pytorch generated_from_trainer license:apache-2.0 region:us
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: bert-base-uncased-test_16_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_16_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: 1.4523
- F1: {'f1': 0.8282041293338528}
- Accuracy: {'accuracy': 0.8236}

## 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   | 0.6924          | {'f1': 0.34501642935377874} | {'accuracy': 0.5216} |
| No log        | 2.0   | 26   | 0.6882          | {'f1': 0.46713947990543736} | {'accuracy': 0.5492} |
| No log        | 3.0   | 39   | 0.6838          | {'f1': 0.5512547851977881}  | {'accuracy': 0.578}  |
| No log        | 4.0   | 52   | 0.6769          | {'f1': 0.42633567188343224} | {'accuracy': 0.5748} |
| No log        | 5.0   | 65   | 0.6556          | {'f1': 0.5819964349376114}  | {'accuracy': 0.6248} |
| No log        | 6.0   | 78   | 0.6259          | {'f1': 0.6498553121124432}  | {'accuracy': 0.6612} |
| No log        | 7.0   | 91   | 0.5996          | {'f1': 0.6816693944353519}  | {'accuracy': 0.6888} |
| No log        | 8.0   | 104  | 0.5652          | {'f1': 0.7300184162062615}  | {'accuracy': 0.7068} |
| No log        | 9.0   | 117  | 0.5545          | {'f1': 0.7577464788732394}  | {'accuracy': 0.7248} |
| No log        | 10.0  | 130  | 0.5519          | {'f1': 0.7614510809820447}  | {'accuracy': 0.7396} |
| No log        | 11.0  | 143  | 0.5610          | {'f1': 0.7769886363636364}  | {'accuracy': 0.7488} |
| No log        | 12.0  | 156  | 0.5165          | {'f1': 0.7841921735761334}  | {'accuracy': 0.7772} |
| No log        | 13.0  | 169  | 0.5503          | {'f1': 0.7601539119281746}  | {'accuracy': 0.7756} |
| No log        | 14.0  | 182  | 0.5292          | {'f1': 0.7821740941274469}  | {'accuracy': 0.7908} |
| No log        | 15.0  | 195  | 0.5220          | {'f1': 0.8040238450074516}  | {'accuracy': 0.7896} |
| No log        | 16.0  | 208  | 0.5622          | {'f1': 0.8059701492537312}  | {'accuracy': 0.8024} |
| No log        | 17.0  | 221  | 0.5942          | {'f1': 0.8030182684670374}  | {'accuracy': 0.8016} |
| No log        | 18.0  | 234  | 0.6197          | {'f1': 0.8131952435749904}  | {'accuracy': 0.8052} |
| No log        | 19.0  | 247  | 0.6677          | {'f1': 0.8140060240963856}  | {'accuracy': 0.8024} |
| No log        | 20.0  | 260  | 0.7322          | {'f1': 0.7898305084745764}  | {'accuracy': 0.8016} |
| No log        | 21.0  | 273  | 0.7278          | {'f1': 0.8039457459926018}  | {'accuracy': 0.8092} |
| No log        | 22.0  | 286  | 0.7253          | {'f1': 0.8110419906687402}  | {'accuracy': 0.8056} |
| No log        | 23.0  | 299  | 0.7409          | {'f1': 0.8124507486209613}  | {'accuracy': 0.8096} |
| No log        | 24.0  | 312  | 0.7735          | {'f1': 0.8232169954476479}  | {'accuracy': 0.8136} |
| No log        | 25.0  | 325  | 0.7893          | {'f1': 0.8152969894222944}  | {'accuracy': 0.8184} |
| No log        | 26.0  | 338  | 0.8000          | {'f1': 0.817246835443038}   | {'accuracy': 0.8152} |
| No log        | 27.0  | 351  | 0.8183          | {'f1': 0.8175009854158455}  | {'accuracy': 0.8148} |
| No log        | 28.0  | 364  | 0.8288          | {'f1': 0.8190776507686244}  | {'accuracy': 0.8164} |
| No log        | 29.0  | 377  | 0.8793          | {'f1': 0.8233124308373294}  | {'accuracy': 0.8084} |
| No log        | 30.0  | 390  | 0.8778          | {'f1': 0.8087206910736323}  | {'accuracy': 0.814}  |
| No log        | 31.0  | 403  | 0.8484          | {'f1': 0.824655436447167}   | {'accuracy': 0.8168} |
| No log        | 32.0  | 416  | 0.8732          | {'f1': 0.82834406972338}    | {'accuracy': 0.8188} |
| No log        | 33.0  | 429  | 0.8856          | {'f1': 0.8159362549800797}  | {'accuracy': 0.8152} |
| No log        | 34.0  | 442  | 0.9012          | {'f1': 0.8258859784283513}  | {'accuracy': 0.8192} |
| No log        | 35.0  | 455  | 0.9184          | {'f1': 0.8156645569620253}  | {'accuracy': 0.8136} |
| No log        | 36.0  | 468  | 0.9545          | {'f1': 0.823352165725047}   | {'accuracy': 0.8124} |
| No log        | 37.0  | 481  | 0.9520          | {'f1': 0.8212074303405573}  | {'accuracy': 0.8152} |
| No log        | 38.0  | 494  | 0.9724          | {'f1': 0.81181707810603}    | {'accuracy': 0.814}  |
| 0.1904        | 39.0  | 507  | 0.9668          | {'f1': 0.8222648752399232}  | {'accuracy': 0.8148} |
| 0.1904        | 40.0  | 520  | 0.9684          | {'f1': 0.8177813376051262}  | {'accuracy': 0.818}  |
| 0.1904        | 41.0  | 533  | 0.9888          | {'f1': 0.8287878787878789}  | {'accuracy': 0.8192} |
| 0.1904        | 42.0  | 546  | 1.0402          | {'f1': 0.8071636817992504}  | {'accuracy': 0.8148} |
| 0.1904        | 43.0  | 559  | 1.0224          | {'f1': 0.818640776699029}   | {'accuracy': 0.8132} |
| 0.1904        | 44.0  | 572  | 1.0390          | {'f1': 0.817864077669903}   | {'accuracy': 0.8124} |
| 0.1904        | 45.0  | 585  | 1.1882          | {'f1': 0.7851851851851853}  | {'accuracy': 0.8028} |
| 0.1904        | 46.0  | 598  | 1.0246          | {'f1': 0.8259860788863109}  | {'accuracy': 0.82}   |
| 0.1904        | 47.0  | 611  | 1.0492          | {'f1': 0.8100535640708695}  | {'accuracy': 0.8156} |
| 0.1904        | 48.0  | 624  | 1.0127          | {'f1': 0.8293448411141624}  | {'accuracy': 0.826}  |
| 0.1904        | 49.0  | 637  | 1.1182          | {'f1': 0.8010247651579845}  | {'accuracy': 0.8136} |
| 0.1904        | 50.0  | 650  | 1.0229          | {'f1': 0.8275049115913556}  | {'accuracy': 0.8244} |
| 0.1904        | 51.0  | 663  | 1.0610          | {'f1': 0.8301026225769669}  | {'accuracy': 0.8212} |
| 0.1904        | 52.0  | 676  | 1.0652          | {'f1': 0.8152350081037277}  | {'accuracy': 0.8176} |
| 0.1904        | 53.0  | 689  | 1.0522          | {'f1': 0.825545171339564}   | {'accuracy': 0.8208} |
| 0.1904        | 54.0  | 702  | 1.0731          | {'f1': 0.8177813376051262}  | {'accuracy': 0.818}  |
| 0.1904        | 55.0  | 715  | 1.0828          | {'f1': 0.8180379746835443}  | {'accuracy': 0.816}  |
| 0.1904        | 56.0  | 728  | 1.0955          | {'f1': 0.8228483211115398}  | {'accuracy': 0.8164} |
| 0.1904        | 57.0  | 741  | 1.1408          | {'f1': 0.8041666666666666}  | {'accuracy': 0.812}  |
| 0.1904        | 58.0  | 754  | 1.1443          | {'f1': 0.8273062730627306}  | {'accuracy': 0.8128} |
| 0.1904        | 59.0  | 767  | 1.1490          | {'f1': 0.8041407867494824}  | {'accuracy': 0.8108} |
| 0.1904        | 60.0  | 780  | 1.1251          | {'f1': 0.8243700639338096}  | {'accuracy': 0.8132} |
| 0.1904        | 61.0  | 793  | 1.1560          | {'f1': 0.8067993366500829}  | {'accuracy': 0.8136} |
| 0.1904        | 62.0  | 806  | 1.1154          | {'f1': 0.8140544808527438}  | {'accuracy': 0.8116} |
| 0.1904        | 63.0  | 819  | 1.1284          | {'f1': 0.8237547892720306}  | {'accuracy': 0.816}  |
| 0.1904        | 64.0  | 832  | 1.1035          | {'f1': 0.8199052132701422}  | {'accuracy': 0.8176} |
| 0.1904        | 65.0  | 845  | 1.1498          | {'f1': 0.8122162608336772}  | {'accuracy': 0.818}  |
| 0.1904        | 66.0  | 858  | 1.1032          | {'f1': 0.824313725490196}   | {'accuracy': 0.8208} |
| 0.1904        | 67.0  | 871  | 1.1103          | {'f1': 0.8270270270270269}  | {'accuracy': 0.8208} |
| 0.1904        | 68.0  | 884  | 1.1100          | {'f1': 0.8249027237354084}  | {'accuracy': 0.82}   |
| 0.1904        | 69.0  | 897  | 1.1118          | {'f1': 0.8255950058525166}  | {'accuracy': 0.8212} |
| 0.1904        | 70.0  | 910  | 1.1415          | {'f1': 0.8293963254593175}  | {'accuracy': 0.818}  |
| 0.1904        | 71.0  | 923  | 1.1696          | {'f1': 0.8101582014987511}  | {'accuracy': 0.8176} |
| 0.1904        | 72.0  | 936  | 1.1047          | {'f1': 0.8335255670895808}  | {'accuracy': 0.8268} |
| 0.1904        | 73.0  | 949  | 1.1170          | {'f1': 0.8350983358547655}  | {'accuracy': 0.8256} |
| 0.1904        | 74.0  | 962  | 1.0945          | {'f1': 0.8333333333333333}  | {'accuracy': 0.828}  |
| 0.1904        | 75.0  | 975  | 1.1270          | {'f1': 0.8357760240511086}  | {'accuracy': 0.8252} |
| 0.1904        | 76.0  | 988  | 1.1019          | {'f1': 0.8337832626301581}  | {'accuracy': 0.8276} |
| 0.0034        | 77.0  | 1001 | 1.1019          | {'f1': 0.8329448329448329}  | {'accuracy': 0.828}  |
| 0.0034        | 78.0  | 1014 | 1.1066          | {'f1': 0.8326213592233009}  | {'accuracy': 0.8276} |
| 0.0034        | 79.0  | 1027 | 1.1238          | {'f1': 0.8217741935483871}  | {'accuracy': 0.8232} |
| 0.0034        | 80.0  | 1040 | 1.1272          | {'f1': 0.820823244552058}   | {'accuracy': 0.8224} |
| 0.0034        | 81.0  | 1053 | 1.1152          | {'f1': 0.8322304398598677}  | {'accuracy': 0.8276} |
| 0.0034        | 82.0  | 1066 | 1.1221          | {'f1': 0.8333974605617546}  | {'accuracy': 0.8268} |
| 0.0034        | 83.0  | 1079 | 1.1257          | {'f1': 0.834355828220859}   | {'accuracy': 0.8272} |
| 0.0034        | 84.0  | 1092 | 1.1243          | {'f1': 0.8333974605617546}  | {'accuracy': 0.8268} |
| 0.0034        | 85.0  | 1105 | 1.1229          | {'f1': 0.8332046332046331}  | {'accuracy': 0.8272} |
| 0.0034        | 86.0  | 1118 | 1.1460          | {'f1': 0.8208045509955302}  | {'accuracy': 0.8236} |
| 0.0034        | 87.0  | 1131 | 1.1643          | {'f1': 0.8331450094161958}  | {'accuracy': 0.8228} |
| 0.0034        | 88.0  | 1144 | 1.1578          | {'f1': 0.825090470446321}   | {'accuracy': 0.826}  |
| 0.0034        | 89.0  | 1157 | 1.3734          | {'f1': 0.8269774011299434}  | {'accuracy': 0.804}  |
| 0.0034        | 90.0  | 1170 | 1.3068          | {'f1': 0.7988013698630138}  | {'accuracy': 0.812}  |
| 0.0034        | 91.0  | 1183 | 1.2197          | {'f1': 0.8332714444857038}  | {'accuracy': 0.8204} |
| 0.0034        | 92.0  | 1196 | 1.1748          | {'f1': 0.8174190970834998}  | {'accuracy': 0.8172} |
| 0.0034        | 93.0  | 1209 | 1.1761          | {'f1': 0.8166062071745264}  | {'accuracy': 0.818}  |
| 0.0034        | 94.0  | 1222 | 1.2006          | {'f1': 0.8146622734761121}  | {'accuracy': 0.82}   |
| 0.0034        | 95.0  | 1235 | 1.1610          | {'f1': 0.8323076923076923}  | {'accuracy': 0.8256} |
| 0.0034        | 96.0  | 1248 | 1.1756          | {'f1': 0.8370510396975426}  | {'accuracy': 0.8276} |
| 0.0034        | 97.0  | 1261 | 1.2171          | {'f1': 0.812603648424544}   | {'accuracy': 0.8192} |
| 0.0034        | 98.0  | 1274 | 1.1959          | {'f1': 0.8168783285538713}  | {'accuracy': 0.8212} |
| 0.0034        | 99.0  | 1287 | 1.1805          | {'f1': 0.8344774980930587}  | {'accuracy': 0.8264} |
| 0.0034        | 100.0 | 1300 | 1.1942          | {'f1': 0.8371741594257649}  | {'accuracy': 0.8276} |
| 0.0034        | 101.0 | 1313 | 1.1747          | {'f1': 0.8332694518972786}  | {'accuracy': 0.826}  |
| 0.0034        | 102.0 | 1326 | 1.1655          | {'f1': 0.8292301680343885}  | {'accuracy': 0.8252} |
| 0.0034        | 103.0 | 1339 | 1.1666          | {'f1': 0.8296875}           | {'accuracy': 0.8256} |
| 0.0034        | 104.0 | 1352 | 1.1706          | {'f1': 0.8340425531914895}  | {'accuracy': 0.8284} |
| 0.0034        | 105.0 | 1365 | 1.2513          | {'f1': 0.808421052631579}   | {'accuracy': 0.818}  |
| 0.0034        | 106.0 | 1378 | 1.1799          | {'f1': 0.8342989571263036}  | {'accuracy': 0.8284} |
| 0.0034        | 107.0 | 1391 | 1.1937          | {'f1': 0.8216303470540758}  | {'accuracy': 0.8232} |
| 0.0034        | 108.0 | 1404 | 1.2025          | {'f1': 0.82414068745004}    | {'accuracy': 0.824}  |
| 0.0034        | 109.0 | 1417 | 1.2674          | {'f1': 0.8359866716031099}  | {'accuracy': 0.8228} |
| 0.0034        | 110.0 | 1430 | 1.2135          | {'f1': 0.8231587239070499}  | {'accuracy': 0.8204} |
| 0.0034        | 111.0 | 1443 | 1.2182          | {'f1': 0.821656050955414}   | {'accuracy': 0.8208} |
| 0.0034        | 112.0 | 1456 | 1.2181          | {'f1': 0.8222664015904573}  | {'accuracy': 0.8212} |
| 0.0034        | 113.0 | 1469 | 1.2174          | {'f1': 0.823156225218081}   | {'accuracy': 0.8216} |
| 0.0034        | 114.0 | 1482 | 1.2166          | {'f1': 0.825296442687747}   | {'accuracy': 0.8232} |
| 0.0034        | 115.0 | 1495 | 1.2167          | {'f1': 0.8249118683901293}  | {'accuracy': 0.8212} |
| 0.002         | 116.0 | 1508 | 1.2176          | {'f1': 0.8253223915592028}  | {'accuracy': 0.8212} |
| 0.002         | 117.0 | 1521 | 1.3367          | {'f1': 0.7998289136013687}  | {'accuracy': 0.8128} |
| 0.002         | 118.0 | 1534 | 1.4711          | {'f1': 0.8263009845288326}  | {'accuracy': 0.8024} |
| 0.002         | 119.0 | 1547 | 1.3399          | {'f1': 0.8018628281117698}  | {'accuracy': 0.8128} |
| 0.002         | 120.0 | 1560 | 1.3563          | {'f1': 0.7993197278911565}  | {'accuracy': 0.8112} |
| 0.002         | 121.0 | 1573 | 1.2461          | {'f1': 0.8310888803385917}  | {'accuracy': 0.8244} |
| 0.002         | 122.0 | 1586 | 1.2615          | {'f1': 0.8359788359788359}  | {'accuracy': 0.8264} |
| 0.002         | 123.0 | 1599 | 1.3245          | {'f1': 0.8064107971320118}  | {'accuracy': 0.8164} |
| 0.002         | 124.0 | 1612 | 1.2978          | {'f1': 0.8384473197781885}  | {'accuracy': 0.8252} |
| 0.002         | 125.0 | 1625 | 1.2612          | {'f1': 0.8151465798045603}  | {'accuracy': 0.8184} |
| 0.002         | 126.0 | 1638 | 1.2248          | {'f1': 0.8311890838206627}  | {'accuracy': 0.8268} |
| 0.002         | 127.0 | 1651 | 1.2302          | {'f1': 0.8400609291698401}  | {'accuracy': 0.832}  |
| 0.002         | 128.0 | 1664 | 1.2314          | {'f1': 0.8391023202738684}  | {'accuracy': 0.8308} |
| 0.002         | 129.0 | 1677 | 1.2311          | {'f1': 0.8397411496003045}  | {'accuracy': 0.8316} |
| 0.002         | 130.0 | 1690 | 1.2292          | {'f1': 0.8390541571319603}  | {'accuracy': 0.8312} |
| 0.002         | 131.0 | 1703 | 1.2272          | {'f1': 0.8374233128834357}  | {'accuracy': 0.8304} |
| 0.002         | 132.0 | 1716 | 1.2271          | {'f1': 0.8374951978486362}  | {'accuracy': 0.8308} |
| 0.002         | 133.0 | 1729 | 1.2278          | {'f1': 0.8379416282642089}  | {'accuracy': 0.8312} |
| 0.002         | 134.0 | 1742 | 1.2255          | {'f1': 0.8327512611563834}  | {'accuracy': 0.8276} |
| 0.002         | 135.0 | 1755 | 1.2323          | {'f1': 0.8382409177820267}  | {'accuracy': 0.8308} |
| 0.002         | 136.0 | 1768 | 1.2486          | {'f1': 0.8400000000000001}  | {'accuracy': 0.8304} |
| 0.002         | 137.0 | 1781 | 1.2466          | {'f1': 0.8393194706994328}  | {'accuracy': 0.83}   |
| 0.002         | 138.0 | 1794 | 1.2443          | {'f1': 0.8389057750759878}  | {'accuracy': 0.8304} |
| 0.002         | 139.0 | 1807 | 1.2382          | {'f1': 0.8370313695485846}  | {'accuracy': 0.8296} |
| 0.002         | 140.0 | 1820 | 1.2361          | {'f1': 0.8357748650732459}  | {'accuracy': 0.8296} |
| 0.002         | 141.0 | 1833 | 1.2361          | {'f1': 0.8338485316846985}  | {'accuracy': 0.828}  |
| 0.002         | 142.0 | 1846 | 1.2370          | {'f1': 0.8347490347490347}  | {'accuracy': 0.8288} |
| 0.002         | 143.0 | 1859 | 1.2379          | {'f1': 0.8347490347490347}  | {'accuracy': 0.8288} |
| 0.002         | 144.0 | 1872 | 1.2389          | {'f1': 0.8353258773621287}  | {'accuracy': 0.8292} |
| 0.002         | 145.0 | 1885 | 1.2399          | {'f1': 0.8363496341932999}  | {'accuracy': 0.83}   |
| 0.002         | 146.0 | 1898 | 1.2405          | {'f1': 0.8370484242890085}  | {'accuracy': 0.8304} |
| 0.002         | 147.0 | 1911 | 1.2413          | {'f1': 0.8380660015349194}  | {'accuracy': 0.8312} |
| 0.002         | 148.0 | 1924 | 1.2428          | {'f1': 0.837796480489671}   | {'accuracy': 0.8304} |
| 0.002         | 149.0 | 1937 | 1.2422          | {'f1': 0.836153846153846}   | {'accuracy': 0.8296} |
| 0.002         | 150.0 | 1950 | 1.2429          | {'f1': 0.8342989571263036}  | {'accuracy': 0.8284} |
| 0.002         | 151.0 | 1963 | 1.2446          | {'f1': 0.8338485316846985}  | {'accuracy': 0.828}  |
| 0.002         | 152.0 | 1976 | 1.2456          | {'f1': 0.8338485316846985}  | {'accuracy': 0.828}  |
| 0.002         | 153.0 | 1989 | 1.2492          | {'f1': 0.8294786358290867}  | {'accuracy': 0.826}  |
| 0.0006        | 154.0 | 2002 | 1.2568          | {'f1': 0.8233425962683605}  | {'accuracy': 0.822}  |
| 0.0006        | 155.0 | 2015 | 1.2544          | {'f1': 0.8274772996446901}  | {'accuracy': 0.8252} |
| 0.0006        | 156.0 | 2028 | 1.2590          | {'f1': 0.821841371064169}   | {'accuracy': 0.8212} |
| 0.0006        | 157.0 | 2041 | 1.2627          | {'f1': 0.8203252032520325}  | {'accuracy': 0.8232} |
| 0.0006        | 158.0 | 2054 | 1.2343          | {'f1': 0.8357748650732459}  | {'accuracy': 0.8296} |
| 0.0006        | 159.0 | 2067 | 1.2512          | {'f1': 0.8401515151515151}  | {'accuracy': 0.8312} |
| 0.0006        | 160.0 | 2080 | 1.2342          | {'f1': 0.8332679482149863}  | {'accuracy': 0.83}   |
| 0.0006        | 161.0 | 2093 | 1.2540          | {'f1': 0.8236245954692557}  | {'accuracy': 0.8256} |
| 0.0006        | 162.0 | 2106 | 1.2716          | {'f1': 0.8407212622088654}  | {'accuracy': 0.8304} |
| 0.0006        | 163.0 | 2119 | 1.3067          | {'f1': 0.8432752871433864}  | {'accuracy': 0.8308} |
| 0.0006        | 164.0 | 2132 | 1.3170          | {'f1': 0.8439690151235706}  | {'accuracy': 0.8308} |
| 0.0006        | 165.0 | 2145 | 1.2534          | {'f1': 0.8348765432098765}  | {'accuracy': 0.8288} |
| 0.0006        | 166.0 | 2158 | 1.4568          | {'f1': 0.8335724533715927}  | {'accuracy': 0.8144} |
| 0.0006        | 167.0 | 2171 | 1.7255          | {'f1': 0.7619485294117648}  | {'accuracy': 0.7928} |
| 0.0006        | 168.0 | 2184 | 1.3573          | {'f1': 0.8297715549005158}  | {'accuracy': 0.8152} |
| 0.0006        | 169.0 | 2197 | 1.3207          | {'f1': 0.8359433258762118}  | {'accuracy': 0.824}  |
| 0.0006        | 170.0 | 2210 | 1.3038          | {'f1': 0.8335843373493976}  | {'accuracy': 0.8232} |
| 0.0006        | 171.0 | 2223 | 1.2915          | {'f1': 0.8342205323193916}  | {'accuracy': 0.8256} |
| 0.0006        | 172.0 | 2236 | 1.2849          | {'f1': 0.8298117556665386}  | {'accuracy': 0.8228} |
| 0.0006        | 173.0 | 2249 | 1.4631          | {'f1': 0.8022212729602733}  | {'accuracy': 0.8148} |
| 0.0006        | 174.0 | 2262 | 1.3428          | {'f1': 0.8366592756836658}  | {'accuracy': 0.8232} |
| 0.0006        | 175.0 | 2275 | 1.2966          | {'f1': 0.8220472440944883}  | {'accuracy': 0.8192} |
| 0.0006        | 176.0 | 2288 | 1.3188          | {'f1': 0.8358662613981763}  | {'accuracy': 0.8272} |
| 0.0006        | 177.0 | 2301 | 1.4370          | {'f1': 0.8347826086956524}  | {'accuracy': 0.8176} |
| 0.0006        | 178.0 | 2314 | 1.3209          | {'f1': 0.8352985926207683}  | {'accuracy': 0.8268} |
| 0.0006        | 179.0 | 2327 | 1.3109          | {'f1': 0.8333333333333334}  | {'accuracy': 0.8272} |
| 0.0006        | 180.0 | 2340 | 1.3097          | {'f1': 0.8330745341614907}  | {'accuracy': 0.828}  |
| 0.0006        | 181.0 | 2353 | 1.3097          | {'f1': 0.8332685581033813}  | {'accuracy': 0.8284} |
| 0.0006        | 182.0 | 2366 | 1.3102          | {'f1': 0.8332685581033813}  | {'accuracy': 0.8284} |
| 0.0006        | 183.0 | 2379 | 1.3107          | {'f1': 0.8332685581033813}  | {'accuracy': 0.8284} |
| 0.0006        | 184.0 | 2392 | 1.3111          | {'f1': 0.8332685581033813}  | {'accuracy': 0.8284} |
| 0.0006        | 185.0 | 2405 | 1.3115          | {'f1': 0.8332685581033813}  | {'accuracy': 0.8284} |
| 0.0006        | 186.0 | 2418 | 1.3121          | {'f1': 0.8337218337218338}  | {'accuracy': 0.8288} |
| 0.0006        | 187.0 | 2431 | 1.3124          | {'f1': 0.8332685581033813}  | {'accuracy': 0.8284} |
| 0.0006        | 188.0 | 2444 | 1.3125          | {'f1': 0.8331388564760793}  | {'accuracy': 0.8284} |
| 0.0006        | 189.0 | 2457 | 1.3129          | {'f1': 0.8325545171339565}  | {'accuracy': 0.828}  |
| 0.0006        | 190.0 | 2470 | 1.3134          | {'f1': 0.8330089528999609}  | {'accuracy': 0.8284} |
| 0.0006        | 191.0 | 2483 | 1.3139          | {'f1': 0.8331388564760793}  | {'accuracy': 0.8284} |
| 0.0006        | 192.0 | 2496 | 1.3150          | {'f1': 0.8333980582524272}  | {'accuracy': 0.8284} |
| 0.0026        | 193.0 | 2509 | 1.3162          | {'f1': 0.8332688588007737}  | {'accuracy': 0.8276} |
| 0.0026        | 194.0 | 2522 | 1.3166          | {'f1': 0.8335913312693498}  | {'accuracy': 0.828}  |
| 0.0026        | 195.0 | 2535 | 1.3170          | {'f1': 0.8337853545137544}  | {'accuracy': 0.8284} |
| 0.0026        | 196.0 | 2548 | 1.3174          | {'f1': 0.8337853545137544}  | {'accuracy': 0.8284} |
| 0.0026        | 197.0 | 2561 | 1.3177          | {'f1': 0.8343034536282499}  | {'accuracy': 0.8292} |
| 0.0026        | 198.0 | 2574 | 1.3185          | {'f1': 0.8329466357308585}  | {'accuracy': 0.8272} |
| 0.0026        | 199.0 | 2587 | 1.3179          | {'f1': 0.83125}             | {'accuracy': 0.8272} |
| 0.0026        | 200.0 | 2600 | 1.3191          | {'f1': 0.8277755982738328}  | {'accuracy': 0.8244} |
| 0.0026        | 201.0 | 2613 | 1.3336          | {'f1': 0.8183648811921063}  | {'accuracy': 0.8196} |
| 0.0026        | 202.0 | 2626 | 1.3417          | {'f1': 0.8191403081914032}  | {'accuracy': 0.8216} |
| 0.0026        | 203.0 | 2639 | 1.3388          | {'f1': 0.8192478770723818}  | {'accuracy': 0.8212} |
| 0.0026        | 204.0 | 2652 | 1.3314          | {'f1': 0.8196062675773402}  | {'accuracy': 0.8204} |
| 0.0026        | 205.0 | 2665 | 1.3284          | {'f1': 0.820943245403677}   | {'accuracy': 0.8208} |
| 0.0026        | 206.0 | 2678 | 1.3247          | {'f1': 0.8220372572334523}  | {'accuracy': 0.8204} |
| 0.0026        | 207.0 | 2691 | 1.3207          | {'f1': 0.8256087981146898}  | {'accuracy': 0.8224} |
| 0.0026        | 208.0 | 2704 | 1.3203          | {'f1': 0.8326848249027238}  | {'accuracy': 0.828}  |
| 0.0026        | 209.0 | 2717 | 1.3791          | {'f1': 0.8407079646017698}  | {'accuracy': 0.8272} |
| 0.0026        | 210.0 | 2730 | 1.3041          | {'f1': 0.8251521298174442}  | {'accuracy': 0.8276} |
| 0.0026        | 211.0 | 2743 | 1.2786          | {'f1': 0.8385376999238386}  | {'accuracy': 0.8304} |
| 0.0026        | 212.0 | 2756 | 1.2782          | {'f1': 0.8351477449455676}  | {'accuracy': 0.8304} |
| 0.0026        | 213.0 | 2769 | 1.3099          | {'f1': 0.8365566932119834}  | {'accuracy': 0.8276} |
| 0.0026        | 214.0 | 2782 | 1.3136          | {'f1': 0.8366805608184918}  | {'accuracy': 0.8276} |
| 0.0026        | 215.0 | 2795 | 1.3667          | {'f1': 0.8195488721804511}  | {'accuracy': 0.8272} |
| 0.0026        | 216.0 | 2808 | 1.3974          | {'f1': 0.8440899202320521}  | {'accuracy': 0.828}  |
| 0.0026        | 217.0 | 2821 | 1.4398          | {'f1': 0.8103225806451613}  | {'accuracy': 0.8236} |
| 0.0026        | 218.0 | 2834 | 1.7629          | {'f1': 0.8198630136986301}  | {'accuracy': 0.7896} |
| 0.0026        | 219.0 | 2847 | 1.5840          | {'f1': 0.7884532529082292}  | {'accuracy': 0.8036} |
| 0.0026        | 220.0 | 2860 | 1.4395          | {'f1': 0.8162460567823343}  | {'accuracy': 0.8136} |
| 0.0026        | 221.0 | 2873 | 1.4460          | {'f1': 0.8201160541586073}  | {'accuracy': 0.814}  |
| 0.0026        | 222.0 | 2886 | 1.6072          | {'f1': 0.7866036925719193}  | {'accuracy': 0.8012} |
| 0.0026        | 223.0 | 2899 | 1.4704          | {'f1': 0.816967792615868}   | {'accuracy': 0.8136} |
| 0.0026        | 224.0 | 2912 | 1.4871          | {'f1': 0.8194233687405159}  | {'accuracy': 0.8096} |
| 0.0026        | 225.0 | 2925 | 1.4758          | {'f1': 0.8201771274547555}  | {'accuracy': 0.8132} |
| 0.0026        | 226.0 | 2938 | 1.4734          | {'f1': 0.8220338983050847}  | {'accuracy': 0.8152} |
| 0.0026        | 227.0 | 2951 | 1.4819          | {'f1': 0.8214285714285715}  | {'accuracy': 0.812}  |
| 0.0026        | 228.0 | 2964 | 1.4753          | {'f1': 0.8232149675448645}  | {'accuracy': 0.8148} |
| 0.0026        | 229.0 | 2977 | 1.4708          | {'f1': 0.8227168073676132}  | {'accuracy': 0.8152} |
| 0.0026        | 230.0 | 2990 | 1.4720          | {'f1': 0.8226733052470317}  | {'accuracy': 0.8148} |
| 0.0018        | 231.0 | 3003 | 1.4702          | {'f1': 0.8263056092843328}  | {'accuracy': 0.8204} |
| 0.0018        | 232.0 | 3016 | 1.4794          | {'f1': 0.8153420324238829}  | {'accuracy': 0.8132} |
| 0.0018        | 233.0 | 3029 | 1.4842          | {'f1': 0.8144616607071911}  | {'accuracy': 0.8132} |
| 0.0018        | 234.0 | 3042 | 1.6032          | {'f1': 0.7861420017108641}  | {'accuracy': 0.8}    |
| 0.0018        | 235.0 | 3055 | 1.4249          | {'f1': 0.8261376896149358}  | {'accuracy': 0.8212} |
| 0.0018        | 236.0 | 3068 | 1.5246          | {'f1': 0.8329718004338396}  | {'accuracy': 0.8152} |
| 0.0018        | 237.0 | 3081 | 1.4204          | {'f1': 0.8286792452830187}  | {'accuracy': 0.8184} |
| 0.0018        | 238.0 | 3094 | 1.4120          | {'f1': 0.8244575936883628}  | {'accuracy': 0.822}  |
| 0.0018        | 239.0 | 3107 | 1.4170          | {'f1': 0.8208184346444181}  | {'accuracy': 0.8196} |
| 0.0018        | 240.0 | 3120 | 1.4178          | {'f1': 0.8211446740858506}  | {'accuracy': 0.82}   |
| 0.0018        | 241.0 | 3133 | 1.4179          | {'f1': 0.8208184346444181}  | {'accuracy': 0.8196} |
| 0.0018        | 242.0 | 3146 | 1.4176          | {'f1': 0.8217546645494245}  | {'accuracy': 0.8204} |
| 0.0018        | 243.0 | 3159 | 1.4175          | {'f1': 0.8222222222222223}  | {'accuracy': 0.8208} |
| 0.0018        | 244.0 | 3172 | 1.4175          | {'f1': 0.8226894089646964}  | {'accuracy': 0.8212} |
| 0.0018        | 245.0 | 3185 | 1.4173          | {'f1': 0.8234362628661915}  | {'accuracy': 0.8216} |
| 0.0018        | 246.0 | 3198 | 1.4170          | {'f1': 0.8231104075979422}  | {'accuracy': 0.8212} |
| 0.0018        | 247.0 | 3211 | 1.4172          | {'f1': 0.8231104075979422}  | {'accuracy': 0.8212} |
| 0.0018        | 248.0 | 3224 | 1.4170          | {'f1': 0.8235759493670886}  | {'accuracy': 0.8216} |
| 0.0018        | 249.0 | 3237 | 1.4166          | {'f1': 0.8237154150197629}  | {'accuracy': 0.8216} |
| 0.0018        | 250.0 | 3250 | 1.4157          | {'f1': 0.824782951854775}   | {'accuracy': 0.8224} |
| 0.0018        | 251.0 | 3263 | 1.4147          | {'f1': 0.8258471237194642}  | {'accuracy': 0.8232} |
| 0.0018        | 252.0 | 3276 | 1.4139          | {'f1': 0.8267716535433071}  | {'accuracy': 0.824}  |
| 0.0018        | 253.0 | 3289 | 1.4158          | {'f1': 0.8263095706971249}  | {'accuracy': 0.8236} |
| 0.0018        | 254.0 | 3302 | 1.4164          | {'f1': 0.8263095706971249}  | {'accuracy': 0.8236} |
| 0.0018        | 255.0 | 3315 | 1.4164          | {'f1': 0.8263095706971249}  | {'accuracy': 0.8236} |
| 0.0018        | 256.0 | 3328 | 1.4163          | {'f1': 0.8263095706971249}  | {'accuracy': 0.8236} |
| 0.0018        | 257.0 | 3341 | 1.4156          | {'f1': 0.8275049115913556}  | {'accuracy': 0.8244} |
| 0.0018        | 258.0 | 3354 | 1.4152          | {'f1': 0.8276403612092659}  | {'accuracy': 0.8244} |
| 0.0018        | 259.0 | 3367 | 1.4152          | {'f1': 0.8271266170129361}  | {'accuracy': 0.8236} |
| 0.0018        | 260.0 | 3380 | 1.4151          | {'f1': 0.8261550509005481}  | {'accuracy': 0.8224} |
| 0.0018        | 261.0 | 3393 | 1.4152          | {'f1': 0.8258317025440313}  | {'accuracy': 0.822}  |
| 0.0018        | 262.0 | 3406 | 1.4153          | {'f1': 0.8262910798122066}  | {'accuracy': 0.8224} |
| 0.0018        | 263.0 | 3419 | 1.4156          | {'f1': 0.8261550509005481}  | {'accuracy': 0.8224} |
| 0.0018        | 264.0 | 3432 | 1.4160          | {'f1': 0.8268025078369906}  | {'accuracy': 0.8232} |
| 0.0018        | 265.0 | 3445 | 1.4161          | {'f1': 0.8268025078369906}  | {'accuracy': 0.8232} |
| 0.0018        | 266.0 | 3458 | 1.4163          | {'f1': 0.8268025078369906}  | {'accuracy': 0.8232} |
| 0.0018        | 267.0 | 3471 | 1.4170          | {'f1': 0.8268025078369906}  | {'accuracy': 0.8232} |
| 0.0018        | 268.0 | 3484 | 1.4173          | {'f1': 0.8268025078369906}  | {'accuracy': 0.8232} |
| 0.0018        | 269.0 | 3497 | 1.4182          | {'f1': 0.8276403612092659}  | {'accuracy': 0.8244} |
| 0.0009        | 270.0 | 3510 | 1.4186          | {'f1': 0.8276403612092659}  | {'accuracy': 0.8244} |
| 0.0009        | 271.0 | 3523 | 1.4189          | {'f1': 0.8276403612092659}  | {'accuracy': 0.8244} |
| 0.0009        | 272.0 | 3536 | 1.4194          | {'f1': 0.8276403612092659}  | {'accuracy': 0.8244} |
| 0.0009        | 273.0 | 3549 | 1.4196          | {'f1': 0.8276403612092659}  | {'accuracy': 0.8244} |
| 0.0009        | 274.0 | 3562 | 1.4197          | {'f1': 0.8276403612092659}  | {'accuracy': 0.8244} |
| 0.0009        | 275.0 | 3575 | 1.4195          | {'f1': 0.8277755982738328}  | {'accuracy': 0.8244} |
| 0.0009        | 276.0 | 3588 | 1.4196          | {'f1': 0.8268025078369906}  | {'accuracy': 0.8232} |
| 0.0009        | 277.0 | 3601 | 1.4200          | {'f1': 0.8271266170129361}  | {'accuracy': 0.8236} |
| 0.0009        | 278.0 | 3614 | 1.4201          | {'f1': 0.8268025078369906}  | {'accuracy': 0.8232} |
| 0.0009        | 279.0 | 3627 | 1.4203          | {'f1': 0.8268025078369906}  | {'accuracy': 0.8232} |
| 0.0009        | 280.0 | 3640 | 1.4205          | {'f1': 0.8268025078369906}  | {'accuracy': 0.8232} |
| 0.0009        | 281.0 | 3653 | 1.4205          | {'f1': 0.827073552425665}   | {'accuracy': 0.8232} |
| 0.0009        | 282.0 | 3666 | 1.4207          | {'f1': 0.8272087568412823}  | {'accuracy': 0.8232} |
| 0.0009        | 283.0 | 3679 | 1.4209          | {'f1': 0.8273972602739728}  | {'accuracy': 0.8236} |
| 0.0009        | 284.0 | 3692 | 1.4212          | {'f1': 0.8273972602739728}  | {'accuracy': 0.8236} |
| 0.0009        | 285.0 | 3705 | 1.4213          | {'f1': 0.827073552425665}   | {'accuracy': 0.8232} |
| 0.0009        | 286.0 | 3718 | 1.4215          | {'f1': 0.8275322643723112}  | {'accuracy': 0.8236} |
| 0.0009        | 287.0 | 3731 | 1.4216          | {'f1': 0.8272087568412823}  | {'accuracy': 0.8232} |
| 0.0009        | 288.0 | 3744 | 1.4214          | {'f1': 0.8270206950409996}  | {'accuracy': 0.8228} |
| 0.0009        | 289.0 | 3757 | 1.4214          | {'f1': 0.8282041293338528}  | {'accuracy': 0.8236} |
| 0.0009        | 290.0 | 3770 | 1.4208          | {'f1': 0.828361100348702}   | {'accuracy': 0.8228} |
| 0.0009        | 291.0 | 3783 | 1.4212          | {'f1': 0.8287591805179745}  | {'accuracy': 0.8228} |
| 0.0009        | 292.0 | 3796 | 1.4214          | {'f1': 0.8287591805179745}  | {'accuracy': 0.8228} |
| 0.0009        | 293.0 | 3809 | 1.4217          | {'f1': 0.8292117465224111}  | {'accuracy': 0.8232} |
| 0.0009        | 294.0 | 3822 | 1.4218          | {'f1': 0.8290796597061098}  | {'accuracy': 0.8232} |
| 0.0009        | 295.0 | 3835 | 1.4220          | {'f1': 0.8287591805179745}  | {'accuracy': 0.8228} |
| 0.0009        | 296.0 | 3848 | 1.4223          | {'f1': 0.8292117465224111}  | {'accuracy': 0.8232} |
| 0.0009        | 297.0 | 3861 | 1.4227          | {'f1': 0.8296639629200464}  | {'accuracy': 0.8236} |
| 0.0009        | 298.0 | 3874 | 1.4229          | {'f1': 0.8290235430335777}  | {'accuracy': 0.8228} |
| 0.0009        | 299.0 | 3887 | 1.4230          | {'f1': 0.8296639629200464}  | {'accuracy': 0.8236} |
| 0.0009        | 300.0 | 3900 | 1.4232          | {'f1': 0.8292117465224111}  | {'accuracy': 0.8232} |
| 0.0009        | 301.0 | 3913 | 1.4233          | {'f1': 0.8287591805179745}  | {'accuracy': 0.8228} |
| 0.0009        | 302.0 | 3926 | 1.4286          | {'f1': 0.8276947285601889}  | {'accuracy': 0.8248} |
| 0.0009        | 303.0 | 3939 | 1.4324          | {'f1': 0.8245059288537548}  | {'accuracy': 0.8224} |
| 0.0009        | 304.0 | 3952 | 1.4288          | {'f1': 0.8276947285601889}  | {'accuracy': 0.8248} |
| 0.0009        | 305.0 | 3965 | 1.4255          | {'f1': 0.8277755982738328}  | {'accuracy': 0.8244} |
| 0.0009        | 306.0 | 3978 | 1.4249          | {'f1': 0.8275862068965518}  | {'accuracy': 0.824}  |
| 0.0009        | 307.0 | 3991 | 1.4248          | {'f1': 0.8275862068965518}  | {'accuracy': 0.824}  |
| 0.0           | 308.0 | 4004 | 1.4249          | {'f1': 0.8280454367410889}  | {'accuracy': 0.8244} |
| 0.0           | 309.0 | 4017 | 1.4257          | {'f1': 0.8275862068965518}  | {'accuracy': 0.824}  |
| 0.0           | 310.0 | 4030 | 1.4276          | {'f1': 0.8281004709576137}  | {'accuracy': 0.8248} |
| 0.0           | 311.0 | 4043 | 1.4281          | {'f1': 0.8282907662082514}  | {'accuracy': 0.8252} |
| 0.0           | 312.0 | 4056 | 1.4282          | {'f1': 0.8281004709576137}  | {'accuracy': 0.8248} |
| 0.0           | 313.0 | 4069 | 1.4253          | {'f1': 0.8277474668745128}  | {'accuracy': 0.8232} |
| 0.0           | 314.0 | 4082 | 1.4248          | {'f1': 0.827906976744186}   | {'accuracy': 0.8224} |
| 0.0           | 315.0 | 4095 | 1.4250          | {'f1': 0.8288148721920992}  | {'accuracy': 0.8232} |
| 0.0           | 316.0 | 4108 | 1.4252          | {'f1': 0.8292682926829268}  | {'accuracy': 0.8236} |
| 0.0           | 317.0 | 4121 | 1.4253          | {'f1': 0.8296639629200464}  | {'accuracy': 0.8236} |
| 0.0           | 318.0 | 4134 | 1.4255          | {'f1': 0.8301158301158301}  | {'accuracy': 0.824}  |
| 0.0           | 319.0 | 4147 | 1.4257          | {'f1': 0.8296639629200464}  | {'accuracy': 0.8236} |
| 0.0           | 320.0 | 4160 | 1.4259          | {'f1': 0.8296639629200464}  | {'accuracy': 0.8236} |
| 0.0           | 321.0 | 4173 | 1.4261          | {'f1': 0.8296639629200464}  | {'accuracy': 0.8236} |
| 0.0           | 322.0 | 4186 | 1.4265          | {'f1': 0.8308285163776494}  | {'accuracy': 0.8244} |
| 0.0           | 323.0 | 4199 | 1.4269          | {'f1': 0.8309587986137851}  | {'accuracy': 0.8244} |
| 0.0           | 324.0 | 4212 | 1.4272          | {'f1': 0.8314087759815243}  | {'accuracy': 0.8248} |
| 0.0           | 325.0 | 4225 | 1.4275          | {'f1': 0.8314087759815243}  | {'accuracy': 0.8248} |
| 0.0           | 326.0 | 4238 | 1.4277          | {'f1': 0.8314087759815243}  | {'accuracy': 0.8248} |
| 0.0           | 327.0 | 4251 | 1.4278          | {'f1': 0.8309587986137851}  | {'accuracy': 0.8244} |
| 0.0           | 328.0 | 4264 | 1.4279          | {'f1': 0.8305084745762712}  | {'accuracy': 0.824}  |
| 0.0           | 329.0 | 4277 | 1.4281          | {'f1': 0.8305084745762712}  | {'accuracy': 0.824}  |
| 0.0           | 330.0 | 4290 | 1.4283          | {'f1': 0.8305084745762712}  | {'accuracy': 0.824}  |
| 0.0           | 331.0 | 4303 | 1.4286          | {'f1': 0.8314693405322021}  | {'accuracy': 0.8252} |
| 0.0           | 332.0 | 4316 | 1.4288          | {'f1': 0.8296639629200464}  | {'accuracy': 0.8236} |
| 0.0           | 333.0 | 4329 | 1.4290          | {'f1': 0.8298530549110597}  | {'accuracy': 0.824}  |
| 0.0           | 334.0 | 4342 | 1.4292          | {'f1': 0.8301740812379111}  | {'accuracy': 0.8244} |
| 0.0           | 335.0 | 4355 | 1.4295          | {'f1': 0.8297213622291022}  | {'accuracy': 0.824}  |
| 0.0           | 336.0 | 4368 | 1.4295          | {'f1': 0.8288148721920992}  | {'accuracy': 0.8232} |
| 0.0           | 337.0 | 4381 | 1.4292          | {'f1': 0.8285492629945695}  | {'accuracy': 0.8232} |
| 0.0           | 338.0 | 4394 | 1.4293          | {'f1': 0.8285492629945695}  | {'accuracy': 0.8232} |
| 0.0           | 339.0 | 4407 | 1.4293          | {'f1': 0.828361100348702}   | {'accuracy': 0.8228} |
| 0.0           | 340.0 | 4420 | 1.4294          | {'f1': 0.8301740812379111}  | {'accuracy': 0.8244} |
| 0.0           | 341.0 | 4433 | 1.4298          | {'f1': 0.8314087759815243}  | {'accuracy': 0.8248} |
| 0.0           | 342.0 | 4446 | 1.4301          | {'f1': 0.8310888803385917}  | {'accuracy': 0.8244} |
| 0.0           | 343.0 | 4459 | 1.4303          | {'f1': 0.8315384615384616}  | {'accuracy': 0.8248} |
| 0.0           | 344.0 | 4472 | 1.4307          | {'f1': 0.8315384615384616}  | {'accuracy': 0.8248} |
| 0.0           | 345.0 | 4485 | 1.4306          | {'f1': 0.8315384615384616}  | {'accuracy': 0.8248} |
| 0.0           | 346.0 | 4498 | 1.4303          | {'f1': 0.8314087759815243}  | {'accuracy': 0.8248} |
| 0.0           | 347.0 | 4511 | 1.4293          | {'f1': 0.8304364619544227}  | {'accuracy': 0.8244} |
| 0.0           | 348.0 | 4524 | 1.4292          | {'f1': 0.8301740812379111}  | {'accuracy': 0.8244} |
| 0.0           | 349.0 | 4537 | 1.4293          | {'f1': 0.8301740812379111}  | {'accuracy': 0.8244} |
| 0.0           | 350.0 | 4550 | 1.4294          | {'f1': 0.8313392512543419}  | {'accuracy': 0.8252} |
| 0.0           | 351.0 | 4563 | 1.4277          | {'f1': 0.8278274387874076}  | {'accuracy': 0.8228} |
| 0.0           | 352.0 | 4576 | 1.4276          | {'f1': 0.8275593616193071}  | {'accuracy': 0.8228} |
| 0.0           | 353.0 | 4589 | 1.4276          | {'f1': 0.827425009738995}   | {'accuracy': 0.8228} |
| 0.0           | 354.0 | 4602 | 1.4278          | {'f1': 0.8277474668745128}  | {'accuracy': 0.8232} |
| 0.0           | 355.0 | 4615 | 1.4275          | {'f1': 0.8304364619544227}  | {'accuracy': 0.8244} |
| 0.0           | 356.0 | 4628 | 1.4281          | {'f1': 0.8306980331662168}  | {'accuracy': 0.8244} |
| 0.0           | 357.0 | 4641 | 1.4286          | {'f1': 0.8314087759815243}  | {'accuracy': 0.8248} |
| 0.0           | 358.0 | 4654 | 1.4287          | {'f1': 0.8312788906009245}  | {'accuracy': 0.8248} |
| 0.0           | 359.0 | 4667 | 1.4289          | {'f1': 0.8314087759815243}  | {'accuracy': 0.8248} |
| 0.0           | 360.0 | 4680 | 1.4291          | {'f1': 0.8312788906009245}  | {'accuracy': 0.8248} |
| 0.0           | 361.0 | 4693 | 1.4291          | {'f1': 0.8311488049344642}  | {'accuracy': 0.8248} |
| 0.0           | 362.0 | 4706 | 1.4292          | {'f1': 0.8311488049344642}  | {'accuracy': 0.8248} |
| 0.0           | 363.0 | 4719 | 1.4383          | {'f1': 0.8281557215886748}  | {'accuracy': 0.8252} |
| 0.0           | 364.0 | 4732 | 1.4445          | {'f1': 0.8256735340729001}  | {'accuracy': 0.824}  |
| 0.0           | 365.0 | 4745 | 1.4462          | {'f1': 0.8252080856123662}  | {'accuracy': 0.8236} |
| 0.0           | 366.0 | 4758 | 1.4463          | {'f1': 0.8252080856123662}  | {'accuracy': 0.8236} |
| 0.0           | 367.0 | 4771 | 1.4441          | {'f1': 0.8260869565217391}  | {'accuracy': 0.824}  |
| 0.0           | 368.0 | 4784 | 1.4435          | {'f1': 0.8271507498026835}  | {'accuracy': 0.8248} |
| 0.0           | 369.0 | 4797 | 1.4432          | {'f1': 0.8276134122287968}  | {'accuracy': 0.8252} |
| 0.0           | 370.0 | 4810 | 1.4429          | {'f1': 0.8272870662460567}  | {'accuracy': 0.8248} |
| 0.0           | 371.0 | 4823 | 1.4427          | {'f1': 0.8278849940921623}  | {'accuracy': 0.8252} |
| 0.0           | 372.0 | 4836 | 1.4426          | {'f1': 0.8280204643841007}  | {'accuracy': 0.8252} |
| 0.0           | 373.0 | 4849 | 1.4426          | {'f1': 0.8280204643841007}  | {'accuracy': 0.8252} |
| 0.0           | 374.0 | 4862 | 1.4428          | {'f1': 0.8280204643841007}  | {'accuracy': 0.8252} |
| 0.0           | 375.0 | 4875 | 1.4415          | {'f1': 0.8278301886792453}  | {'accuracy': 0.8248} |
| 0.0           | 376.0 | 4888 | 1.4412          | {'f1': 0.828750981932443}   | {'accuracy': 0.8256} |
| 0.0           | 377.0 | 4901 | 1.4416          | {'f1': 0.8278301886792453}  | {'accuracy': 0.8248} |
| 0.0           | 378.0 | 4914 | 1.4506          | {'f1': 0.8247914183551848}  | {'accuracy': 0.8236} |
| 0.0           | 379.0 | 4927 | 1.4528          | {'f1': 0.8253083963390371}  | {'accuracy': 0.8244} |
| 0.0           | 380.0 | 4940 | 1.4528          | {'f1': 0.8253083963390371}  | {'accuracy': 0.8244} |
| 0.0           | 381.0 | 4953 | 1.4527          | {'f1': 0.8253083963390371}  | {'accuracy': 0.8244} |
| 0.0           | 382.0 | 4966 | 1.4519          | {'f1': 0.8251192368839427}  | {'accuracy': 0.824}  |
| 0.0           | 383.0 | 4979 | 1.4503          | {'f1': 0.8261386138613862}  | {'accuracy': 0.8244} |
| 0.0           | 384.0 | 4992 | 1.4494          | {'f1': 0.8264136022143139}  | {'accuracy': 0.8244} |
| 0.0           | 385.0 | 5005 | 1.4490          | {'f1': 0.8274772996446901}  | {'accuracy': 0.8252} |
| 0.0           | 386.0 | 5018 | 1.4483          | {'f1': 0.8279400157853197}  | {'accuracy': 0.8256} |
| 0.0           | 387.0 | 5031 | 1.4479          | {'f1': 0.8272870662460567}  | {'accuracy': 0.8248} |
| 0.0           | 388.0 | 5044 | 1.4477          | {'f1': 0.8274231678486997}  | {'accuracy': 0.8248} |
| 0.0           | 389.0 | 5057 | 1.4471          | {'f1': 0.8281557215886748}  | {'accuracy': 0.8252} |
| 0.0           | 390.0 | 5070 | 1.4501          | {'f1': 0.8274772996446901}  | {'accuracy': 0.8252} |
| 0.0           | 391.0 | 5083 | 1.4676          | {'f1': 0.8250401284109149}  | {'accuracy': 0.8256} |
| 0.0           | 392.0 | 5096 | 1.4718          | {'f1': 0.8244766505636072}  | {'accuracy': 0.8256} |
| 0.0           | 393.0 | 5109 | 1.4718          | {'f1': 0.8249496981891349}  | {'accuracy': 0.826}  |
| 0.0           | 394.0 | 5122 | 1.4704          | {'f1': 0.8252310164724789}  | {'accuracy': 0.826}  |
| 0.0           | 395.0 | 5135 | 1.4684          | {'f1': 0.8247091857200161}  | {'accuracy': 0.8252} |
| 0.0           | 396.0 | 5148 | 1.4633          | {'f1': 0.8258785942492013}  | {'accuracy': 0.8256} |
| 0.0           | 397.0 | 5161 | 1.4528          | {'f1': 0.8270676691729324}  | {'accuracy': 0.8252} |
| 0.0           | 398.0 | 5174 | 1.4502          | {'f1': 0.8285376428852975}  | {'accuracy': 0.826}  |
| 0.0           | 399.0 | 5187 | 1.4493          | {'f1': 0.8276947285601889}  | {'accuracy': 0.8248} |
| 0.0           | 400.0 | 5200 | 1.4476          | {'f1': 0.8263943440691282}  | {'accuracy': 0.8232} |
| 0.0           | 401.0 | 5213 | 1.4489          | {'f1': 0.8289992119779355}  | {'accuracy': 0.8264} |
| 0.0           | 402.0 | 5226 | 1.4496          | {'f1': 0.8290564547966838}  | {'accuracy': 0.8268} |
| 0.0           | 403.0 | 5239 | 1.4494          | {'f1': 0.829518547750592}   | {'accuracy': 0.8272} |
| 0.0           | 404.0 | 5252 | 1.4496          | {'f1': 0.8291913214990139}  | {'accuracy': 0.8268} |
| 0.0           | 405.0 | 5265 | 1.4496          | {'f1': 0.8291913214990139}  | {'accuracy': 0.8268} |
| 0.0           | 406.0 | 5278 | 1.4494          | {'f1': 0.8289992119779355}  | {'accuracy': 0.8264} |
| 0.0           | 407.0 | 5291 | 1.4493          | {'f1': 0.828672705789681}   | {'accuracy': 0.826}  |
| 0.0           | 408.0 | 5304 | 1.4491          | {'f1': 0.8283464566929134}  | {'accuracy': 0.8256} |
| 0.0           | 409.0 | 5317 | 1.4490          | {'f1': 0.8280204643841007}  | {'accuracy': 0.8252} |
| 0.0           | 410.0 | 5330 | 1.4491          | {'f1': 0.8280204643841007}  | {'accuracy': 0.8252} |
| 0.0           | 411.0 | 5343 | 1.4495          | {'f1': 0.8280204643841007}  | {'accuracy': 0.8252} |
| 0.0           | 412.0 | 5356 | 1.4494          | {'f1': 0.8276947285601889}  | {'accuracy': 0.8248} |
| 0.0           | 413.0 | 5369 | 1.4493          | {'f1': 0.8276947285601889}  | {'accuracy': 0.8248} |
| 0.0           | 414.0 | 5382 | 1.4493          | {'f1': 0.8273692489186001}  | {'accuracy': 0.8244} |
| 0.0           | 415.0 | 5395 | 1.4493          | {'f1': 0.8278301886792453}  | {'accuracy': 0.8248} |
| 0.0           | 416.0 | 5408 | 1.4493          | {'f1': 0.8279654359780046}  | {'accuracy': 0.8248} |
| 0.0           | 417.0 | 5421 | 1.4492          | {'f1': 0.8279654359780046}  | {'accuracy': 0.8248} |
| 0.0           | 418.0 | 5434 | 1.4493          | {'f1': 0.8273155416012559}  | {'accuracy': 0.824}  |
| 0.0           | 419.0 | 5447 | 1.4493          | {'f1': 0.8273155416012559}  | {'accuracy': 0.824}  |
| 0.0           | 420.0 | 5460 | 1.4493          | {'f1': 0.828235294117647}   | {'accuracy': 0.8248} |
| 0.0           | 421.0 | 5473 | 1.4493          | {'f1': 0.828235294117647}   | {'accuracy': 0.8248} |
| 0.0           | 422.0 | 5486 | 1.4498          | {'f1': 0.8273155416012559}  | {'accuracy': 0.824}  |
| 0.0           | 423.0 | 5499 | 1.4499          | {'f1': 0.8273155416012559}  | {'accuracy': 0.824}  |
| 0.0           | 424.0 | 5512 | 1.4499          | {'f1': 0.828235294117647}   | {'accuracy': 0.8248} |
| 0.0           | 425.0 | 5525 | 1.4504          | {'f1': 0.8273155416012559}  | {'accuracy': 0.824}  |
| 0.0           | 426.0 | 5538 | 1.4507          | {'f1': 0.8273155416012559}  | {'accuracy': 0.824}  |
| 0.0           | 427.0 | 5551 | 1.4472          | {'f1': 0.8306264501160093}  | {'accuracy': 0.8248} |
| 0.0           | 428.0 | 5564 | 1.4526          | {'f1': 0.8352402745995423}  | {'accuracy': 0.8272} |
| 0.0           | 429.0 | 5577 | 1.4554          | {'f1': 0.8340296240030383}  | {'accuracy': 0.8252} |
| 0.0           | 430.0 | 5590 | 1.4555          | {'f1': 0.8340296240030383}  | {'accuracy': 0.8252} |
| 0.0           | 431.0 | 5603 | 1.4543          | {'f1': 0.8337771015595283}  | {'accuracy': 0.8252} |
| 0.0           | 432.0 | 5616 | 1.4541          | {'f1': 0.8340943683409437}  | {'accuracy': 0.8256} |
| 0.0           | 433.0 | 5629 | 1.4541          | {'f1': 0.8344118766653978}  | {'accuracy': 0.826}  |
| 0.0           | 434.0 | 5642 | 1.4510          | {'f1': 0.832183908045977}   | {'accuracy': 0.8248} |
| 0.0           | 435.0 | 5655 | 1.4500          | {'f1': 0.83}                | {'accuracy': 0.8232} |
| 0.0           | 436.0 | 5668 | 1.4497          | {'f1': 0.829738058551618}   | {'accuracy': 0.8232} |
| 0.0           | 437.0 | 5681 | 1.4486          | {'f1': 0.8279106232849863}  | {'accuracy': 0.8244} |
| 0.0           | 438.0 | 5694 | 1.4499          | {'f1': 0.8274231678486997}  | {'accuracy': 0.8248} |
| 0.0           | 439.0 | 5707 | 1.4504          | {'f1': 0.8284023668639053}  | {'accuracy': 0.826}  |
| 0.0           | 440.0 | 5720 | 1.4504          | {'f1': 0.8284023668639053}  | {'accuracy': 0.826}  |
| 0.0           | 441.0 | 5733 | 1.4504          | {'f1': 0.8280757097791798}  | {'accuracy': 0.8256} |
| 0.0           | 442.0 | 5746 | 1.4504          | {'f1': 0.8277493102089082}  | {'accuracy': 0.8252} |
| 0.0           | 443.0 | 5759 | 1.4502          | {'f1': 0.8275590551181103}  | {'accuracy': 0.8248} |
| 0.0           | 444.0 | 5772 | 1.4500          | {'f1': 0.828616352201258}   | {'accuracy': 0.8256} |
| 0.0           | 445.0 | 5785 | 1.4498          | {'f1': 0.8282907662082514}  | {'accuracy': 0.8252} |
| 0.0           | 446.0 | 5798 | 1.4498          | {'f1': 0.8282907662082514}  | {'accuracy': 0.8252} |
| 0.0           | 447.0 | 5811 | 1.4499          | {'f1': 0.8282907662082514}  | {'accuracy': 0.8252} |
| 0.0           | 448.0 | 5824 | 1.4499          | {'f1': 0.8279654359780046}  | {'accuracy': 0.8248} |
| 0.0           | 449.0 | 5837 | 1.4500          | {'f1': 0.8279654359780046}  | {'accuracy': 0.8248} |
| 0.0           | 450.0 | 5850 | 1.4500          | {'f1': 0.8284255987436199}  | {'accuracy': 0.8252} |
| 0.0           | 451.0 | 5863 | 1.4500          | {'f1': 0.8281004709576137}  | {'accuracy': 0.8248} |
| 0.0           | 452.0 | 5876 | 1.4500          | {'f1': 0.8283699059561128}  | {'accuracy': 0.8248} |
| 0.0           | 453.0 | 5889 | 1.4500          | {'f1': 0.8277212216131559}  | {'accuracy': 0.824}  |
| 0.0           | 454.0 | 5902 | 1.4501          | {'f1': 0.8281800391389432}  | {'accuracy': 0.8244} |
| 0.0           | 455.0 | 5915 | 1.4501          | {'f1': 0.8281800391389432}  | {'accuracy': 0.8244} |
| 0.0           | 456.0 | 5928 | 1.4500          | {'f1': 0.8286384976525822}  | {'accuracy': 0.8248} |
| 0.0           | 457.0 | 5941 | 1.4499          | {'f1': 0.8270206950409996}  | {'accuracy': 0.8228} |
| 0.0           | 458.0 | 5954 | 1.4499          | {'f1': 0.8266978922716627}  | {'accuracy': 0.8224} |
| 0.0           | 459.0 | 5967 | 1.4500          | {'f1': 0.8271556769410847}  | {'accuracy': 0.8228} |
| 0.0           | 460.0 | 5980 | 1.4501          | {'f1': 0.826833073322933}   | {'accuracy': 0.8224} |
| 0.0           | 461.0 | 5993 | 1.4502          | {'f1': 0.8271556769410847}  | {'accuracy': 0.8228} |
| 0.0           | 462.0 | 6006 | 1.4502          | {'f1': 0.826833073322933}   | {'accuracy': 0.8224} |
| 0.0           | 463.0 | 6019 | 1.4503          | {'f1': 0.826833073322933}   | {'accuracy': 0.8224} |
| 0.0           | 464.0 | 6032 | 1.4504          | {'f1': 0.826833073322933}   | {'accuracy': 0.8224} |
| 0.0           | 465.0 | 6045 | 1.4506          | {'f1': 0.826833073322933}   | {'accuracy': 0.8224} |
| 0.0           | 466.0 | 6058 | 1.4511          | {'f1': 0.8270206950409996}  | {'accuracy': 0.8228} |
| 0.0           | 467.0 | 6071 | 1.4512          | {'f1': 0.8270206950409996}  | {'accuracy': 0.8228} |
| 0.0           | 468.0 | 6084 | 1.4513          | {'f1': 0.8270206950409996}  | {'accuracy': 0.8228} |
| 0.0           | 469.0 | 6097 | 1.4514          | {'f1': 0.8270206950409996}  | {'accuracy': 0.8228} |
| 0.0           | 470.0 | 6110 | 1.4514          | {'f1': 0.8270206950409996}  | {'accuracy': 0.8228} |
| 0.0           | 471.0 | 6123 | 1.4515          | {'f1': 0.8270206950409996}  | {'accuracy': 0.8228} |
| 0.0           | 472.0 | 6136 | 1.4515          | {'f1': 0.8274785323965652}  | {'accuracy': 0.8232} |
| 0.0           | 473.0 | 6149 | 1.4516          | {'f1': 0.8274785323965652}  | {'accuracy': 0.8232} |
| 0.0           | 474.0 | 6162 | 1.4516          | {'f1': 0.8271556769410847}  | {'accuracy': 0.8228} |
| 0.0           | 475.0 | 6175 | 1.4517          | {'f1': 0.8271556769410847}  | {'accuracy': 0.8228} |
| 0.0           | 476.0 | 6188 | 1.4517          | {'f1': 0.8271556769410847}  | {'accuracy': 0.8228} |
| 0.0           | 477.0 | 6201 | 1.4517          | {'f1': 0.8271556769410847}  | {'accuracy': 0.8228} |
| 0.0           | 478.0 | 6214 | 1.4518          | {'f1': 0.82729044834308}    | {'accuracy': 0.8228} |
| 0.0           | 479.0 | 6227 | 1.4518          | {'f1': 0.82729044834308}    | {'accuracy': 0.8228} |
| 0.0           | 480.0 | 6240 | 1.4519          | {'f1': 0.82729044834308}    | {'accuracy': 0.8228} |
| 0.0           | 481.0 | 6253 | 1.4519          | {'f1': 0.82729044834308}    | {'accuracy': 0.8228} |
| 0.0           | 482.0 | 6266 | 1.4519          | {'f1': 0.82729044834308}    | {'accuracy': 0.8228} |
| 0.0           | 483.0 | 6279 | 1.4520          | {'f1': 0.82729044834308}    | {'accuracy': 0.8228} |
| 0.0           | 484.0 | 6292 | 1.4520          | {'f1': 0.8277474668745128}  | {'accuracy': 0.8232} |
| 0.0           | 485.0 | 6305 | 1.4520          | {'f1': 0.8277474668745128}  | {'accuracy': 0.8232} |
| 0.0           | 486.0 | 6318 | 1.4521          | {'f1': 0.8282041293338528}  | {'accuracy': 0.8236} |
| 0.0           | 487.0 | 6331 | 1.4521          | {'f1': 0.8282041293338528}  | {'accuracy': 0.8236} |
| 0.0           | 488.0 | 6344 | 1.4522          | {'f1': 0.8277474668745128}  | {'accuracy': 0.8232} |
| 0.0           | 489.0 | 6357 | 1.4522          | {'f1': 0.8277474668745128}  | {'accuracy': 0.8232} |
| 0.0           | 490.0 | 6370 | 1.4522          | {'f1': 0.8282041293338528}  | {'accuracy': 0.8236} |
| 0.0           | 491.0 | 6383 | 1.4523          | {'f1': 0.8282041293338528}  | {'accuracy': 0.8236} |
| 0.0           | 492.0 | 6396 | 1.4523          | {'f1': 0.8282041293338528}  | {'accuracy': 0.8236} |
| 0.0           | 493.0 | 6409 | 1.4523          | {'f1': 0.8282041293338528}  | {'accuracy': 0.8236} |
| 0.0           | 494.0 | 6422 | 1.4523          | {'f1': 0.8282041293338528}  | {'accuracy': 0.8236} |
| 0.0           | 495.0 | 6435 | 1.4523          | {'f1': 0.8282041293338528}  | {'accuracy': 0.8236} |
| 0.0           | 496.0 | 6448 | 1.4523          | {'f1': 0.8282041293338528}  | {'accuracy': 0.8236} |
| 0.0           | 497.0 | 6461 | 1.4523          | {'f1': 0.8282041293338528}  | {'accuracy': 0.8236} |
| 0.0           | 498.0 | 6474 | 1.4523          | {'f1': 0.8282041293338528}  | {'accuracy': 0.8236} |
| 0.0           | 499.0 | 6487 | 1.4523          | {'f1': 0.8282041293338528}  | {'accuracy': 0.8236} |
| 0.0           | 500.0 | 6500 | 1.4523          | {'f1': 0.8282041293338528}  | {'accuracy': 0.8236} |


### Framework versions

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