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_500
  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_500

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: 1.2845
- F1: {'f1': 0.8862179487179487}
- Accuracy: {'accuracy': 0.8864}

## 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   | 32    | 0.6877          | {'f1': 0.3681048607318405} | {'accuracy': 0.5372} |
| No log        | 2.0   | 64    | 0.6758          | {'f1': 0.327455919395466}  | {'accuracy': 0.5728} |
| No log        | 3.0   | 96    | 0.5685          | {'f1': 0.6833333333333333} | {'accuracy': 0.7112} |
| No log        | 4.0   | 128   | 0.4751          | {'f1': 0.7951363301400148} | {'accuracy': 0.7776} |
| No log        | 5.0   | 160   | 0.4088          | {'f1': 0.8316752884998011} | {'accuracy': 0.8308} |
| No log        | 6.0   | 192   | 0.3793          | {'f1': 0.8511301636788777} | {'accuracy': 0.8472} |
| No log        | 7.0   | 224   | 0.3794          | {'f1': 0.8486312399355878} | {'accuracy': 0.8496} |
| No log        | 8.0   | 256   | 0.4121          | {'f1': 0.8492257538712306} | {'accuracy': 0.852}  |
| No log        | 9.0   | 288   | 0.3895          | {'f1': 0.8575875486381322} | {'accuracy': 0.8536} |
| No log        | 10.0  | 320   | 0.4960          | {'f1': 0.8497297297297297} | {'accuracy': 0.8332} |
| No log        | 11.0  | 352   | 0.4200          | {'f1': 0.8564650059311981} | {'accuracy': 0.8548} |
| No log        | 12.0  | 384   | 0.4513          | {'f1': 0.8606985146527499} | {'accuracy': 0.8612} |
| No log        | 13.0  | 416   | 0.6481          | {'f1': 0.8077442593426384} | {'accuracy': 0.8292} |
| No log        | 14.0  | 448   | 0.4766          | {'f1': 0.8713335940555339} | {'accuracy': 0.8684} |
| No log        | 15.0  | 480   | 0.5145          | {'f1': 0.8694986605434367} | {'accuracy': 0.8636} |
| 0.2917        | 16.0  | 512   | 0.5238          | {'f1': 0.8653624856156501} | {'accuracy': 0.8596} |
| 0.2917        | 17.0  | 544   | 0.5432          | {'f1': 0.8691339183517741} | {'accuracy': 0.8628} |
| 0.2917        | 18.0  | 576   | 0.5481          | {'f1': 0.8594905505341003} | {'accuracy': 0.8632} |
| 0.2917        | 19.0  | 608   | 0.5885          | {'f1': 0.8667917448405253} | {'accuracy': 0.858}  |
| 0.2917        | 20.0  | 640   | 0.6552          | {'f1': 0.8473706712270199} | {'accuracy': 0.8572} |
| 0.2917        | 21.0  | 672   | 0.5610          | {'f1': 0.8746105919003115} | {'accuracy': 0.8712} |
| 0.2917        | 22.0  | 704   | 0.6055          | {'f1': 0.8668532586965214} | {'accuracy': 0.8668} |
| 0.2917        | 23.0  | 736   | 0.7313          | {'f1': 0.8440445586975149} | {'accuracy': 0.8544} |
| 0.2917        | 24.0  | 768   | 0.6457          | {'f1': 0.8701996927803379} | {'accuracy': 0.8648} |
| 0.2917        | 25.0  | 800   | 0.7746          | {'f1': 0.8427835051546393} | {'accuracy': 0.8536} |
| 0.2917        | 26.0  | 832   | 0.6619          | {'f1': 0.8726016884113585} | {'accuracy': 0.8672} |
| 0.2917        | 27.0  | 864   | 0.7860          | {'f1': 0.8489761092150171} | {'accuracy': 0.8584} |
| 0.2917        | 28.0  | 896   | 0.6837          | {'f1': 0.8769968051118211} | {'accuracy': 0.8768} |
| 0.2917        | 29.0  | 928   | 0.7311          | {'f1': 0.8708881578947368} | {'accuracy': 0.8744} |
| 0.2917        | 30.0  | 960   | 0.7216          | {'f1': 0.8781074578989576} | {'accuracy': 0.8784} |
| 0.2917        | 31.0  | 992   | 0.7178          | {'f1': 0.8824463860206514} | {'accuracy': 0.8816} |
| 0.0335        | 32.0  | 1024  | 0.7308          | {'f1': 0.8810916179337233} | {'accuracy': 0.878}  |
| 0.0335        | 33.0  | 1056  | 0.7302          | {'f1': 0.8816521048451151} | {'accuracy': 0.8808} |
| 0.0335        | 34.0  | 1088  | 0.7797          | {'f1': 0.8712709440130773} | {'accuracy': 0.874}  |
| 0.0335        | 35.0  | 1120  | 0.8001          | {'f1': 0.8726530612244897} | {'accuracy': 0.8752} |
| 0.0335        | 36.0  | 1152  | 0.7963          | {'f1': 0.8738411930673115} | {'accuracy': 0.8748} |
| 0.0335        | 37.0  | 1184  | 0.8263          | {'f1': 0.8765762323270919} | {'accuracy': 0.8708} |
| 0.0335        | 38.0  | 1216  | 0.8035          | {'f1': 0.8827258320126782} | {'accuracy': 0.8816} |
| 0.0335        | 39.0  | 1248  | 0.8680          | {'f1': 0.8734020618556702} | {'accuracy': 0.8772} |
| 0.0335        | 40.0  | 1280  | 0.8244          | {'f1': 0.8771371769383697} | {'accuracy': 0.8764} |
| 0.0335        | 41.0  | 1312  | 0.8517          | {'f1': 0.8748977923139819} | {'accuracy': 0.8776} |
| 0.0335        | 42.0  | 1344  | 0.8202          | {'f1': 0.8817034700315458} | {'accuracy': 0.88}   |
| 0.0335        | 43.0  | 1376  | 0.8370          | {'f1': 0.8735909822866345} | {'accuracy': 0.8744} |
| 0.0335        | 44.0  | 1408  | 0.8726          | {'f1': 0.8699958728848535} | {'accuracy': 0.874}  |
| 0.0335        | 45.0  | 1440  | 0.9942          | {'f1': 0.8514090520922288} | {'accuracy': 0.8608} |
| 0.0335        | 46.0  | 1472  | 0.8527          | {'f1': 0.8821028218013142} | {'accuracy': 0.878}  |
| 0.0067        | 47.0  | 1504  | 0.8594          | {'f1': 0.8831168831168831} | {'accuracy': 0.8812} |
| 0.0067        | 48.0  | 1536  | 0.8859          | {'f1': 0.8751476959432848} | {'accuracy': 0.8732} |
| 0.0067        | 49.0  | 1568  | 0.9008          | {'f1': 0.8705410821643287} | {'accuracy': 0.8708} |
| 0.0067        | 50.0  | 1600  | 1.0122          | {'f1': 0.856060606060606}  | {'accuracy': 0.8632} |
| 0.0067        | 51.0  | 1632  | 1.0199          | {'f1': 0.8560509554140128} | {'accuracy': 0.8644} |
| 0.0067        | 52.0  | 1664  | 0.8915          | {'f1': 0.8775592131674026} | {'accuracy': 0.878}  |
| 0.0067        | 53.0  | 1696  | 0.8944          | {'f1': 0.8781664656212306} | {'accuracy': 0.8788} |
| 0.0067        | 54.0  | 1728  | 0.8983          | {'f1': 0.8772635814889336} | {'accuracy': 0.878}  |
| 0.0067        | 55.0  | 1760  | 0.8887          | {'f1': 0.8765133171912833} | {'accuracy': 0.8776} |
| 0.0067        | 56.0  | 1792  | 0.8827          | {'f1': 0.8813151563753007} | {'accuracy': 0.8816} |
| 0.0067        | 57.0  | 1824  | 0.8847          | {'f1': 0.8813151563753007} | {'accuracy': 0.8816} |
| 0.0067        | 58.0  | 1856  | 0.9177          | {'f1': 0.873469387755102}  | {'accuracy': 0.876}  |
| 0.0067        | 59.0  | 1888  | 0.9794          | {'f1': 0.8687370600414078} | {'accuracy': 0.8732} |
| 0.0067        | 60.0  | 1920  | 0.9186          | {'f1': 0.8826550770446463} | {'accuracy': 0.8812} |
| 0.0067        | 61.0  | 1952  | 0.9259          | {'f1': 0.8793440062475596} | {'accuracy': 0.8764} |
| 0.0067        | 62.0  | 1984  | 0.9303          | {'f1': 0.8809338521400777} | {'accuracy': 0.8776} |
| 0.0019        | 63.0  | 2016  | 0.9508          | {'f1': 0.8805799313239222} | {'accuracy': 0.8748} |
| 0.0019        | 64.0  | 2048  | 0.9179          | {'f1': 0.8887165568049632} | {'accuracy': 0.8852} |
| 0.0019        | 65.0  | 2080  | 0.9498          | {'f1': 0.879219194794632}  | {'accuracy': 0.8812} |
| 0.0019        | 66.0  | 2112  | 0.9239          | {'f1': 0.8827374086889658} | {'accuracy': 0.878}  |
| 0.0019        | 67.0  | 2144  | 0.9988          | {'f1': 0.875558867362146}  | {'accuracy': 0.8664} |
| 0.0019        | 68.0  | 2176  | 1.0901          | {'f1': 0.8585944115156647} | {'accuracy': 0.8664} |
| 0.0019        | 69.0  | 2208  | 1.2280          | {'f1': 0.8389349628982977} | {'accuracy': 0.8524} |
| 0.0019        | 70.0  | 2240  | 0.9945          | {'f1': 0.8655357881671494} | {'accuracy': 0.87}   |
| 0.0019        | 71.0  | 2272  | 1.1583          | {'f1': 0.850752688172043}  | {'accuracy': 0.8612} |
| 0.0019        | 72.0  | 2304  | 0.9407          | {'f1': 0.8785197103781175} | {'accuracy': 0.8792} |
| 0.0019        | 73.0  | 2336  | 0.9479          | {'f1': 0.884113584036838}  | {'accuracy': 0.8792} |
| 0.0019        | 74.0  | 2368  | 0.9388          | {'f1': 0.8819334389857368} | {'accuracy': 0.8808} |
| 0.0019        | 75.0  | 2400  | 0.9555          | {'f1': 0.8748500599760095} | {'accuracy': 0.8748} |
| 0.0019        | 76.0  | 2432  | 1.0311          | {'f1': 0.865424430641822}  | {'accuracy': 0.87}   |
| 0.0019        | 77.0  | 2464  | 1.0358          | {'f1': 0.8749530604581299} | {'accuracy': 0.8668} |
| 0.0019        | 78.0  | 2496  | 0.9811          | {'f1': 0.8757062146892655} | {'accuracy': 0.8768} |
| 0.0038        | 79.0  | 2528  | 0.9731          | {'f1': 0.877207062600321}  | {'accuracy': 0.8776} |
| 0.0038        | 80.0  | 2560  | 1.1528          | {'f1': 0.8681318681318682} | {'accuracy': 0.856}  |
| 0.0038        | 81.0  | 2592  | 0.9636          | {'f1': 0.8753529649052039} | {'accuracy': 0.8764} |
| 0.0038        | 82.0  | 2624  | 1.0047          | {'f1': 0.8793950850661625} | {'accuracy': 0.8724} |
| 0.0038        | 83.0  | 2656  | 1.0107          | {'f1': 0.8737704918032787} | {'accuracy': 0.8768} |
| 0.0038        | 84.0  | 2688  | 1.0927          | {'f1': 0.87247335538405}   | {'accuracy': 0.8612} |
| 0.0038        | 85.0  | 2720  | 0.9591          | {'f1': 0.8860759493670884} | {'accuracy': 0.8848} |
| 0.0038        | 86.0  | 2752  | 1.1233          | {'f1': 0.864955826672276}  | {'accuracy': 0.8716} |
| 0.0038        | 87.0  | 2784  | 0.9808          | {'f1': 0.8857938718662952} | {'accuracy': 0.8852} |
| 0.0038        | 88.0  | 2816  | 0.9947          | {'f1': 0.88420245398773}   | {'accuracy': 0.8792} |
| 0.0038        | 89.0  | 2848  | 0.9814          | {'f1': 0.8777327935222672} | {'accuracy': 0.8792} |
| 0.0038        | 90.0  | 2880  | 0.9825          | {'f1': 0.8871775125144398} | {'accuracy': 0.8828} |
| 0.0038        | 91.0  | 2912  | 0.9671          | {'f1': 0.886976926085256}  | {'accuracy': 0.8844} |
| 0.0038        | 92.0  | 2944  | 0.9660          | {'f1': 0.8859166011014948} | {'accuracy': 0.884}  |
| 0.0038        | 93.0  | 2976  | 0.9681          | {'f1': 0.8855564325177585} | {'accuracy': 0.884}  |
| 0.0054        | 94.0  | 3008  | 0.9698          | {'f1': 0.8866222047861907} | {'accuracy': 0.8844} |
| 0.0054        | 95.0  | 3040  | 0.9718          | {'f1': 0.8871473354231975} | {'accuracy': 0.8848} |
| 0.0054        | 96.0  | 3072  | 0.9721          | {'f1': 0.8867110936887496} | {'accuracy': 0.8844} |
| 0.0054        | 97.0  | 3104  | 1.0211          | {'f1': 0.8853333333333333} | {'accuracy': 0.8796} |
| 0.0054        | 98.0  | 3136  | 0.9764          | {'f1': 0.8861756597085467} | {'accuracy': 0.8844} |
| 0.0054        | 99.0  | 3168  | 0.9777          | {'f1': 0.8847524752475247} | {'accuracy': 0.8836} |
| 0.0054        | 100.0 | 3200  | 1.1425          | {'f1': 0.8621997471554993} | {'accuracy': 0.8692} |
| 0.0054        | 101.0 | 3232  | 1.2408          | {'f1': 0.8535745047372953} | {'accuracy': 0.864}  |
| 0.0054        | 102.0 | 3264  | 0.9696          | {'f1': 0.8812749003984064} | {'accuracy': 0.8808} |
| 0.0054        | 103.0 | 3296  | 0.9785          | {'f1': 0.8848106208512301} | {'accuracy': 0.882}  |
| 0.0054        | 104.0 | 3328  | 0.9845          | {'f1': 0.8816521048451151} | {'accuracy': 0.8808} |
| 0.0054        | 105.0 | 3360  | 0.9848          | {'f1': 0.8817460317460318} | {'accuracy': 0.8808} |
| 0.0054        | 106.0 | 3392  | 0.9853          | {'f1': 0.8819334389857368} | {'accuracy': 0.8808} |
| 0.0054        | 107.0 | 3424  | 0.9945          | {'f1': 0.8828468612554978} | {'accuracy': 0.8828} |
| 0.0054        | 108.0 | 3456  | 0.9833          | {'f1': 0.8891500195848022} | {'accuracy': 0.8868} |
| 0.0054        | 109.0 | 3488  | 0.9872          | {'f1': 0.8904428904428903} | {'accuracy': 0.8872} |
| 0.004         | 110.0 | 3520  | 1.0961          | {'f1': 0.8714168714168714} | {'accuracy': 0.8744} |
| 0.004         | 111.0 | 3552  | 1.0768          | {'f1': 0.8778073848496383} | {'accuracy': 0.8716} |
| 0.004         | 112.0 | 3584  | 1.0828          | {'f1': 0.8754234098607452} | {'accuracy': 0.8676} |
| 0.004         | 113.0 | 3616  | 0.9793          | {'f1': 0.8854368932038834} | {'accuracy': 0.882}  |
| 0.004         | 114.0 | 3648  | 1.3126          | {'f1': 0.8445798868088812} | {'accuracy': 0.8572} |
| 0.004         | 115.0 | 3680  | 1.0056          | {'f1': 0.8866615265998459} | {'accuracy': 0.8824} |
| 0.004         | 116.0 | 3712  | 0.9960          | {'f1': 0.887229862475442}  | {'accuracy': 0.8852} |
| 0.004         | 117.0 | 3744  | 1.0465          | {'f1': 0.885681731864793}  | {'accuracy': 0.8796} |
| 0.004         | 118.0 | 3776  | 1.1502          | {'f1': 0.8644781144781145} | {'accuracy': 0.8712} |
| 0.004         | 119.0 | 3808  | 1.0003          | {'f1': 0.8858846918489065} | {'accuracy': 0.8852} |
| 0.004         | 120.0 | 3840  | 1.0303          | {'f1': 0.876979293544458}  | {'accuracy': 0.8788} |
| 0.004         | 121.0 | 3872  | 1.0281          | {'f1': 0.8781869688385269} | {'accuracy': 0.8796} |
| 0.004         | 122.0 | 3904  | 1.0240          | {'f1': 0.88}               | {'accuracy': 0.8812} |
| 0.004         | 123.0 | 3936  | 1.0234          | {'f1': 0.8804523424878836} | {'accuracy': 0.8816} |
| 0.004         | 124.0 | 3968  | 1.0203          | {'f1': 0.8815471394037065} | {'accuracy': 0.8824} |
| 0.007         | 125.0 | 4000  | 1.0133          | {'f1': 0.882803060813532}  | {'accuracy': 0.8836} |
| 0.007         | 126.0 | 4032  | 1.0361          | {'f1': 0.8794788273615635} | {'accuracy': 0.8816} |
| 0.007         | 127.0 | 4064  | 1.0037          | {'f1': 0.8832933653077539} | {'accuracy': 0.8832} |
| 0.007         | 128.0 | 4096  | 1.0028          | {'f1': 0.8833865814696485} | {'accuracy': 0.8832} |
| 0.007         | 129.0 | 4128  | 1.0397          | {'f1': 0.8788617886178862} | {'accuracy': 0.8808} |
| 0.007         | 130.0 | 4160  | 1.0992          | {'f1': 0.8769855929072775} | {'accuracy': 0.8668} |
| 0.007         | 131.0 | 4192  | 0.9497          | {'f1': 0.8808578236695789} | {'accuracy': 0.88}   |
| 0.007         | 132.0 | 4224  | 0.9535          | {'f1': 0.8804780876494025} | {'accuracy': 0.88}   |
| 0.007         | 133.0 | 4256  | 1.0237          | {'f1': 0.8838612368024134} | {'accuracy': 0.8768} |
| 0.007         | 134.0 | 4288  | 1.2089          | {'f1': 0.8522188711762171} | {'accuracy': 0.8628} |
| 0.007         | 135.0 | 4320  | 0.9913          | {'f1': 0.8774767488879902} | {'accuracy': 0.8788} |
| 0.007         | 136.0 | 4352  | 0.9646          | {'f1': 0.8876625936145053} | {'accuracy': 0.886}  |
| 0.007         | 137.0 | 4384  | 0.9656          | {'f1': 0.8866141732283465} | {'accuracy': 0.8848} |
| 0.007         | 138.0 | 4416  | 0.9670          | {'f1': 0.8869633714060654} | {'accuracy': 0.8852} |
| 0.007         | 139.0 | 4448  | 0.9681          | {'f1': 0.8869633714060654} | {'accuracy': 0.8852} |
| 0.007         | 140.0 | 4480  | 0.9745          | {'f1': 0.8869496231654106} | {'accuracy': 0.886}  |
| 0.0028        | 141.0 | 4512  | 0.9768          | {'f1': 0.8851807707588399} | {'accuracy': 0.8844} |
| 0.0028        | 142.0 | 4544  | 0.9775          | {'f1': 0.8860658991663358} | {'accuracy': 0.8852} |
| 0.0028        | 143.0 | 4576  | 0.9785          | {'f1': 0.8869496231654106} | {'accuracy': 0.886}  |
| 0.0028        | 144.0 | 4608  | 0.9795          | {'f1': 0.8869496231654106} | {'accuracy': 0.886}  |
| 0.0028        | 145.0 | 4640  | 0.9802          | {'f1': 0.8869496231654106} | {'accuracy': 0.886}  |
| 0.0028        | 146.0 | 4672  | 0.9811          | {'f1': 0.8865979381443299} | {'accuracy': 0.8856} |
| 0.0028        | 147.0 | 4704  | 0.9823          | {'f1': 0.8865979381443299} | {'accuracy': 0.8856} |
| 0.0028        | 148.0 | 4736  | 0.9842          | {'f1': 0.8865079365079365} | {'accuracy': 0.8856} |
| 0.0028        | 149.0 | 4768  | 0.9873          | {'f1': 0.8851807707588399} | {'accuracy': 0.8844} |
| 0.0028        | 150.0 | 4800  | 0.9911          | {'f1': 0.8836653386454183} | {'accuracy': 0.8832} |
| 0.0028        | 151.0 | 4832  | 0.9916          | {'f1': 0.8829617834394905} | {'accuracy': 0.8824} |
| 0.0028        | 152.0 | 4864  | 0.9920          | {'f1': 0.8829617834394905} | {'accuracy': 0.8824} |
| 0.0028        | 153.0 | 4896  | 0.9926          | {'f1': 0.8842942345924454} | {'accuracy': 0.8836} |
| 0.0028        | 154.0 | 4928  | 0.9929          | {'f1': 0.8851807707588399} | {'accuracy': 0.8844} |
| 0.0028        | 155.0 | 4960  | 0.9933          | {'f1': 0.8851807707588399} | {'accuracy': 0.8844} |
| 0.0028        | 156.0 | 4992  | 1.3663          | {'f1': 0.8461873638344227} | {'accuracy': 0.8588} |
| 0.0           | 157.0 | 5024  | 1.0619          | {'f1': 0.879219194794632}  | {'accuracy': 0.8812} |
| 0.0           | 158.0 | 5056  | 1.0303          | {'f1': 0.888803680981595}  | {'accuracy': 0.884}  |
| 0.0           | 159.0 | 5088  | 1.1667          | {'f1': 0.8680994521702485} | {'accuracy': 0.8748} |
| 0.0           | 160.0 | 5120  | 1.0939          | {'f1': 0.874074074074074}  | {'accuracy': 0.8776} |
| 0.0           | 161.0 | 5152  | 1.0803          | {'f1': 0.8746427113107391} | {'accuracy': 0.8772} |
| 0.0           | 162.0 | 5184  | 1.0660          | {'f1': 0.876979293544458}  | {'accuracy': 0.8788} |
| 0.0           | 163.0 | 5216  | 1.0580          | {'f1': 0.8794498381877023} | {'accuracy': 0.8808} |
| 0.0           | 164.0 | 5248  | 1.0544          | {'f1': 0.8808578236695789} | {'accuracy': 0.88}   |
| 0.0           | 165.0 | 5280  | 1.0617          | {'f1': 0.8809523809523809} | {'accuracy': 0.88}   |
| 0.0           | 166.0 | 5312  | 1.0701          | {'f1': 0.8790419161676648} | {'accuracy': 0.8788} |
| 0.0           | 167.0 | 5344  | 1.0888          | {'f1': 0.8773204196933011} | {'accuracy': 0.8784} |
| 0.0           | 168.0 | 5376  | 1.1879          | {'f1': 0.8666107382550337} | {'accuracy': 0.8728} |
| 0.0           | 169.0 | 5408  | 1.1651          | {'f1': 0.8685524126455907} | {'accuracy': 0.8736} |
| 0.0           | 170.0 | 5440  | 1.1967          | {'f1': 0.8771407297096053} | {'accuracy': 0.868}  |
| 0.0           | 171.0 | 5472  | 1.1247          | {'f1': 0.8737623762376238} | {'accuracy': 0.8776} |
| 0.0018        | 172.0 | 5504  | 1.0690          | {'f1': 0.8882875918051798} | {'accuracy': 0.8844} |
| 0.0018        | 173.0 | 5536  | 1.1525          | {'f1': 0.8836158192090395} | {'accuracy': 0.8764} |
| 0.0018        | 174.0 | 5568  | 1.1367          | {'f1': 0.8857791225416036} | {'accuracy': 0.8792} |
| 0.0018        | 175.0 | 5600  | 1.1446          | {'f1': 0.8738105088953249} | {'accuracy': 0.878}  |
| 0.0018        | 176.0 | 5632  | 1.0122          | {'f1': 0.8882812499999999} | {'accuracy': 0.8856} |
| 0.0018        | 177.0 | 5664  | 1.0805          | {'f1': 0.874384236453202}  | {'accuracy': 0.8776} |
| 0.0018        | 178.0 | 5696  | 1.0170          | {'f1': 0.888631090487239}  | {'accuracy': 0.8848} |
| 0.0018        | 179.0 | 5728  | 1.0286          | {'f1': 0.8874801901743266} | {'accuracy': 0.8864} |
| 0.0018        | 180.0 | 5760  | 1.0230          | {'f1': 0.8895027624309392} | {'accuracy': 0.888}  |
| 0.0018        | 181.0 | 5792  | 1.0283          | {'f1': 0.8887128712871286} | {'accuracy': 0.8876} |
| 0.0018        | 182.0 | 5824  | 1.0507          | {'f1': 0.8824476650563606} | {'accuracy': 0.8832} |
| 0.0018        | 183.0 | 5856  | 1.0512          | {'f1': 0.8824476650563606} | {'accuracy': 0.8832} |
| 0.0018        | 184.0 | 5888  | 1.0517          | {'f1': 0.8825422365245374} | {'accuracy': 0.8832} |
| 0.0018        | 185.0 | 5920  | 1.0522          | {'f1': 0.8825422365245374} | {'accuracy': 0.8832} |
| 0.0018        | 186.0 | 5952  | 1.0522          | {'f1': 0.8826366559485529} | {'accuracy': 0.8832} |
| 0.0018        | 187.0 | 5984  | 1.0521          | {'f1': 0.8828250401284109} | {'accuracy': 0.8832} |
| 0.0078        | 188.0 | 6016  | 1.0524          | {'f1': 0.8821170809943865} | {'accuracy': 0.8824} |
| 0.0078        | 189.0 | 6048  | 1.1665          | {'f1': 0.8748430305567183} | {'accuracy': 0.8804} |
| 0.0078        | 190.0 | 6080  | 1.0072          | {'f1': 0.8893234258897145} | {'accuracy': 0.8868} |
| 0.0078        | 191.0 | 6112  | 1.1264          | {'f1': 0.8772652388797365} | {'accuracy': 0.8808} |
| 0.0078        | 192.0 | 6144  | 1.0573          | {'f1': 0.8888888888888888} | {'accuracy': 0.886}  |
| 0.0078        | 193.0 | 6176  | 1.2255          | {'f1': 0.8725449226911827} | {'accuracy': 0.878}  |
| 0.0078        | 194.0 | 6208  | 1.1498          | {'f1': 0.8796366389099167} | {'accuracy': 0.8728} |
| 0.0078        | 195.0 | 6240  | 1.0907          | {'f1': 0.8875878220140515} | {'accuracy': 0.8848} |
| 0.0078        | 196.0 | 6272  | 1.0891          | {'f1': 0.8867924528301887} | {'accuracy': 0.8848} |
| 0.0078        | 197.0 | 6304  | 1.0897          | {'f1': 0.8871411718442783} | {'accuracy': 0.8852} |
| 0.0078        | 198.0 | 6336  | 1.0911          | {'f1': 0.8858375833660258} | {'accuracy': 0.8836} |
| 0.0078        | 199.0 | 6368  | 1.0925          | {'f1': 0.8865414710485133} | {'accuracy': 0.884}  |
| 0.0078        | 200.0 | 6400  | 1.0929          | {'f1': 0.8858375833660258} | {'accuracy': 0.8836} |
| 0.0078        | 201.0 | 6432  | 1.1341          | {'f1': 0.8781478472786353} | {'accuracy': 0.88}   |
| 0.0078        | 202.0 | 6464  | 1.0999          | {'f1': 0.8904483430799219} | {'accuracy': 0.8876} |
| 0.0078        | 203.0 | 6496  | 1.1062          | {'f1': 0.8888027896164277} | {'accuracy': 0.8852} |
| 0.0005        | 204.0 | 6528  | 1.1030          | {'f1': 0.888975762314308}  | {'accuracy': 0.8864} |
| 0.0005        | 205.0 | 6560  | 1.7304          | {'f1': 0.8167492120666365} | {'accuracy': 0.8372} |
| 0.0005        | 206.0 | 6592  | 1.2413          | {'f1': 0.8805637982195845} | {'accuracy': 0.8712} |
| 0.0005        | 207.0 | 6624  | 1.4884          | {'f1': 0.846288209606987}  | {'accuracy': 0.8592} |
| 0.0005        | 208.0 | 6656  | 1.3248          | {'f1': 0.864176570458404}  | {'accuracy': 0.872}  |
| 0.0005        | 209.0 | 6688  | 1.2540          | {'f1': 0.8740058601925491} | {'accuracy': 0.8796} |
| 0.0005        | 210.0 | 6720  | 1.2431          | {'f1': 0.8738512949039265} | {'accuracy': 0.8792} |
| 0.0005        | 211.0 | 6752  | 1.1901          | {'f1': 0.876904075751338}  | {'accuracy': 0.8804} |
| 0.0005        | 212.0 | 6784  | 1.1800          | {'f1': 0.8783285538713642} | {'accuracy': 0.8812} |
| 0.0005        | 213.0 | 6816  | 1.1750          | {'f1': 0.8780687397708675} | {'accuracy': 0.8808} |
| 0.0005        | 214.0 | 6848  | 1.1727          | {'f1': 0.878267973856209}  | {'accuracy': 0.8808} |
| 0.0005        | 215.0 | 6880  | 1.1681          | {'f1': 0.8788249694002447} | {'accuracy': 0.8812} |
| 0.0005        | 216.0 | 6912  | 1.1765          | {'f1': 0.88}               | {'accuracy': 0.874}  |
| 0.0005        | 217.0 | 6944  | 1.3407          | {'f1': 0.8631756756756757} | {'accuracy': 0.8704} |
| 0.0005        | 218.0 | 6976  | 1.4356          | {'f1': 0.8650018096272167} | {'accuracy': 0.8508} |
| 0.0009        | 219.0 | 7008  | 1.4440          | {'f1': 0.8549356223175966} | {'accuracy': 0.8648} |
| 0.0009        | 220.0 | 7040  | 1.2496          | {'f1': 0.8812448812448812} | {'accuracy': 0.884}  |
| 0.0009        | 221.0 | 7072  | 1.3283          | {'f1': 0.8739076154806491} | {'accuracy': 0.8788} |
| 0.0009        | 222.0 | 7104  | 1.4234          | {'f1': 0.8731370410759725} | {'accuracy': 0.8604} |
| 0.0009        | 223.0 | 7136  | 1.3118          | {'f1': 0.87474162877222}   | {'accuracy': 0.8788} |
| 0.0009        | 224.0 | 7168  | 1.4137          | {'f1': 0.8634064080944351} | {'accuracy': 0.8704} |
| 0.0009        | 225.0 | 7200  | 1.3351          | {'f1': 0.8811292719167905} | {'accuracy': 0.872}  |
| 0.0009        | 226.0 | 7232  | 1.1947          | {'f1': 0.887003470883147}  | {'accuracy': 0.8828} |
| 0.0009        | 227.0 | 7264  | 1.2201          | {'f1': 0.8854961832061068} | {'accuracy': 0.886}  |
| 0.0009        | 228.0 | 7296  | 1.2129          | {'f1': 0.8857715430861725} | {'accuracy': 0.886}  |
| 0.0009        | 229.0 | 7328  | 1.2047          | {'f1': 0.8876494023904382} | {'accuracy': 0.8872} |
| 0.0009        | 230.0 | 7360  | 1.2003          | {'f1': 0.8882958444529165} | {'accuracy': 0.8828} |
| 0.0009        | 231.0 | 7392  | 1.2151          | {'f1': 0.876689881196231}  | {'accuracy': 0.8796} |
| 0.0009        | 232.0 | 7424  | 1.2241          | {'f1': 0.8760262725779967} | {'accuracy': 0.8792} |
| 0.0009        | 233.0 | 7456  | 1.2242          | {'f1': 0.8756668034468609} | {'accuracy': 0.8788} |
| 0.0009        | 234.0 | 7488  | 1.1810          | {'f1': 0.8898370830100852} | {'accuracy': 0.8864} |
| 0.0023        | 235.0 | 7520  | 1.2169          | {'f1': 0.8829190056134724} | {'accuracy': 0.8832} |
| 0.0023        | 236.0 | 7552  | 1.2205          | {'f1': 0.8826366559485529} | {'accuracy': 0.8832} |
| 0.0023        | 237.0 | 7584  | 1.2187          | {'f1': 0.8828250401284109} | {'accuracy': 0.8832} |
| 0.0023        | 238.0 | 7616  | 1.2189          | {'f1': 0.8828250401284109} | {'accuracy': 0.8832} |
| 0.0023        | 239.0 | 7648  | 1.2188          | {'f1': 0.8832731648616126} | {'accuracy': 0.8836} |
| 0.0023        | 240.0 | 7680  | 1.2202          | {'f1': 0.8827309236947791} | {'accuracy': 0.8832} |
| 0.0023        | 241.0 | 7712  | 1.2204          | {'f1': 0.8827309236947791} | {'accuracy': 0.8832} |
| 0.0023        | 242.0 | 7744  | 1.2205          | {'f1': 0.8827309236947791} | {'accuracy': 0.8832} |
| 0.0023        | 243.0 | 7776  | 1.2547          | {'f1': 0.8872919818456882} | {'accuracy': 0.8808} |
| 0.0023        | 244.0 | 7808  | 1.3307          | {'f1': 0.8742216687422167} | {'accuracy': 0.8788} |
| 0.0023        | 245.0 | 7840  | 1.1926          | {'f1': 0.8924731182795698} | {'accuracy': 0.888}  |
| 0.0023        | 246.0 | 7872  | 1.2151          | {'f1': 0.8898208158597025} | {'accuracy': 0.8844} |
| 0.0023        | 247.0 | 7904  | 1.2105          | {'f1': 0.8907563025210083} | {'accuracy': 0.8856} |
| 0.0023        | 248.0 | 7936  | 1.2051          | {'f1': 0.8905053598774885} | {'accuracy': 0.8856} |
| 0.0023        | 249.0 | 7968  | 1.1982          | {'f1': 0.8928982725527831} | {'accuracy': 0.8884} |
| 0.0001        | 250.0 | 8000  | 1.1941          | {'f1': 0.89119569396386}   | {'accuracy': 0.8868} |
| 0.0001        | 251.0 | 8032  | 1.1925          | {'f1': 0.8914549653579676} | {'accuracy': 0.8872} |
| 0.0001        | 252.0 | 8064  | 1.1918          | {'f1': 0.8913713405238829} | {'accuracy': 0.8872} |
| 0.0001        | 253.0 | 8096  | 1.1918          | {'f1': 0.8913713405238829} | {'accuracy': 0.8872} |
| 0.0001        | 254.0 | 8128  | 1.1912          | {'f1': 0.8908600077130737} | {'accuracy': 0.8868} |
| 0.0001        | 255.0 | 8160  | 1.1887          | {'f1': 0.8912959381044487} | {'accuracy': 0.8876} |
| 0.0001        | 256.0 | 8192  | 1.1865          | {'f1': 0.8906976744186046} | {'accuracy': 0.8872} |
| 0.0001        | 257.0 | 8224  | 1.1863          | {'f1': 0.8910430399379605} | {'accuracy': 0.8876} |
| 0.0001        | 258.0 | 8256  | 1.1863          | {'f1': 0.8910430399379605} | {'accuracy': 0.8876} |
| 0.0001        | 259.0 | 8288  | 1.1802          | {'f1': 0.892018779342723}  | {'accuracy': 0.8896} |
| 0.0001        | 260.0 | 8320  | 1.1802          | {'f1': 0.8934169278996866} | {'accuracy': 0.8912} |
| 0.0001        | 261.0 | 8352  | 1.1805          | {'f1': 0.8934169278996866} | {'accuracy': 0.8912} |
| 0.0001        | 262.0 | 8384  | 1.4889          | {'f1': 0.8654173764906302} | {'accuracy': 0.8736} |
| 0.0001        | 263.0 | 8416  | 1.3746          | {'f1': 0.8706968933669186} | {'accuracy': 0.8768} |
| 0.0001        | 264.0 | 8448  | 1.3063          | {'f1': 0.8736013261500206} | {'accuracy': 0.878}  |
| 0.0001        | 265.0 | 8480  | 1.2974          | {'f1': 0.8760330578512396} | {'accuracy': 0.88}   |
| 0.0001        | 266.0 | 8512  | 1.2960          | {'f1': 0.8760330578512396} | {'accuracy': 0.88}   |
| 0.0001        | 267.0 | 8544  | 1.2942          | {'f1': 0.8761354252683732} | {'accuracy': 0.88}   |
| 0.0001        | 268.0 | 8576  | 1.2919          | {'f1': 0.876802637000412}  | {'accuracy': 0.8804} |
| 0.0001        | 269.0 | 8608  | 1.2435          | {'f1': 0.8825680617635107} | {'accuracy': 0.8844} |
| 0.0001        | 270.0 | 8640  | 1.2408          | {'f1': 0.8824006488240065} | {'accuracy': 0.884}  |
| 0.0001        | 271.0 | 8672  | 1.2407          | {'f1': 0.8824006488240065} | {'accuracy': 0.884}  |
| 0.0001        | 272.0 | 8704  | 1.2394          | {'f1': 0.8824959481361425} | {'accuracy': 0.884}  |
| 0.0001        | 273.0 | 8736  | 1.2387          | {'f1': 0.8838526912181304} | {'accuracy': 0.8852} |
| 0.0001        | 274.0 | 8768  | 1.2384          | {'f1': 0.883495145631068}  | {'accuracy': 0.8848} |
| 0.0001        | 275.0 | 8800  | 1.2383          | {'f1': 0.8831378892033966} | {'accuracy': 0.8844} |
| 0.0001        | 276.0 | 8832  | 1.2382          | {'f1': 0.8827809215844786} | {'accuracy': 0.884}  |
| 0.0001        | 277.0 | 8864  | 1.2375          | {'f1': 0.8824242424242424} | {'accuracy': 0.8836} |
| 0.0001        | 278.0 | 8896  | 1.2368          | {'f1': 0.8820678513731826} | {'accuracy': 0.8832} |
| 0.0001        | 279.0 | 8928  | 1.2367          | {'f1': 0.8820678513731826} | {'accuracy': 0.8832} |
| 0.0001        | 280.0 | 8960  | 1.2362          | {'f1': 0.8820678513731826} | {'accuracy': 0.8832} |
| 0.0001        | 281.0 | 8992  | 1.2360          | {'f1': 0.8825191764230925} | {'accuracy': 0.8836} |
| 0.0           | 282.0 | 9024  | 1.2358          | {'f1': 0.8825191764230925} | {'accuracy': 0.8836} |
| 0.0           | 283.0 | 9056  | 1.2355          | {'f1': 0.8825191764230925} | {'accuracy': 0.8836} |
| 0.0           | 284.0 | 9088  | 1.2352          | {'f1': 0.8825191764230925} | {'accuracy': 0.8836} |
| 0.0           | 285.0 | 9120  | 1.2351          | {'f1': 0.881807180314643}  | {'accuracy': 0.8828} |
| 0.0           | 286.0 | 9152  | 1.1996          | {'f1': 0.8912959381044487} | {'accuracy': 0.8876} |
| 0.0           | 287.0 | 9184  | 1.2033          | {'f1': 0.8910355486862442} | {'accuracy': 0.8872} |
| 0.0           | 288.0 | 9216  | 1.2026          | {'f1': 0.8910355486862442} | {'accuracy': 0.8872} |
| 0.0           | 289.0 | 9248  | 1.2024          | {'f1': 0.8910355486862442} | {'accuracy': 0.8872} |
| 0.0           | 290.0 | 9280  | 1.2008          | {'f1': 0.8908668730650156} | {'accuracy': 0.8872} |
| 0.0           | 291.0 | 9312  | 1.1950          | {'f1': 0.8930523028883685} | {'accuracy': 0.8904} |
| 0.0           | 292.0 | 9344  | 1.1950          | {'f1': 0.8930523028883685} | {'accuracy': 0.8904} |
| 0.0           | 293.0 | 9376  | 1.1952          | {'f1': 0.8930523028883685} | {'accuracy': 0.8904} |
| 0.0           | 294.0 | 9408  | 1.1954          | {'f1': 0.8930523028883685} | {'accuracy': 0.8904} |
| 0.0           | 295.0 | 9440  | 1.1955          | {'f1': 0.8930523028883685} | {'accuracy': 0.8904} |
| 0.0           | 296.0 | 9472  | 1.1957          | {'f1': 0.8926200702850448} | {'accuracy': 0.89}   |
| 0.0           | 297.0 | 9504  | 1.1957          | {'f1': 0.8913213448006255} | {'accuracy': 0.8888} |
| 0.0           | 298.0 | 9536  | 1.1957          | {'f1': 0.890802348336595}  | {'accuracy': 0.8884} |
| 0.0           | 299.0 | 9568  | 1.1959          | {'f1': 0.890802348336595}  | {'accuracy': 0.8884} |
| 0.0           | 300.0 | 9600  | 1.1961          | {'f1': 0.8899334116725421} | {'accuracy': 0.8876} |
| 0.0           | 301.0 | 9632  | 1.1966          | {'f1': 0.8899334116725421} | {'accuracy': 0.8876} |
| 0.0           | 302.0 | 9664  | 1.1969          | {'f1': 0.890282131661442}  | {'accuracy': 0.888}  |
| 0.0           | 303.0 | 9696  | 1.1972          | {'f1': 0.890282131661442}  | {'accuracy': 0.888}  |
| 0.0           | 304.0 | 9728  | 1.1974          | {'f1': 0.890282131661442}  | {'accuracy': 0.888}  |
| 0.0           | 305.0 | 9760  | 1.1976          | {'f1': 0.890282131661442}  | {'accuracy': 0.888}  |
| 0.0           | 306.0 | 9792  | 1.1979          | {'f1': 0.890282131661442}  | {'accuracy': 0.888}  |
| 0.0           | 307.0 | 9824  | 1.1981          | {'f1': 0.890282131661442}  | {'accuracy': 0.888}  |
| 0.0           | 308.0 | 9856  | 1.1982          | {'f1': 0.890282131661442}  | {'accuracy': 0.888}  |
| 0.0           | 309.0 | 9888  | 1.1985          | {'f1': 0.890282131661442}  | {'accuracy': 0.888}  |
| 0.0           | 310.0 | 9920  | 1.1987          | {'f1': 0.890282131661442}  | {'accuracy': 0.888}  |
| 0.0           | 311.0 | 9952  | 1.1989          | {'f1': 0.890282131661442}  | {'accuracy': 0.888}  |
| 0.0           | 312.0 | 9984  | 1.1991          | {'f1': 0.890282131661442}  | {'accuracy': 0.888}  |
| 0.0           | 313.0 | 10016 | 1.1993          | {'f1': 0.890282131661442}  | {'accuracy': 0.888}  |
| 0.0           | 314.0 | 10048 | 1.1997          | {'f1': 0.890282131661442}  | {'accuracy': 0.888}  |
| 0.0           | 315.0 | 10080 | 1.2001          | {'f1': 0.890282131661442}  | {'accuracy': 0.888}  |
| 0.0           | 316.0 | 10112 | 1.2007          | {'f1': 0.8901960784313726} | {'accuracy': 0.888}  |
| 0.0           | 317.0 | 10144 | 1.2010          | {'f1': 0.8901960784313726} | {'accuracy': 0.888}  |
| 0.0           | 318.0 | 10176 | 1.2012          | {'f1': 0.8901960784313726} | {'accuracy': 0.888}  |
| 0.0           | 319.0 | 10208 | 1.2015          | {'f1': 0.8901960784313726} | {'accuracy': 0.888}  |
| 0.0           | 320.0 | 10240 | 1.2044          | {'f1': 0.8902920284135754} | {'accuracy': 0.8888} |
| 0.0           | 321.0 | 10272 | 1.2048          | {'f1': 0.8906435057244373} | {'accuracy': 0.8892} |
| 0.0           | 322.0 | 10304 | 1.2050          | {'f1': 0.8906435057244373} | {'accuracy': 0.8892} |
| 0.0           | 323.0 | 10336 | 1.2051          | {'f1': 0.8902920284135754} | {'accuracy': 0.8888} |
| 0.0           | 324.0 | 10368 | 1.2054          | {'f1': 0.8902920284135754} | {'accuracy': 0.8888} |
| 0.0           | 325.0 | 10400 | 1.2056          | {'f1': 0.8902920284135754} | {'accuracy': 0.8888} |
| 0.0           | 326.0 | 10432 | 1.2059          | {'f1': 0.8902920284135754} | {'accuracy': 0.8888} |
| 0.0           | 327.0 | 10464 | 1.2061          | {'f1': 0.8902920284135754} | {'accuracy': 0.8888} |
| 0.0           | 328.0 | 10496 | 1.2132          | {'f1': 0.8903525765207285} | {'accuracy': 0.8868} |
| 0.0           | 329.0 | 10528 | 1.2158          | {'f1': 0.8908668730650156} | {'accuracy': 0.8872} |
| 0.0           | 330.0 | 10560 | 1.2159          | {'f1': 0.8907823392718822} | {'accuracy': 0.8872} |
| 0.0           | 331.0 | 10592 | 1.2158          | {'f1': 0.8903525765207285} | {'accuracy': 0.8868} |
| 0.0           | 332.0 | 10624 | 1.2158          | {'f1': 0.889922480620155}  | {'accuracy': 0.8864} |
| 0.0           | 333.0 | 10656 | 1.2160          | {'f1': 0.889922480620155}  | {'accuracy': 0.8864} |
| 0.0           | 334.0 | 10688 | 1.2154          | {'f1': 0.8906128782001551} | {'accuracy': 0.8872} |
| 0.0           | 335.0 | 10720 | 1.2152          | {'f1': 0.8909584788513776} | {'accuracy': 0.8876} |
| 0.0           | 336.0 | 10752 | 1.2154          | {'f1': 0.8909584788513776} | {'accuracy': 0.8876} |
| 0.0           | 337.0 | 10784 | 1.2155          | {'f1': 0.8909584788513776} | {'accuracy': 0.8876} |
| 0.0           | 338.0 | 10816 | 1.2156          | {'f1': 0.8909584788513776} | {'accuracy': 0.8876} |
| 0.0           | 339.0 | 10848 | 1.2157          | {'f1': 0.8909584788513776} | {'accuracy': 0.8876} |
| 0.0           | 340.0 | 10880 | 1.2158          | {'f1': 0.8909584788513776} | {'accuracy': 0.8876} |
| 0.0           | 341.0 | 10912 | 1.2159          | {'f1': 0.8909584788513776} | {'accuracy': 0.8876} |
| 0.0           | 342.0 | 10944 | 1.2161          | {'f1': 0.8909584788513776} | {'accuracy': 0.8876} |
| 0.0           | 343.0 | 10976 | 1.2160          | {'f1': 0.8913043478260869} | {'accuracy': 0.888}  |
| 0.0           | 344.0 | 11008 | 1.2149          | {'f1': 0.8906189178668742} | {'accuracy': 0.8876} |
| 0.0           | 345.0 | 11040 | 1.2146          | {'f1': 0.8914910226385637} | {'accuracy': 0.8888} |
| 0.0           | 346.0 | 11072 | 1.2148          | {'f1': 0.8914910226385637} | {'accuracy': 0.8888} |
| 0.0           | 347.0 | 11104 | 1.2151          | {'f1': 0.8914910226385637} | {'accuracy': 0.8888} |
| 0.0           | 348.0 | 11136 | 1.2153          | {'f1': 0.8914910226385637} | {'accuracy': 0.8888} |
| 0.0           | 349.0 | 11168 | 1.2156          | {'f1': 0.8914910226385637} | {'accuracy': 0.8888} |
| 0.0           | 350.0 | 11200 | 1.2159          | {'f1': 0.8914910226385637} | {'accuracy': 0.8888} |
| 0.0           | 351.0 | 11232 | 1.2162          | {'f1': 0.8914910226385637} | {'accuracy': 0.8888} |
| 0.0           | 352.0 | 11264 | 1.2164          | {'f1': 0.8914910226385637} | {'accuracy': 0.8888} |
| 0.0           | 353.0 | 11296 | 1.2167          | {'f1': 0.8914910226385637} | {'accuracy': 0.8888} |
| 0.0           | 354.0 | 11328 | 1.1966          | {'f1': 0.8851164626924596} | {'accuracy': 0.8836} |
| 0.0           | 355.0 | 11360 | 1.2026          | {'f1': 0.8888888888888888} | {'accuracy': 0.8856} |
| 0.0           | 356.0 | 11392 | 1.1992          | {'f1': 0.8900195694716242} | {'accuracy': 0.8876} |
| 0.0           | 357.0 | 11424 | 1.1983          | {'f1': 0.8889760690466848} | {'accuracy': 0.8868} |
| 0.0           | 358.0 | 11456 | 1.1987          | {'f1': 0.8889760690466848} | {'accuracy': 0.8868} |
| 0.0           | 359.0 | 11488 | 1.1991          | {'f1': 0.8889760690466848} | {'accuracy': 0.8868} |
| 0.001         | 360.0 | 11520 | 1.1998          | {'f1': 0.8874901652242329} | {'accuracy': 0.8856} |
| 0.001         | 361.0 | 11552 | 1.2004          | {'f1': 0.887229862475442}  | {'accuracy': 0.8852} |
| 0.001         | 362.0 | 11584 | 1.2008          | {'f1': 0.887229862475442}  | {'accuracy': 0.8852} |
| 0.001         | 363.0 | 11616 | 1.2012          | {'f1': 0.887229862475442}  | {'accuracy': 0.8852} |
| 0.001         | 364.0 | 11648 | 1.2018          | {'f1': 0.887229862475442}  | {'accuracy': 0.8852} |
| 0.001         | 365.0 | 11680 | 1.2027          | {'f1': 0.887229862475442}  | {'accuracy': 0.8852} |
| 0.001         | 366.0 | 11712 | 1.2033          | {'f1': 0.887229862475442}  | {'accuracy': 0.8852} |
| 0.001         | 367.0 | 11744 | 1.2037          | {'f1': 0.887229862475442}  | {'accuracy': 0.8852} |
| 0.001         | 368.0 | 11776 | 1.2040          | {'f1': 0.887229862475442}  | {'accuracy': 0.8852} |
| 0.001         | 369.0 | 11808 | 1.2044          | {'f1': 0.887229862475442}  | {'accuracy': 0.8852} |
| 0.001         | 370.0 | 11840 | 1.2048          | {'f1': 0.887229862475442}  | {'accuracy': 0.8852} |
| 0.001         | 371.0 | 11872 | 1.2052          | {'f1': 0.887229862475442}  | {'accuracy': 0.8852} |
| 0.001         | 372.0 | 11904 | 1.2056          | {'f1': 0.887229862475442}  | {'accuracy': 0.8852} |
| 0.001         | 373.0 | 11936 | 1.2061          | {'f1': 0.887229862475442}  | {'accuracy': 0.8852} |
| 0.001         | 374.0 | 11968 | 1.2067          | {'f1': 0.887229862475442}  | {'accuracy': 0.8852} |
| 0.0           | 375.0 | 12000 | 1.2075          | {'f1': 0.8879276445143532} | {'accuracy': 0.886}  |
| 0.0           | 376.0 | 12032 | 1.2079          | {'f1': 0.8879276445143532} | {'accuracy': 0.886}  |
| 0.0           | 377.0 | 12064 | 1.2084          | {'f1': 0.8875786163522013} | {'accuracy': 0.8856} |
| 0.0           | 378.0 | 12096 | 1.2089          | {'f1': 0.8875786163522013} | {'accuracy': 0.8856} |
| 0.0           | 379.0 | 12128 | 1.2096          | {'f1': 0.8874015748031495} | {'accuracy': 0.8856} |
| 0.0           | 380.0 | 12160 | 1.2126          | {'f1': 0.883960396039604}  | {'accuracy': 0.8828} |
| 0.0           | 381.0 | 12192 | 1.2139          | {'f1': 0.8849206349206349} | {'accuracy': 0.884}  |
| 0.0           | 382.0 | 12224 | 1.2143          | {'f1': 0.8849206349206349} | {'accuracy': 0.884}  |
| 0.0           | 383.0 | 12256 | 1.2147          | {'f1': 0.8849206349206349} | {'accuracy': 0.884}  |
| 0.0           | 384.0 | 12288 | 1.2267          | {'f1': 0.8845385537355175} | {'accuracy': 0.8844} |
| 0.0           | 385.0 | 12320 | 1.2280          | {'f1': 0.8845385537355175} | {'accuracy': 0.8844} |
| 0.0           | 386.0 | 12352 | 1.2274          | {'f1': 0.8845385537355175} | {'accuracy': 0.8844} |
| 0.0           | 387.0 | 12384 | 1.2268          | {'f1': 0.8846307385229542} | {'accuracy': 0.8844} |
| 0.0           | 388.0 | 12416 | 1.2270          | {'f1': 0.8850758180367119} | {'accuracy': 0.8848} |
| 0.0           | 389.0 | 12448 | 1.2541          | {'f1': 0.8848631239935587} | {'accuracy': 0.8856} |
| 0.0           | 390.0 | 12480 | 1.2600          | {'f1': 0.8829701372074253} | {'accuracy': 0.884}  |
| 0.0           | 391.0 | 12512 | 1.2595          | {'f1': 0.8830645161290323} | {'accuracy': 0.884}  |
| 0.0           | 392.0 | 12544 | 1.2595          | {'f1': 0.8830645161290323} | {'accuracy': 0.884}  |
| 0.0           | 393.0 | 12576 | 1.2595          | {'f1': 0.8830645161290323} | {'accuracy': 0.884}  |
| 0.0           | 394.0 | 12608 | 1.2595          | {'f1': 0.8835147118097542} | {'accuracy': 0.8844} |
| 0.0           | 395.0 | 12640 | 1.2595          | {'f1': 0.8839645447219985} | {'accuracy': 0.8848} |
| 0.0           | 396.0 | 12672 | 1.2592          | {'f1': 0.8839645447219985} | {'accuracy': 0.8848} |
| 0.0           | 397.0 | 12704 | 1.2579          | {'f1': 0.8848631239935587} | {'accuracy': 0.8856} |
| 0.0           | 398.0 | 12736 | 1.2578          | {'f1': 0.8845070422535211} | {'accuracy': 0.8852} |
| 0.0           | 399.0 | 12768 | 1.2576          | {'f1': 0.8845070422535211} | {'accuracy': 0.8852} |
| 0.0           | 400.0 | 12800 | 1.2458          | {'f1': 0.8844301765650081} | {'accuracy': 0.8848} |
| 0.0           | 401.0 | 12832 | 1.2442          | {'f1': 0.8838141025641026} | {'accuracy': 0.884}  |
| 0.0           | 402.0 | 12864 | 1.2439          | {'f1': 0.8847077662129704} | {'accuracy': 0.8848} |
| 0.0           | 403.0 | 12896 | 1.2441          | {'f1': 0.8851540616246498} | {'accuracy': 0.8852} |
| 0.0           | 404.0 | 12928 | 1.2443          | {'f1': 0.8851540616246498} | {'accuracy': 0.8852} |
| 0.0           | 405.0 | 12960 | 1.2468          | {'f1': 0.8838141025641026} | {'accuracy': 0.884}  |
| 0.0           | 406.0 | 12992 | 1.2472          | {'f1': 0.8838141025641026} | {'accuracy': 0.884}  |
| 0.0           | 407.0 | 13024 | 1.2473          | {'f1': 0.8842611133360032} | {'accuracy': 0.8844} |
| 0.0           | 408.0 | 13056 | 1.2472          | {'f1': 0.8842611133360032} | {'accuracy': 0.8844} |
| 0.0           | 409.0 | 13088 | 1.2467          | {'f1': 0.8851540616246498} | {'accuracy': 0.8852} |
| 0.0           | 410.0 | 13120 | 1.2465          | {'f1': 0.8851540616246498} | {'accuracy': 0.8852} |
| 0.0           | 411.0 | 13152 | 1.2467          | {'f1': 0.8851540616246498} | {'accuracy': 0.8852} |
| 0.0           | 412.0 | 13184 | 1.2467          | {'f1': 0.8851540616246498} | {'accuracy': 0.8852} |
| 0.0           | 413.0 | 13216 | 1.2468          | {'f1': 0.8851540616246498} | {'accuracy': 0.8852} |
| 0.0           | 414.0 | 13248 | 1.2450          | {'f1': 0.8848920863309353} | {'accuracy': 0.8848} |
| 0.0           | 415.0 | 13280 | 1.2449          | {'f1': 0.8848920863309353} | {'accuracy': 0.8848} |
| 0.0           | 416.0 | 13312 | 1.2451          | {'f1': 0.8848920863309353} | {'accuracy': 0.8848} |
| 0.0           | 417.0 | 13344 | 1.2451          | {'f1': 0.8853375948861366} | {'accuracy': 0.8852} |
| 0.0           | 418.0 | 13376 | 1.2456          | {'f1': 0.8853375948861366} | {'accuracy': 0.8852} |
| 0.0           | 419.0 | 13408 | 1.2460          | {'f1': 0.8853375948861366} | {'accuracy': 0.8852} |
| 0.0           | 420.0 | 13440 | 1.2462          | {'f1': 0.8849840255591055} | {'accuracy': 0.8848} |
| 0.0           | 421.0 | 13472 | 1.2464          | {'f1': 0.8849840255591055} | {'accuracy': 0.8848} |
| 0.0           | 422.0 | 13504 | 1.2457          | {'f1': 0.8859649122807017} | {'accuracy': 0.8856} |
| 0.0           | 423.0 | 13536 | 1.2469          | {'f1': 0.8850758180367119} | {'accuracy': 0.8848} |
| 0.0           | 424.0 | 13568 | 1.2473          | {'f1': 0.8850758180367119} | {'accuracy': 0.8848} |
| 0.0           | 425.0 | 13600 | 1.2476          | {'f1': 0.8850758180367119} | {'accuracy': 0.8848} |
| 0.0           | 426.0 | 13632 | 1.2477          | {'f1': 0.8855205424810532} | {'accuracy': 0.8852} |
| 0.0           | 427.0 | 13664 | 1.2479          | {'f1': 0.8855205424810532} | {'accuracy': 0.8852} |
| 0.0           | 428.0 | 13696 | 1.2480          | {'f1': 0.8859649122807017} | {'accuracy': 0.8856} |
| 0.0           | 429.0 | 13728 | 1.2935          | {'f1': 0.8833063209076175} | {'accuracy': 0.8848} |
| 0.0           | 430.0 | 13760 | 1.3489          | {'f1': 0.8799672265464974} | {'accuracy': 0.8828} |
| 0.0           | 431.0 | 13792 | 1.3497          | {'f1': 0.8799672265464974} | {'accuracy': 0.8828} |
| 0.0           | 432.0 | 13824 | 1.2992          | {'f1': 0.8833063209076175} | {'accuracy': 0.8848} |
| 0.0           | 433.0 | 13856 | 1.2547          | {'f1': 0.8846459824980112} | {'accuracy': 0.884}  |
| 0.0           | 434.0 | 13888 | 1.2543          | {'f1': 0.8859753675009933} | {'accuracy': 0.8852} |
| 0.0           | 435.0 | 13920 | 1.2547          | {'f1': 0.8859753675009933} | {'accuracy': 0.8852} |
| 0.0           | 436.0 | 13952 | 1.2550          | {'f1': 0.8859753675009933} | {'accuracy': 0.8852} |
| 0.0           | 437.0 | 13984 | 1.2554          | {'f1': 0.8859753675009933} | {'accuracy': 0.8852} |
| 0.0           | 438.0 | 14016 | 1.2556          | {'f1': 0.8859753675009933} | {'accuracy': 0.8852} |
| 0.0           | 439.0 | 14048 | 1.2559          | {'f1': 0.8859753675009933} | {'accuracy': 0.8852} |
| 0.0           | 440.0 | 14080 | 1.2562          | {'f1': 0.8856235107227959} | {'accuracy': 0.8848} |
| 0.0           | 441.0 | 14112 | 1.2564          | {'f1': 0.8856235107227959} | {'accuracy': 0.8848} |
| 0.0           | 442.0 | 14144 | 1.2588          | {'f1': 0.8849064117881322} | {'accuracy': 0.8844} |
| 0.0           | 443.0 | 14176 | 1.2605          | {'f1': 0.8852589641434263} | {'accuracy': 0.8848} |
| 0.0           | 444.0 | 14208 | 1.2608          | {'f1': 0.8852589641434263} | {'accuracy': 0.8848} |
| 0.0           | 445.0 | 14240 | 1.2610          | {'f1': 0.8852589641434263} | {'accuracy': 0.8848} |
| 0.0           | 446.0 | 14272 | 1.5715          | {'f1': 0.8583581454700128} | {'accuracy': 0.8668} |
| 0.0           | 447.0 | 14304 | 1.3320          | {'f1': 0.8823768823768823} | {'accuracy': 0.8844} |
| 0.0           | 448.0 | 14336 | 1.3084          | {'f1': 0.8824959481361425} | {'accuracy': 0.884}  |
| 0.0           | 449.0 | 14368 | 1.3075          | {'f1': 0.8834008097165993} | {'accuracy': 0.8848} |
| 0.0           | 450.0 | 14400 | 1.3071          | {'f1': 0.8834008097165993} | {'accuracy': 0.8848} |
| 0.0           | 451.0 | 14432 | 1.3054          | {'f1': 0.8847553578649412} | {'accuracy': 0.886}  |
| 0.0           | 452.0 | 14464 | 1.3053          | {'f1': 0.8847553578649412} | {'accuracy': 0.886}  |
| 0.0           | 453.0 | 14496 | 1.3053          | {'f1': 0.8847553578649412} | {'accuracy': 0.886}  |
| 0.0002        | 454.0 | 14528 | 1.3052          | {'f1': 0.8847553578649412} | {'accuracy': 0.886}  |
| 0.0002        | 455.0 | 14560 | 1.3009          | {'f1': 0.8841340331045618} | {'accuracy': 0.8852} |
| 0.0002        | 456.0 | 14592 | 1.3006          | {'f1': 0.8841340331045618} | {'accuracy': 0.8852} |
| 0.0002        | 457.0 | 14624 | 1.2918          | {'f1': 0.8852194925493353} | {'accuracy': 0.886}  |
| 0.0002        | 458.0 | 14656 | 1.2913          | {'f1': 0.8852194925493353} | {'accuracy': 0.886}  |
| 0.0002        | 459.0 | 14688 | 1.2914          | {'f1': 0.8852194925493353} | {'accuracy': 0.886}  |
| 0.0002        | 460.0 | 14720 | 1.2914          | {'f1': 0.8852194925493353} | {'accuracy': 0.886}  |
| 0.0002        | 461.0 | 14752 | 1.2914          | {'f1': 0.8852194925493353} | {'accuracy': 0.886}  |
| 0.0002        | 462.0 | 14784 | 1.2915          | {'f1': 0.8852194925493353} | {'accuracy': 0.886}  |
| 0.0002        | 463.0 | 14816 | 1.2915          | {'f1': 0.8852194925493353} | {'accuracy': 0.886}  |
| 0.0002        | 464.0 | 14848 | 1.2913          | {'f1': 0.8852194925493353} | {'accuracy': 0.886}  |
| 0.0002        | 465.0 | 14880 | 1.2913          | {'f1': 0.8852194925493353} | {'accuracy': 0.886}  |
| 0.0002        | 466.0 | 14912 | 1.2913          | {'f1': 0.8852194925493353} | {'accuracy': 0.886}  |
| 0.0002        | 467.0 | 14944 | 1.2913          | {'f1': 0.8852194925493353} | {'accuracy': 0.886}  |
| 0.0002        | 468.0 | 14976 | 1.2912          | {'f1': 0.8852194925493353} | {'accuracy': 0.886}  |
| 0.0           | 469.0 | 15008 | 1.2912          | {'f1': 0.8852194925493353} | {'accuracy': 0.886}  |
| 0.0           | 470.0 | 15040 | 1.2911          | {'f1': 0.8852194925493353} | {'accuracy': 0.886}  |
| 0.0           | 471.0 | 15072 | 1.2911          | {'f1': 0.8852194925493353} | {'accuracy': 0.886}  |
| 0.0           | 472.0 | 15104 | 1.2911          | {'f1': 0.8856682769726248} | {'accuracy': 0.8864} |
| 0.0           | 473.0 | 15136 | 1.2912          | {'f1': 0.8856682769726248} | {'accuracy': 0.8864} |
| 0.0           | 474.0 | 15168 | 1.2912          | {'f1': 0.8856682769726248} | {'accuracy': 0.8864} |
| 0.0           | 475.0 | 15200 | 1.2912          | {'f1': 0.8856682769726248} | {'accuracy': 0.8864} |
| 0.0           | 476.0 | 15232 | 1.2893          | {'f1': 0.8853118712273642} | {'accuracy': 0.886}  |
| 0.0           | 477.0 | 15264 | 1.2879          | {'f1': 0.8858520900321544} | {'accuracy': 0.8864} |
| 0.0           | 478.0 | 15296 | 1.2879          | {'f1': 0.8858520900321544} | {'accuracy': 0.8864} |
| 0.0           | 479.0 | 15328 | 1.2879          | {'f1': 0.8858520900321544} | {'accuracy': 0.8864} |
| 0.0           | 480.0 | 15360 | 1.2879          | {'f1': 0.8858520900321544} | {'accuracy': 0.8864} |
| 0.0           | 481.0 | 15392 | 1.2880          | {'f1': 0.8858520900321544} | {'accuracy': 0.8864} |
| 0.0           | 482.0 | 15424 | 1.2881          | {'f1': 0.8858520900321544} | {'accuracy': 0.8864} |
| 0.0           | 483.0 | 15456 | 1.2881          | {'f1': 0.8858520900321544} | {'accuracy': 0.8864} |
| 0.0           | 484.0 | 15488 | 1.2882          | {'f1': 0.8858520900321544} | {'accuracy': 0.8864} |
| 0.0           | 485.0 | 15520 | 1.2882          | {'f1': 0.8858520900321544} | {'accuracy': 0.8864} |
| 0.0           | 486.0 | 15552 | 1.2883          | {'f1': 0.8858520900321544} | {'accuracy': 0.8864} |
| 0.0           | 487.0 | 15584 | 1.2883          | {'f1': 0.8858520900321544} | {'accuracy': 0.8864} |
| 0.0           | 488.0 | 15616 | 1.2882          | {'f1': 0.8858520900321544} | {'accuracy': 0.8864} |
| 0.0           | 489.0 | 15648 | 1.2846          | {'f1': 0.8862179487179487} | {'accuracy': 0.8864} |
| 0.0           | 490.0 | 15680 | 1.2844          | {'f1': 0.8862179487179487} | {'accuracy': 0.8864} |
| 0.0           | 491.0 | 15712 | 1.2845          | {'f1': 0.8862179487179487} | {'accuracy': 0.8864} |
| 0.0           | 492.0 | 15744 | 1.2845          | {'f1': 0.8862179487179487} | {'accuracy': 0.8864} |
| 0.0           | 493.0 | 15776 | 1.2843          | {'f1': 0.8862179487179487} | {'accuracy': 0.8864} |
| 0.0           | 494.0 | 15808 | 1.2844          | {'f1': 0.8862179487179487} | {'accuracy': 0.8864} |
| 0.0           | 495.0 | 15840 | 1.2844          | {'f1': 0.8862179487179487} | {'accuracy': 0.8864} |
| 0.0           | 496.0 | 15872 | 1.2844          | {'f1': 0.8862179487179487} | {'accuracy': 0.8864} |
| 0.0           | 497.0 | 15904 | 1.2844          | {'f1': 0.8862179487179487} | {'accuracy': 0.8864} |
| 0.0           | 498.0 | 15936 | 1.2845          | {'f1': 0.8862179487179487} | {'accuracy': 0.8864} |
| 0.0           | 499.0 | 15968 | 1.2845          | {'f1': 0.8862179487179487} | {'accuracy': 0.8864} |
| 0.0           | 500.0 | 16000 | 1.2845          | {'f1': 0.8862179487179487} | {'accuracy': 0.8864} |


### Framework versions

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