8442171518489379} | {'accuracy': 0.8416} |
| 0.0009        | 301.0 | 3913 | 1.2622          | {'f1': 0.8442171518489379} | {'accuracy': 0.8416} |
| 0.0009        | 302.0 | 3926 | 1.2623          | {'f1': 0.8442171518489379} | {'accuracy': 0.8416} |
| 0.0009        | 303.0 | 3939 | 1.2628          | {'f1': 0.8435159637366968} | {'accuracy': 0.8412} |
| 0.0009        | 304.0 | 3952 | 1.2630          | {'f1': 0.8435159637366968} | {'accuracy': 0.8412} |
| 0.0009        | 305.0 | 3965 | 1.2631          | {'f1': 0.8433070866141733} | {'accuracy': 0.8408} |
| 0.0009        | 306.0 | 3978 | 1.2633          | {'f1': 0.8433070866141733} | {'accuracy': 0.8408} |
| 0.0009        | 307.0 | 3991 | 1.2635          | {'f1': 0.843762298307753}  | {'accuracy': 0.8412} |
| 0.0           | 308.0 | 4004 | 1.2636          | {'f1': 0.8442171518489379} | {'accuracy': 0.8416} |
| 0.0           | 309.0 | 4017 | 1.2638          | {'f1': 0.8442171518489379} | {'accuracy': 0.8416} |
| 0.0           | 310.0 | 4030 | 1.2640          | {'f1': 0.8442171518489379} | {'accuracy': 0.8416} |
| 0.0           | 311.0 | 4043 | 1.2641          | {'f1': 0.843885174990169}  | {'accuracy': 0.8412} |
| 0.0           | 312.0 | 4056 | 1.2644          | {'f1': 0.843885174990169}  | {'accuracy': 0.8412} |
| 0.0           | 313.0 | 4069 | 1.2645          | {'f1': 0.8444619010212097} | {'accuracy': 0.8416} |
| 0.0           | 314.0 | 4082 | 1.2647          | {'f1': 0.8444619010212097} | {'accuracy': 0.8416} |
| 0.0           | 315.0 | 4095 | 1.2648          | {'f1': 0.8444619010212097} | {'accuracy': 0.8416} |
| 0.0           | 316.0 | 4108 | 1.2650          | {'f1': 0.8444619010212097} | {'accuracy': 0.8416} |
| 0.0           | 317.0 | 4121 | 1.2681          | {'f1': 0.8475750577367206} | {'accuracy': 0.8416} |
| 0.0           | 318.0 | 4134 | 1.2693          | {'f1': 0.846923076923077}  | {'accuracy': 0.8408} |
| 0.0           | 319.0 | 4147 | 1.2684          | {'f1': 0.847248941900731}  | {'accuracy': 0.8412} |
| 0.0           | 320.0 | 4160 | 1.2681          | {'f1': 0.8479014247208319} | {'accuracy': 0.842}  |
| 0.0           | 321.0 | 4173 | 1.2680          | {'f1': 0.8488820354664611} | {'accuracy': 0.8432} |
| 0.0           | 322.0 | 4186 | 1.2681          | {'f1': 0.8488820354664611} | {'accuracy': 0.8432} |
| 0.0           | 323.0 | 4199 | 1.2683          | {'f1': 0.8488820354664611} | {'accuracy': 0.8432} |
| 0.0           | 324.0 | 4212 | 1.2683          | {'f1': 0.8487654320987655} | {'accuracy': 0.8432} |
| 0.0           | 325.0 | 4225 | 1.2687          | {'f1': 0.8488820354664611} | {'accuracy': 0.8432} |
| 0.0           | 326.0 | 4238 | 1.2673          | {'f1': 0.8491879350348028} | {'accuracy': 0.844}  |
| 0.0           | 327.0 | 4251 | 1.2669          | {'f1': 0.8490712074303406} | {'accuracy': 0.844}  |
| 0.0           | 328.0 | 4264 | 1.2668          | {'f1': 0.848625629113434}  | {'accuracy': 0.8436} |
| 0.0           | 329.0 | 4277 | 1.2669          | {'f1': 0.848625629113434}  | {'accuracy': 0.8436} |
| 0.0           | 330.0 | 4290 | 1.2669          | {'f1': 0.8482731858750485} | {'accuracy': 0.8436} |
| 0.0           | 331.0 | 4303 | 1.2670          | {'f1': 0.8478260869565218} | {'accuracy': 0.8432} |
| 0.0           | 332.0 | 4316 | 1.2672          | {'f1': 0.8481553398058252} | {'accuracy': 0.8436} |
| 0.0           | 333.0 | 4329 | 1.2672          | {'f1': 0.8471411901983664} | {'accuracy': 0.8428} |
| 0.0           | 334.0 | 4342 | 1.2672          | {'f1': 0.8464536243180047} | {'accuracy': 0.8424} |
| 0.0           | 335.0 | 4355 | 1.2674          | {'f1': 0.8463338533541341} | {'accuracy': 0.8424} |
| 0.0           | 336.0 | 4368 | 1.2676          | {'f1': 0.8466640655481857} | {'accuracy': 0.8428} |
| 0.0           | 337.0 | 4381 | 1.2681          | {'f1': 0.8470221876216425} | {'accuracy': 0.8428} |
| 0.0           | 338.0 | 4394 | 1.2685          | {'f1': 0.8470221876216425} | {'accuracy': 0.8428} |
| 0.0           | 339.0 | 4407 | 1.2688          | {'f1': 0.8475894245723173} | {'accuracy': 0.8432} |
| 0.0           | 340.0 | 4420 | 1.2693          | {'f1': 0.8490492821109816} | {'accuracy': 0.8444} |
| 0.0           | 341.0 | 4433 | 1.2698          | {'f1': 0.8491663435440093} | {'accuracy': 0.8444} |
| 0.0           | 342.0 | 4446 | 1.2699          | {'f1': 0.8491663435440093} | {'accuracy': 0.8444} |
| 0.0           | 343.0 | 4459 | 1.2698          | {'f1': 0.8484848484848486} | {'accuracy': 0.844}  |
| 0.0           | 344.0 | 4472 | 1.2700          | {'f1': 0.8484848484848486} | {'accuracy': 0.844}  |
| 0.0           | 345.0 | 4485 | 1.2702          | {'f1': 0.8484848484848486} | {'accuracy': 0.844}  |
| 0.0           | 346.0 | 4498 | 1.2704          | {'f1': 0.8484848484848486} | {'accuracy': 0.844}  |
| 0.0           | 347.0 | 4511 | 1.2707          | {'f1': 0.8484848484848486} | {'accuracy': 0.844}  |
| 0.0           | 348.0 | 4524 | 1.2708          | {'f1': 0.8484848484848486} | {'accuracy': 0.844}  |
| 0.0           | 349.0 | 4537 | 1.2710          | {'f1': 0.8484848484848486} | {'accuracy': 0.844}  |
| 0.0           | 350.0 | 4550 | 1.2713          | {'f1': 0.8489320388349514} | {'accuracy': 0.8444} |
| 0.0           | 351.0 | 4563 | 1.2715          | {'f1': 0.8486024844720497} | {'accuracy': 0.844}  |
| 0.0           | 352.0 | 4576 | 1.2718          | {'f1': 0.8490492821109816} | {'accuracy': 0.8444} |
| 0.0           | 353.0 | 4589 | 1.2720          | {'f1': 0.8487199379363848} | {'accuracy': 0.844}  |
| 0.0           | 354.0 | 4602 | 1.2721          | {'f1': 0.8487199379363848} | {'accuracy': 0.844}  |
| 0.0           | 355.0 | 4615 | 1.2722          | {'f1': 0.8486024844720497} | {'accuracy': 0.844}  |
| 0.0           | 356.0 | 4628 | 1.2724          | {'f1': 0.8486024844720497} | {'accuracy': 0.844}  |
| 0.0           | 357.0 | 4641 | 1.2726          | {'f1': 0.8486024844720497} | {'accuracy': 0.844}  |
| 0.0           | 358.0 | 4654 | 1.2727          | {'f1': 0.8489320388349514} | {'accuracy': 0.8444} |
| 0.0           | 359.0 | 4667 | 1.2729          | {'f1': 0.8486024844720497} | {'accuracy': 0.844}  |
| 0.0           | 360.0 | 4680 | 1.2731          | {'f1': 0.8489320388349514} | {'accuracy': 0.8444} |
| 0.0           | 361.0 | 4693 | 1.2732          | {'f1': 0.8483670295489891} | {'accuracy': 0.844}  |
| 0.0           | 362.0 | 4706 | 1.2734          | {'f1': 0.8460038986354775} | {'accuracy': 0.842}  |
| 0.0           | 363.0 | 4719 | 1.2736          | {'f1': 0.8463338533541341} | {'accuracy': 0.8424} |
| 0.0           | 364.0 | 4732 | 1.2736          | {'f1': 0.8456428292301681} | {'accuracy': 0.842}  |
| 0.0           | 365.0 | 4745 | 1.2737          | {'f1': 0.84609375}         | {'accuracy': 0.8424} |
| 0.0           | 366.0 | 4758 | 1.2739          | {'f1': 0.8463338533541341} | {'accuracy': 0.8424} |
| 0.0           | 367.0 | 4771 | 1.2741          | {'f1': 0.8460038986354775} | {'accuracy': 0.842}  |
| 0.0           | 368.0 | 4784 | 1.2743          | {'f1': 0.8460038986354775} | {'accuracy': 0.842}  |
| 0.0           | 369.0 | 4797 | 1.2756          | {'f1': 0.8449155869650569} | {'accuracy': 0.842}  |
| 0.0           | 370.0 | 4810 | 1.2766          | {'f1': 0.8435159637366968} | {'accuracy': 0.8412} |
| 0.0           | 371.0 | 4823 | 1.2770          | {'f1': 0.8435159637366968} | {'accuracy': 0.8412} |
| 0.0           | 372.0 | 4836 | 1.2770          | {'f1': 0.8435159637366968} | {'accuracy': 0.8412} |
| 0.0           | 373.0 | 4849 | 1.2775          | {'f1': 0.8433925049309664} | {'accuracy': 0.8412} |
| 0.0           | 374.0 | 4862 | 1.2778          | {'f1': 0.8433925049309664} | {'accuracy': 0.8412} |
| 0.0           | 375.0 | 4875 | 1.2798          | {'f1': 0.8434782608695652} | {'accuracy': 0.8416} |
| 0.0           | 376.0 | 4888 | 1.2812          | {'f1': 0.8440221694378464} | {'accuracy': 0.8424} |
| 0.0           | 377.0 | 4901 | 1.2813          | {'f1': 0.8440221694378464} | {'accuracy': 0.8424} |
| 0.0           | 378.0 | 4914 | 1.2812          | {'f1': 0.844145569620253}  | {'accuracy': 0.8424} |
| 0.0           | 379.0 | 4927 | 1.2811          | {'f1': 0.8428120063191155} | {'accuracy': 0.8408} |
| 0.0           | 380.0 | 4940 | 1.2811          | {'f1': 0.8428120063191155} | {'accuracy': 0.8408} |
| 0.0           | 381.0 | 4953 | 1.2811          | {'f1': 0.8428120063191155} | {'accuracy': 0.8408} |
| 0.0           | 382.0 | 4966 | 1.2811          | {'f1': 0.8428120063191155} | {'accuracy': 0.8408} |
| 0.0           | 383.0 | 4979 | 1.2810          | {'f1': 0.8433925049309664} | {'accuracy': 0.8412} |
| 0.0           | 384.0 | 4992 | 1.2813          | {'f1': 0.8429360694554064} | {'accuracy': 0.8408} |
| 0.0           | 385.0 | 5005 | 1.2817          | {'f1': 0.8429360694554064} | {'accuracy': 0.8408} |
| 0.0           | 386.0 | 5018 | 1.2819          | {'f1': 0.8429360694554064} | {'accuracy': 0.8408} |
| 0.0           | 387.0 | 5031 | 1.2818          | {'f1': 0.8433925049309664} | {'accuracy': 0.8412} |
| 0.0           | 388.0 | 5044 | 1.2817          | {'f1': 0.8438485804416405} | {'accuracy': 0.8416} |
| 0.0           | 389.0 | 5057 | 1.2817          | {'f1': 0.8431836091410561} | {'accuracy': 0.8408} |
| 0.0           | 390.0 | 5070 | 1.2821          | {'f1': 0.8435159637366968} | {'accuracy': 0.8412} |
| 0.0           | 391.0 | 5083 | 1.2836          | {'f1': 0.8428120063191155} | {'accuracy': 0.8408} |
| 0.0           | 392.0 | 5096 | 1.2841          | {'f1': 0.8428120063191155} | {'accuracy': 0.8408} |
| 0.0           | 393.0 | 5109 | 1.2845          | {'f1': 0.8428120063191155} | {'accuracy': 0.8408} |
| 0.0           | 394.0 | 5122 | 1.2845          | {'f1': 0.8429360694554064} | {'accuracy': 0.8408} |
| 0.0           | 395.0 | 5135 | 1.2844          | {'f1': 0.8433925049309664} | {'accuracy': 0.8412} |
| 0.0           | 396.0 | 5148 | 1.3032          | {'f1': 0.8459490300494484} | {'accuracy': 0.838}  |
| 0.0           | 397.0 | 5161 | 1.3234          | {'f1': 0.8466165413533835} | {'accuracy': 0.8368} |
| 0.0           | 398.0 | 5174 | 1.3252          | {'f1': 0.8468468468468469} | {'accuracy': 0.8368} |
| 0.0           | 399.0 | 5187 | 1.3222          | {'f1': 0.8461827754795036} | {'accuracy': 0.8364} |
| 0.0           | 400.0 | 5200 | 1.3187          | {'f1': 0.8455162019593068} | {'accuracy': 0.836}  |
| 0.0           | 401.0 | 5213 | 1.3160          | {'f1': 0.8457185967559412} | {'accuracy': 0.8364} |
| 0.0           | 402.0 | 5226 | 1.3146          | {'f1': 0.8457185967559412} | {'accuracy': 0.8364} |
| 0.0           | 403.0 | 5239 | 1.3028          | {'f1': 0.8475864690231851} | {'accuracy': 0.8396} |
| 0.0           | 404.0 | 5252 | 1.2936          | {'f1': 0.8491577335375191} | {'accuracy': 0.8424} |
| 0.0           | 405.0 | 5265 | 1.2915          | {'f1': 0.8481595092024541} | {'accuracy': 0.8416} |
| 0.0           | 406.0 | 5278 | 1.2910          | {'f1': 0.847717683160721}  | {'accuracy': 0.8412} |
| 0.0           | 407.0 | 5291 | 1.2908          | {'f1': 0.8483685220729367} | {'accuracy': 0.842}  |
| 0.0           | 408.0 | 5304 | 1.2907          | {'f1': 0.8483685220729367} | {'accuracy': 0.842}  |
| 0.0           | 409.0 | 5317 | 1.2902          | {'f1': 0.847926267281106}  | {'accuracy': 0.8416} |
| 0.0           | 410.0 | 5330 | 1.2896          | {'f1': 0.8482520169035727} | {'accuracy': 0.842}  |
| 0.0           | 411.0 | 5343 | 1.2869          | {'f1': 0.8491147036181678} | {'accuracy': 0.8432} |
| 0.0           | 412.0 | 5356 | 1.2865          | {'f1': 0.8494416634578358} | {'accuracy': 0.8436} |
| 0.0           | 413.0 | 5369 | 1.2867          | {'f1': 0.8494416634578358} | {'accuracy': 0.8436} |
| 0.0           | 414.0 | 5382 | 1.2867          | {'f1': 0.8494416634578358} | {'accuracy': 0.8436} |
| 0.0           | 415.0 | 5395 | 1.2865          | {'f1': 0.8494416634578358} | {'accuracy': 0.8436} |
| 0.0           | 416.0 | 5408 | 1.2864          | {'f1': 0.8497688751926041} | {'accuracy': 0.844}  |
| 0.0           | 417.0 | 5421 | 1.2865          | {'f1': 0.8497688751926041} | {'accuracy': 0.844}  |
| 0.0           | 418.0 | 5434 | 1.2855          | {'f1': 0.8486486486486486} | {'accuracy': 0.8432} |
| 0.0           | 419.0 | 5447 | 1.2854          | {'f1': 0.8477588871715611} | {'accuracy': 0.8424} |
| 0.0           | 420.0 | 5460 | 1.2855          | {'f1': 0.8477588871715611} | {'accuracy': 0.8424} |
| 0.0           | 421.0 | 5473 | 1.2856          | {'f1': 0.8477588871715611} | {'accuracy': 0.8424} |
| 0.0           | 422.0 | 5486 | 1.2855          | {'f1': 0.8480865867800541} | {'accuracy': 0.8428} |
| 0.0           | 423.0 | 5499 | 1.2854          | {'f1': 0.8480865867800541} | {'accuracy': 0.8428} |
| 0.0           | 424.0 | 5512 | 1.2855          | {'f1': 0.8480865867800541} | {'accuracy': 0.8428} |
| 0.0           | 425.0 | 5525 | 1.2853          | {'f1': 0.8497288923315259} | {'accuracy': 0.8448} |
| 0.0           | 426.0 | 5538 | 1.2848          | {'f1': 0.8488146132918772} | {'accuracy': 0.8444} |
| 0.0           | 427.0 | 5551 | 1.2856          | {'f1': 0.849283223556761}  | {'accuracy': 0.8444} |
| 0.0           | 428.0 | 5564 | 1.2870          | {'f1': 0.8477588871715611} | {'accuracy': 0.8424} |
| 0.0           | 429.0 | 5577 | 1.2878          | {'f1': 0.8482039397450754} | {'accuracy': 0.8428} |
| 0.0           | 430.0 | 5590 | 1.2882          | {'f1': 0.8487654320987655} | {'accuracy': 0.8432} |
| 0.0           | 431.0 | 5603 | 1.2882          | {'f1': 0.8483211115399459} | {'accuracy': 0.8428} |
| 0.0           | 432.0 | 5616 | 1.2883          | {'f1': 0.8478764478764478} | {'accuracy': 0.8424} |
| 0.0           | 433.0 | 5629 | 1.2884          | {'f1': 0.8483211115399459} | {'accuracy': 0.8428} |
| 0.0           | 434.0 | 5642 | 1.2885          | {'f1': 0.8482039397450754} | {'accuracy': 0.8428} |
| 0.0           | 435.0 | 5655 | 1.2884          | {'f1': 0.8482039397450754} | {'accuracy': 0.8428} |
| 0.0           | 436.0 | 5668 | 1.2882          | {'f1': 0.8477588871715611} | {'accuracy': 0.8424} |
| 0.0           | 437.0 | 5681 | 1.2883          | {'f1': 0.8477588871715611} | {'accuracy': 0.8424} |
| 0.0           | 438.0 | 5694 | 1.2882          | {'f1': 0.8477588871715611} | {'accuracy': 0.8424} |
| 0.0           | 439.0 | 5707 | 1.2883          | {'f1': 0.8480865867800541} | {'accuracy': 0.8428} |
| 0.0           | 440.0 | 5720 | 1.2882          | {'f1': 0.848414539829853}  | {'accuracy': 0.8432} |
| 0.0           | 441.0 | 5733 | 1.2882          | {'f1': 0.8490712074303406} | {'accuracy': 0.844}  |
| 0.0           | 442.0 | 5746 | 1.2883          | {'f1': 0.8490712074303406} | {'accuracy': 0.844}  |
| 0.0           | 443.0 | 5759 | 1.2884          | {'f1': 0.8490712074303406} | {'accuracy': 0.844}  |
| 0.0           | 444.0 | 5772 | 1.2885          | {'f1': 0.8490712074303406} | {'accuracy': 0.844}  |
| 0.0           | 445.0 | 5785 | 1.2886          | {'f1': 0.8490712074303406} | {'accuracy': 0.844}  |
| 0.0           | 446.0 | 5798 | 1.2888          | {'f1': 0.8490712074303406} | {'accuracy': 0.844}  |
| 0.0           | 447.0 | 5811 | 1.2890          | {'f1': 0.8490712074303406} | {'accuracy': 0.844}  |
| 0.0           | 448.0 | 5824 | 1.2891          | {'f1': 0.8487427466150871} | {'accuracy': 0.8436} |
| 0.0           | 449.0 | 5837 | 1.2893          | {'f1': 0.848414539829853}  | {'accuracy': 0.8432} |
| 0.0           | 450.0 | 5850 | 1.2894          | {'f1': 0.848414539829853}  | {'accuracy': 0.8432} |
| 0.0           | 451.0 | 5863 | 1.2895          | {'f1': 0.848414539829853}  | {'accuracy': 0.8432} |
| 0.0           | 452.0 | 5876 | 1.2895          | {'f1': 0.8490712074303406} | {'accuracy': 0.844}  |
| 0.0           | 453.0 | 5889 | 1.2895          | {'f1': 0.8490712074303406} | {'accuracy': 0.844}  |
| 0.0           | 454.0 | 5902 | 1.2896          | {'f1': 0.8490712074303406} | {'accuracy': 0.844}  |
| 0.0           | 455.0 | 5915 | 1.2897          | {'f1': 0.8490712074303406} | {'accuracy': 0.844}  |
| 0.0           | 456.0 | 5928 | 1.2898          | {'f1': 0.8490712074303406} | {'accuracy': 0.844}  |
| 0.0           | 457.0 | 5941 | 1.2897          | {'f1': 0.8490712074303406} | {'accuracy': 0.844}  |
| 0.0           | 458.0 | 5954 | 1.2894          | {'f1': 0.849283223556761}  | {'accuracy': 0.8444} |
| 0.0           | 459.0 | 5967 | 1.2893          | {'f1': 0.8491663435440093} | {'accuracy': 0.8444} |
| 0.0           | 460.0 | 5980 | 1.2893          | {'f1': 0.8491663435440093} | {'accuracy': 0.8444} |
| 0.0           | 461.0 | 5993 | 1.2894          | {'f1': 0.8491663435440093} | {'accuracy': 0.8444} |
| 0.0           | 462.0 | 6006 | 1.2895          | {'f1': 0.8491663435440093} | {'accuracy': 0.8444} |
| 0.0           | 463.0 | 6019 | 1.2896          | {'f1': 0.8491663435440093} | {'accuracy': 0.8444} |
| 0.0           | 464.0 | 6032 | 1.2897          | {'f1': 0.8491663435440093} | {'accuracy': 0.8444} |
| 0.0           | 465.0 | 6045 | 1.2898          | {'f1': 0.8491663435440093} | {'accuracy': 0.8444} |
| 0.0           | 466.0 | 6058 | 1.2899          | {'f1': 0.8487199379363848} | {'accuracy': 0.844}  |
| 0.0           | 467.0 | 6071 | 1.2899          | {'f1': 0.8487199379363848} | {'accuracy': 0.844}  |
| 0.0           | 468.0 | 6084 | 1.2900          | {'f1': 0.8487199379363848} | {'accuracy': 0.844}  |
| 0.0           | 469.0 | 6097 | 1.2901          | {'f1': 0.8487199379363848} | {'accuracy': 0.844}  |
| 0.0           | 470.0 | 6110 | 1.2903          | {'f1': 0.8491663435440093} | {'accuracy': 0.8444} |
| 0.0           | 471.0 | 6123 | 1.2905          | {'f1': 0.8496124031007752} | {'accuracy': 0.8448} |
| 0.0           | 472.0 | 6136 | 1.2906          | {'f1': 0.8496124031007752} | {'accuracy': 0.8448} |
| 0.0           | 473.0 | 6149 | 1.2908          | {'f1': 0.8496124031007752} | {'accuracy': 0.8448} |
| 0.0           | 474.0 | 6162 | 1.2909          | {'f1': 0.8493999225706542} | {'accuracy': 0.8444} |
| 0.0           | 475.0 | 6175 | 1.2910          | {'f1': 0.8493999225706542} | {'accuracy': 0.8444} |
| 0.0           | 476.0 | 6188 | 1.2911          | {'f1': 0.8493999225706542} | {'accuracy': 0.8444} |
| 0.0           | 477.0 | 6201 | 1.2912          | {'f1': 0.8493999225706542} | {'accuracy': 0.8444} |
| 0.0           | 478.0 | 6214 | 1.2907          | {'f1': 0.8496124031007752} | {'accuracy': 0.8448} |
| 0.0           | 479.0 | 6227 | 1.2906          | {'f1': 0.8491663435440093} | {'accuracy': 0.8444} |
| 0.0           | 480.0 | 6240 | 1.2906          | {'f1': 0.8491663435440093} | {'accuracy': 0.8444} |
| 0.0           | 481.0 | 6253 | 1.2906          | {'f1': 0.8487199379363848} | {'accuracy': 0.844}  |
| 0.0           | 482.0 | 6266 | 1.2906          | {'f1': 0.8487199379363848} | {'accuracy': 0.844}  |
| 0.0           | 483.0 | 6279 | 1.2907          | {'f1': 0.8487199379363848} | {'accuracy': 0.844}  |
| 0.0           | 484.0 | 6292 | 1.2907          | {'f1': 0.8487199379363848} | {'accuracy': 0.844}  |
| 0.0           | 485.0 | 6305 | 1.2908          | {'f1': 0.8487199379363848} | {'accuracy': 0.844}  |
| 0.0           | 486.0 | 6318 | 1.2908          | {'f1': 0.8491663435440093} | {'accuracy': 0.8444} |
| 0.0           | 487.0 | 6331 | 1.2891          | {'f1': 0.8472059398202424} | {'accuracy': 0.8436} |
| 0.0           | 488.0 | 6344 | 1.2894          | {'f1': 0.8464860620337652} | {'accuracy': 0.8436} |
| 0.0           | 489.0 | 6357 | 1.2898          | {'f1': 0.8459119496855346} | {'accuracy': 0.8432} |
| 0.0           | 490.0 | 6370 | 1.2899          | {'f1': 0.8454581203303184} | {'accuracy': 0.8428} |
| 0.0           | 491.0 | 6383 | 1.2899          | {'f1': 0.8454581203303184} | {'accuracy': 0.8428} |
| 0.0           | 492.0 | 6396 | 1.2900          | {'f1': 0.8454581203303184} | {'accuracy': 0.8428} |
| 0.0           | 493.0 | 6409 | 1.2900          | {'f1': 0.8454581203303184} | {'accuracy': 0.8428} |
| 0.0           | 494.0 | 6422 | 1.2900          | {'f1': 0.8454581203303184} | {'accuracy': 0.8428} |
| 0.0           | 495.0 | 6435 | 1.2900          | {'f1': 0.8454581203303184} | {'accuracy': 0.8428} |
| 0.0           | 496.0 | 6448 | 1.2900          | {'f1': 0.8454581203303184} | {'accuracy': 0.8428} |
| 0.0           | 497.0 | 6461 | 1.2900          | {'f1': 0.8454581203303184} | {'accuracy': 0.8428} |
| 0.0           | 498.0 | 6474 | 1.2900          | {'f1': 0.8454581203303184} | {'accuracy': 0.8428} |
| 0.0           | 499.0 | 6487 | 1.2900          | {'f1': 0.8454581203303184} | {'accuracy': 0.8428} |
| 0.0           | 500.0 | 6500 | 1.2900          | {'f1': 0.8454581203303184} | {'accuracy': 0.8428} |


### Framework versions

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