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_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_16_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: 1.2555
- F1: {'f1': 0.8858187728565624}
- Accuracy: {'accuracy': 0.8876}

## 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    | 0.6772          | {'f1': 0.4197396963123644} | {'accuracy': 0.572}  |
| No log        | 2.0   | 64    | 0.6149          | {'f1': 0.6325088339222615} | {'accuracy': 0.6672} |
| No log        | 3.0   | 96    | 0.4616          | {'f1': 0.7809983896940419} | {'accuracy': 0.7824} |
| No log        | 4.0   | 128   | 0.4102          | {'f1': 0.837847866419295}  | {'accuracy': 0.8252} |
| No log        | 5.0   | 160   | 0.3876          | {'f1': 0.8469551282051282} | {'accuracy': 0.8472} |
| No log        | 6.0   | 192   | 0.3908          | {'f1': 0.8325639949643308} | {'accuracy': 0.8404} |
| No log        | 7.0   | 224   | 0.3592          | {'f1': 0.8642638036809817} | {'accuracy': 0.8584} |
| No log        | 8.0   | 256   | 0.3725          | {'f1': 0.8675728155339806} | {'accuracy': 0.8636} |
| No log        | 9.0   | 288   | 0.3765          | {'f1': 0.859775641025641}  | {'accuracy': 0.86}   |
| No log        | 10.0  | 320   | 0.4279          | {'f1': 0.8678267308404295} | {'accuracy': 0.8572} |
| No log        | 11.0  | 352   | 0.4188          | {'f1': 0.8585055643879174} | {'accuracy': 0.8576} |
| No log        | 12.0  | 384   | 0.4489          | {'f1': 0.8583028826634186} | {'accuracy': 0.8604} |
| No log        | 13.0  | 416   | 0.5263          | {'f1': 0.8507209499575912} | {'accuracy': 0.8592} |
| No log        | 14.0  | 448   | 0.4985          | {'f1': 0.8688591149005278} | {'accuracy': 0.8708} |
| No log        | 15.0  | 480   | 0.5142          | {'f1': 0.870710295291301}  | {'accuracy': 0.8704} |
| 0.2771        | 16.0  | 512   | 0.5228          | {'f1': 0.8710325431900362} | {'accuracy': 0.8716} |
| 0.2771        | 17.0  | 544   | 0.5367          | {'f1': 0.87890625}         | {'accuracy': 0.876}  |
| 0.2771        | 18.0  | 576   | 0.5657          | {'f1': 0.8638420403126286} | {'accuracy': 0.8676} |
| 0.2771        | 19.0  | 608   | 0.6005          | {'f1': 0.8697588126159554} | {'accuracy': 0.8596} |
| 0.2771        | 20.0  | 640   | 0.6059          | {'f1': 0.8561900791996665} | {'accuracy': 0.862}  |
| 0.2771        | 21.0  | 672   | 0.5729          | {'f1': 0.8786936236391913} | {'accuracy': 0.8752} |
| 0.2771        | 22.0  | 704   | 0.6494          | {'f1': 0.862111801242236}  | {'accuracy': 0.8668} |
| 0.2771        | 23.0  | 736   | 0.6270          | {'f1': 0.8745490981963927} | {'accuracy': 0.8748} |
| 0.2771        | 24.0  | 768   | 0.6396          | {'f1': 0.8783521181500195} | {'accuracy': 0.8748} |
| 0.2771        | 25.0  | 800   | 0.6909          | {'f1': 0.8643379366368805} | {'accuracy': 0.8664} |
| 0.2771        | 26.0  | 832   | 0.7048          | {'f1': 0.8665048543689321} | {'accuracy': 0.868}  |
| 0.2771        | 27.0  | 864   | 0.8026          | {'f1': 0.8516949152542372} | {'accuracy': 0.86}   |
| 0.2771        | 28.0  | 896   | 0.7183          | {'f1': 0.8744448930157448} | {'accuracy': 0.8756} |
| 0.2771        | 29.0  | 928   | 0.7226          | {'f1': 0.8765581021310815} | {'accuracy': 0.8772} |
| 0.2771        | 30.0  | 960   | 0.7365          | {'f1': 0.8778930566640064} | {'accuracy': 0.8776} |
| 0.2771        | 31.0  | 992   | 0.8903          | {'f1': 0.8518992744344858} | {'accuracy': 0.8612} |
| 0.0305        | 32.0  | 1024  | 0.7611          | {'f1': 0.8783314020857473} | {'accuracy': 0.874}  |
| 0.0305        | 33.0  | 1056  | 0.7911          | {'f1': 0.8707865168539325} | {'accuracy': 0.8712} |
| 0.0305        | 34.0  | 1088  | 0.8785          | {'f1': 0.8579807289484709} | {'accuracy': 0.8644} |
| 0.0305        | 35.0  | 1120  | 0.8127          | {'f1': 0.8705501618122977} | {'accuracy': 0.872}  |
| 0.0305        | 36.0  | 1152  | 0.8361          | {'f1': 0.8663406682966585} | {'accuracy': 0.8688} |
| 0.0305        | 37.0  | 1184  | 0.8104          | {'f1': 0.8793565683646112} | {'accuracy': 0.874}  |
| 0.0305        | 38.0  | 1216  | 0.8189          | {'f1': 0.875993640699523}  | {'accuracy': 0.8752} |
| 0.0305        | 39.0  | 1248  | 0.8209          | {'f1': 0.8819390148553558} | {'accuracy': 0.8792} |
| 0.0305        | 40.0  | 1280  | 0.8555          | {'f1': 0.869951534733441}  | {'accuracy': 0.8712} |
| 0.0305        | 41.0  | 1312  | 0.8538          | {'f1': 0.8732849071832123} | {'accuracy': 0.8744} |
| 0.0305        | 42.0  | 1344  | 0.8486          | {'f1': 0.8809433244579689} | {'accuracy': 0.8748} |
| 0.0305        | 43.0  | 1376  | 0.8763          | {'f1': 0.8746473196291817} | {'accuracy': 0.8756} |
| 0.0305        | 44.0  | 1408  | 0.9639          | {'f1': 0.855090832277144}  | {'accuracy': 0.8628} |
| 0.0305        | 45.0  | 1440  | 0.8495          | {'f1': 0.8760064412238325} | {'accuracy': 0.8768} |
| 0.0305        | 46.0  | 1472  | 0.8497          | {'f1': 0.8831269349845201} | {'accuracy': 0.8792} |
| 0.0078        | 47.0  | 1504  | 0.8562          | {'f1': 0.8769470404984425} | {'accuracy': 0.8736} |
| 0.0078        | 48.0  | 1536  | 0.8552          | {'f1': 0.8782985427333596} | {'accuracy': 0.8764} |
| 0.0078        | 49.0  | 1568  | 0.8558          | {'f1': 0.8799682034976153} | {'accuracy': 0.8792} |
| 0.0078        | 50.0  | 1600  | 0.8696          | {'f1': 0.8746473196291817} | {'accuracy': 0.8756} |
| 0.0078        | 51.0  | 1632  | 0.9342          | {'f1': 0.87173100871731}   | {'accuracy': 0.8764} |
| 0.0078        | 52.0  | 1664  | 0.9011          | {'f1': 0.8756137479541735} | {'accuracy': 0.8784} |
| 0.0078        | 53.0  | 1696  | 0.9044          | {'f1': 0.8776094965206713} | {'accuracy': 0.8804} |
| 0.0078        | 54.0  | 1728  | 0.8767          | {'f1': 0.8836465413834467} | {'accuracy': 0.8836} |
| 0.0078        | 55.0  | 1760  | 0.9982          | {'f1': 0.8648421052631577} | {'accuracy': 0.8716} |
| 0.0078        | 56.0  | 1792  | 0.8801          | {'f1': 0.8829915560916767} | {'accuracy': 0.8836} |
| 0.0078        | 57.0  | 1824  | 0.8925          | {'f1': 0.8877862595419846} | {'accuracy': 0.8824} |
| 0.0078        | 58.0  | 1856  | 1.0050          | {'f1': 0.8615902397980647} | {'accuracy': 0.8684} |
| 0.0078        | 59.0  | 1888  | 1.0207          | {'f1': 0.8595458368376786} | {'accuracy': 0.8664} |
| 0.0078        | 60.0  | 1920  | 0.9567          | {'f1': 0.8717320261437909} | {'accuracy': 0.8744} |
| 0.0078        | 61.0  | 1952  | 0.9195          | {'f1': 0.8792307692307691} | {'accuracy': 0.8744} |
| 0.0078        | 62.0  | 1984  | 0.9066          | {'f1': 0.875993640699523}  | {'accuracy': 0.8752} |
| 0.0049        | 63.0  | 2016  | 1.0266          | {'f1': 0.8649100794646591} | {'accuracy': 0.8708} |
| 0.0049        | 64.0  | 2048  | 0.9384          | {'f1': 0.8845283018867924} | {'accuracy': 0.8776} |
| 0.0049        | 65.0  | 2080  | 0.9161          | {'f1': 0.8813291139240507} | {'accuracy': 0.88}   |
| 0.0049        | 66.0  | 2112  | 0.9102          | {'f1': 0.8825147347740667} | {'accuracy': 0.8804} |
| 0.0049        | 67.0  | 2144  | 0.9218          | {'f1': 0.8806089743589743} | {'accuracy': 0.8808} |
| 0.0049        | 68.0  | 2176  | 1.1598          | {'f1': 0.8512644663523362} | {'accuracy': 0.8612} |
| 0.0049        | 69.0  | 2208  | 0.9406          | {'f1': 0.8753507014028056} | {'accuracy': 0.8756} |
| 0.0049        | 70.0  | 2240  | 0.9452          | {'f1': 0.8788230739450251} | {'accuracy': 0.8748} |
| 0.0049        | 71.0  | 2272  | 0.9634          | {'f1': 0.8741455568958586} | {'accuracy': 0.8748} |
| 0.0049        | 72.0  | 2304  | 1.0028          | {'f1': 0.8814703675918979} | {'accuracy': 0.8736} |
| 0.0049        | 73.0  | 2336  | 0.9469          | {'f1': 0.875801282051282}  | {'accuracy': 0.876}  |
| 0.0049        | 74.0  | 2368  | 1.0397          | {'f1': 0.8634655532359082} | {'accuracy': 0.8692} |
| 0.0049        | 75.0  | 2400  | 0.9316          | {'f1': 0.8852713178294573} | {'accuracy': 0.8816} |
| 0.0049        | 76.0  | 2432  | 0.9465          | {'f1': 0.8768433638899961} | {'accuracy': 0.8764} |
| 0.0049        | 77.0  | 2464  | 0.9301          | {'f1': 0.8873456790123456} | {'accuracy': 0.8832} |
| 0.0049        | 78.0  | 2496  | 1.0604          | {'f1': 0.8671386922115786} | {'accuracy': 0.8724} |
| 0.004         | 79.0  | 2528  | 0.9293          | {'f1': 0.8854247856586126} | {'accuracy': 0.8824} |
| 0.004         | 80.0  | 2560  | 0.9323          | {'f1': 0.88242233582383}   | {'accuracy': 0.8804} |
| 0.004         | 81.0  | 2592  | 0.9347          | {'f1': 0.887253002712127}  | {'accuracy': 0.8836} |
| 0.004         | 82.0  | 2624  | 0.9612          | {'f1': 0.8804828973843059} | {'accuracy': 0.8812} |
| 0.004         | 83.0  | 2656  | 0.9528          | {'f1': 0.8808664259927798} | {'accuracy': 0.8812} |
| 0.004         | 84.0  | 2688  | 0.9442          | {'f1': 0.8846459824980112} | {'accuracy': 0.884}  |
| 0.004         | 85.0  | 2720  | 0.9392          | {'f1': 0.8828402366863906} | {'accuracy': 0.8812} |
| 0.004         | 86.0  | 2752  | 1.0638          | {'f1': 0.8701461377870564} | {'accuracy': 0.8756} |
| 0.004         | 87.0  | 2784  | 0.9640          | {'f1': 0.8866615265998459} | {'accuracy': 0.8824} |
| 0.004         | 88.0  | 2816  | 1.0389          | {'f1': 0.871900826446281}  | {'accuracy': 0.876}  |
| 0.004         | 89.0  | 2848  | 0.9569          | {'f1': 0.8879310344827586} | {'accuracy': 0.8856} |
| 0.004         | 90.0  | 2880  | 0.9986          | {'f1': 0.887121212121212}  | {'accuracy': 0.8808} |
| 0.004         | 91.0  | 2912  | 1.0599          | {'f1': 0.8691666666666666} | {'accuracy': 0.8744} |
| 0.004         | 92.0  | 2944  | 0.9708          | {'f1': 0.8788368336025848} | {'accuracy': 0.88}   |
| 0.004         | 93.0  | 2976  | 1.0033          | {'f1': 0.8741830065359477} | {'accuracy': 0.8768} |
| 0.0008        | 94.0  | 3008  | 1.2071          | {'f1': 0.8493975903614457} | {'accuracy': 0.86}   |
| 0.0008        | 95.0  | 3040  | 1.0422          | {'f1': 0.8738664468260511} | {'accuracy': 0.8776} |
| 0.0008        | 96.0  | 3072  | 1.0542          | {'f1': 0.8808988764044944} | {'accuracy': 0.8728} |
| 0.0008        | 97.0  | 3104  | 1.0081          | {'f1': 0.8756624541377903} | {'accuracy': 0.878}  |
| 0.0008        | 98.0  | 3136  | 0.9592          | {'f1': 0.8885387948011029} | {'accuracy': 0.8868} |
| 0.0008        | 99.0  | 3168  | 0.9641          | {'f1': 0.8862042088854248} | {'accuracy': 0.8832} |
| 0.0008        | 100.0 | 3200  | 0.9594          | {'f1': 0.8891518737672585} | {'accuracy': 0.8876} |
| 0.0008        | 101.0 | 3232  | 0.9607          | {'f1': 0.8886246531906462} | {'accuracy': 0.8876} |
| 0.0008        | 102.0 | 3264  | 1.2907          | {'f1': 0.8712230215827338} | {'accuracy': 0.8568} |
| 0.0008        | 103.0 | 3296  | 0.9945          | {'f1': 0.8863366336633663} | {'accuracy': 0.8852} |
| 0.0008        | 104.0 | 3328  | 1.0011          | {'f1': 0.8858049167327517} | {'accuracy': 0.8848} |
| 0.0008        | 105.0 | 3360  | 1.0414          | {'f1': 0.8841625522218002} | {'accuracy': 0.878}  |
| 0.0008        | 106.0 | 3392  | 1.0385          | {'f1': 0.8717948717948717} | {'accuracy': 0.876}  |
| 0.0008        | 107.0 | 3424  | 1.0569          | {'f1': 0.8660565723793678} | {'accuracy': 0.8712} |
| 0.0008        | 108.0 | 3456  | 1.0613          | {'f1': 0.8819133034379671} | {'accuracy': 0.8736} |
| 0.0008        | 109.0 | 3488  | 0.9667          | {'f1': 0.88315748339195}   | {'accuracy': 0.8804} |
| 0.0048        | 110.0 | 3520  | 1.1289          | {'f1': 0.8781744571218255} | {'accuracy': 0.8676} |
| 0.0048        | 111.0 | 3552  | 0.9331          | {'f1': 0.8907563025210083} | {'accuracy': 0.8908} |
| 0.0048        | 112.0 | 3584  | 0.9808          | {'f1': 0.8881278538812785} | {'accuracy': 0.8824} |
| 0.0048        | 113.0 | 3616  | 0.9513          | {'f1': 0.8845843422114609} | {'accuracy': 0.8856} |
| 0.0048        | 114.0 | 3648  | 0.9608          | {'f1': 0.8874172185430463} | {'accuracy': 0.8844} |
| 0.0048        | 115.0 | 3680  | 0.9735          | {'f1': 0.8849005072181039} | {'accuracy': 0.882}  |
| 0.0048        | 116.0 | 3712  | 0.9755          | {'f1': 0.8849627012171182} | {'accuracy': 0.8828} |
| 0.0048        | 117.0 | 3744  | 1.0475          | {'f1': 0.8888888888888888} | {'accuracy': 0.882}  |
| 0.0048        | 118.0 | 3776  | 1.0445          | {'f1': 0.8785890073831009} | {'accuracy': 0.8816} |
| 0.0048        | 119.0 | 3808  | 0.9943          | {'f1': 0.8844621513944223} | {'accuracy': 0.884}  |
| 0.0048        | 120.0 | 3840  | 1.0380          | {'f1': 0.8823529411764706} | {'accuracy': 0.8848} |
| 0.0048        | 121.0 | 3872  | 1.1418          | {'f1': 0.8846011131725418} | {'accuracy': 0.8756} |
| 0.0048        | 122.0 | 3904  | 1.0418          | {'f1': 0.8747954173486089} | {'accuracy': 0.8776} |
| 0.0048        | 123.0 | 3936  | 1.0097          | {'f1': 0.8817377312952533} | {'accuracy': 0.8824} |
| 0.0048        | 124.0 | 3968  | 0.9912          | {'f1': 0.8861852433281004} | {'accuracy': 0.884}  |
| 0.0029        | 125.0 | 4000  | 0.9924          | {'f1': 0.8879310344827586} | {'accuracy': 0.8856} |
| 0.0029        | 126.0 | 4032  | 0.9964          | {'f1': 0.8843861740166864} | {'accuracy': 0.8836} |
| 0.0029        | 127.0 | 4064  | 0.9966          | {'f1': 0.8844779674473997} | {'accuracy': 0.8836} |
| 0.0029        | 128.0 | 4096  | 1.0560          | {'f1': 0.8745901639344262} | {'accuracy': 0.8776} |
| 0.0029        | 129.0 | 4128  | 1.0364          | {'f1': 0.8800648298217179} | {'accuracy': 0.8816} |
| 0.0029        | 130.0 | 4160  | 1.0233          | {'f1': 0.8804828973843059} | {'accuracy': 0.8812} |
| 0.0029        | 131.0 | 4192  | 1.0493          | {'f1': 0.889904761904762}  | {'accuracy': 0.8844} |
| 0.0029        | 132.0 | 4224  | 1.0439          | {'f1': 0.8893991580558744} | {'accuracy': 0.8844} |
| 0.0029        | 133.0 | 4256  | 1.0264          | {'f1': 0.8906068805566293} | {'accuracy': 0.8868} |
| 0.0029        | 134.0 | 4288  | 1.1016          | {'f1': 0.8866442199775532} | {'accuracy': 0.8788} |
| 0.0029        | 135.0 | 4320  | 1.0469          | {'f1': 0.8895658796648896} | {'accuracy': 0.884}  |
| 0.0029        | 136.0 | 4352  | 1.1812          | {'f1': 0.8828297715549005} | {'accuracy': 0.8728} |
| 0.0029        | 137.0 | 4384  | 1.0357          | {'f1': 0.8940905602455871} | {'accuracy': 0.8896} |
| 0.0029        | 138.0 | 4416  | 1.1247          | {'f1': 0.8776266996291718} | {'accuracy': 0.8812} |
| 0.0029        | 139.0 | 4448  | 1.0886          | {'f1': 0.8932478310071671} | {'accuracy': 0.8868} |
| 0.0029        | 140.0 | 4480  | 1.0707          | {'f1': 0.8932626797880393} | {'accuracy': 0.8872} |
| 0.0022        | 141.0 | 4512  | 1.0439          | {'f1': 0.8868378812199037} | {'accuracy': 0.8872} |
| 0.0022        | 142.0 | 4544  | 1.0858          | {'f1': 0.8846310640032613} | {'accuracy': 0.8868} |
| 0.0022        | 143.0 | 4576  | 1.0295          | {'f1': 0.8903071400079777} | {'accuracy': 0.89}   |
| 0.0022        | 144.0 | 4608  | 1.0280          | {'f1': 0.8903945795137506} | {'accuracy': 0.89}   |
| 0.0022        | 145.0 | 4640  | 1.0323          | {'f1': 0.8898643256185156} | {'accuracy': 0.8896} |
| 0.0022        | 146.0 | 4672  | 1.0339          | {'f1': 0.8898643256185156} | {'accuracy': 0.8896} |
| 0.0022        | 147.0 | 4704  | 1.0161          | {'f1': 0.8920409771473602} | {'accuracy': 0.8904} |
| 0.0022        | 148.0 | 4736  | 1.2549          | {'f1': 0.861850443599493}  | {'accuracy': 0.8692} |
| 0.0022        | 149.0 | 4768  | 1.0567          | {'f1': 0.8887996788438377} | {'accuracy': 0.8892} |
| 0.0022        | 150.0 | 4800  | 1.0522          | {'f1': 0.8907563025210083} | {'accuracy': 0.8908} |
| 0.0022        | 151.0 | 4832  | 1.0526          | {'f1': 0.8907563025210083} | {'accuracy': 0.8908} |
| 0.0022        | 152.0 | 4864  | 1.2013          | {'f1': 0.8857774502579219} | {'accuracy': 0.876}  |
| 0.0022        | 153.0 | 4896  | 1.1488          | {'f1': 0.8760806916426512} | {'accuracy': 0.8796} |
| 0.0022        | 154.0 | 4928  | 1.0654          | {'f1': 0.8832731648616126} | {'accuracy': 0.8836} |
| 0.0022        | 155.0 | 4960  | 1.0409          | {'f1': 0.8892405063291139} | {'accuracy': 0.888}  |
| 0.0022        | 156.0 | 4992  | 1.3100          | {'f1': 0.8513918629550321} | {'accuracy': 0.8612} |
| 0.001         | 157.0 | 5024  | 1.2608          | {'f1': 0.8628113127902068} | {'accuracy': 0.87}   |
| 0.001         | 158.0 | 5056  | 1.0549          | {'f1': 0.8910355486862442} | {'accuracy': 0.8872} |
| 0.001         | 159.0 | 5088  | 1.1585          | {'f1': 0.8762844225236333} | {'accuracy': 0.8796} |
| 0.001         | 160.0 | 5120  | 1.1419          | {'f1': 0.879542670477746}  | {'accuracy': 0.882}  |
| 0.001         | 161.0 | 5152  | 1.1148          | {'f1': 0.8810963321241435} | {'accuracy': 0.882}  |
| 0.001         | 162.0 | 5184  | 1.1114          | {'f1': 0.8807413376309429} | {'accuracy': 0.8816} |
| 0.001         | 163.0 | 5216  | 1.1111          | {'f1': 0.8811921063229964} | {'accuracy': 0.882}  |
| 0.001         | 164.0 | 5248  | 1.1205          | {'f1': 0.8838141025641026} | {'accuracy': 0.884}  |
| 0.001         | 165.0 | 5280  | 1.1270          | {'f1': 0.8842611133360032} | {'accuracy': 0.8844} |
| 0.001         | 166.0 | 5312  | 1.2663          | {'f1': 0.8605042016806723} | {'accuracy': 0.8672} |
| 0.001         | 167.0 | 5344  | 1.0968          | {'f1': 0.8861267040898154} | {'accuracy': 0.8864} |
| 0.001         | 168.0 | 5376  | 1.3010          | {'f1': 0.8606522659889877} | {'accuracy': 0.8684} |
| 0.001         | 169.0 | 5408  | 1.1075          | {'f1': 0.880161943319838}  | {'accuracy': 0.8816} |
| 0.001         | 170.0 | 5440  | 1.1110          | {'f1': 0.8819472616632859} | {'accuracy': 0.8836} |
| 0.001         | 171.0 | 5472  | 1.0844          | {'f1': 0.8806387225548902} | {'accuracy': 0.8804} |
| 0.0024        | 172.0 | 5504  | 1.4479          | {'f1': 0.8404163052905465} | {'accuracy': 0.8528} |
| 0.0024        | 173.0 | 5536  | 1.1518          | {'f1': 0.8859516616314198} | {'accuracy': 0.8792} |
| 0.0024        | 174.0 | 5568  | 1.2326          | {'f1': 0.8644351464435147} | {'accuracy': 0.8704} |
| 0.0024        | 175.0 | 5600  | 1.1863          | {'f1': 0.8912228057014252} | {'accuracy': 0.884}  |
| 0.0024        | 176.0 | 5632  | 1.1230          | {'f1': 0.8864908073541168} | {'accuracy': 0.8864} |
| 0.0024        | 177.0 | 5664  | 1.2142          | {'f1': 0.8680497925311204} | {'accuracy': 0.8728} |
| 0.0024        | 178.0 | 5696  | 1.3023          | {'f1': 0.8589527027027027} | {'accuracy': 0.8664} |
| 0.0024        | 179.0 | 5728  | 1.1757          | {'f1': 0.8898081985708913} | {'accuracy': 0.8828} |
| 0.0024        | 180.0 | 5760  | 1.2237          | {'f1': 0.8703933747412008} | {'accuracy': 0.8748} |
| 0.0024        | 181.0 | 5792  | 1.1846          | {'f1': 0.8744872846595569} | {'accuracy': 0.8776} |
| 0.0024        | 182.0 | 5824  | 1.1774          | {'f1': 0.8748977923139819} | {'accuracy': 0.8776} |
| 0.0024        | 183.0 | 5856  | 1.1206          | {'f1': 0.8826591910292352} | {'accuracy': 0.8828} |
| 0.0024        | 184.0 | 5888  | 1.1166          | {'f1': 0.8827531012404962} | {'accuracy': 0.8828} |
| 0.0024        | 185.0 | 5920  | 1.1179          | {'f1': 0.8827531012404962} | {'accuracy': 0.8828} |
| 0.0024        | 186.0 | 5952  | 1.1217          | {'f1': 0.8826591910292352} | {'accuracy': 0.8828} |
| 0.0024        | 187.0 | 5984  | 1.1211          | {'f1': 0.8823058446757407} | {'accuracy': 0.8824} |
| 0.0019        | 188.0 | 6016  | 1.1497          | {'f1': 0.8939566704675029} | {'accuracy': 0.8884} |
| 0.0019        | 189.0 | 6048  | 1.0649          | {'f1': 0.8934681181959565} | {'accuracy': 0.8904} |
| 0.0019        | 190.0 | 6080  | 1.1508          | {'f1': 0.8797364085667216} | {'accuracy': 0.8832} |
| 0.0019        | 191.0 | 6112  | 1.0691          | {'f1': 0.885193982581156}  | {'accuracy': 0.884}  |
| 0.0019        | 192.0 | 6144  | 1.0697          | {'f1': 0.8856351404827859} | {'accuracy': 0.8844} |
| 0.0019        | 193.0 | 6176  | 1.0720          | {'f1': 0.8846611177170035} | {'accuracy': 0.8836} |
| 0.0019        | 194.0 | 6208  | 1.0872          | {'f1': 0.8832}             | {'accuracy': 0.8832} |
| 0.0019        | 195.0 | 6240  | 1.1084          | {'f1': 0.8819725141471302} | {'accuracy': 0.8832} |
| 0.0019        | 196.0 | 6272  | 1.1100          | {'f1': 0.8819725141471302} | {'accuracy': 0.8832} |
| 0.0019        | 197.0 | 6304  | 1.1093          | {'f1': 0.8816161616161616} | {'accuracy': 0.8828} |
| 0.0019        | 198.0 | 6336  | 1.1084          | {'f1': 0.8829701372074253} | {'accuracy': 0.884}  |
| 0.0019        | 199.0 | 6368  | 1.1088          | {'f1': 0.8829701372074253} | {'accuracy': 0.884}  |
| 0.0019        | 200.0 | 6400  | 1.1076          | {'f1': 0.8830645161290323} | {'accuracy': 0.884}  |
| 0.0019        | 201.0 | 6432  | 1.1078          | {'f1': 0.8830645161290323} | {'accuracy': 0.884}  |
| 0.0019        | 202.0 | 6464  | 1.3658          | {'f1': 0.8515021459227468} | {'accuracy': 0.8616} |
| 0.0019        | 203.0 | 6496  | 1.7765          | {'f1': 0.8077969174977335} | {'accuracy': 0.8304} |
| 0.0042        | 204.0 | 6528  | 1.3374          | {'f1': 0.8572638712409996} | {'accuracy': 0.8652} |
| 0.0042        | 205.0 | 6560  | 1.3661          | {'f1': 0.8531049250535331} | {'accuracy': 0.8628} |
| 0.0042        | 206.0 | 6592  | 1.0987          | {'f1': 0.8928707586732749} | {'accuracy': 0.8876} |
| 0.0042        | 207.0 | 6624  | 1.0845          | {'f1': 0.8939103791650709} | {'accuracy': 0.8892} |
| 0.0042        | 208.0 | 6656  | 1.0750          | {'f1': 0.893420546363986}  | {'accuracy': 0.8892} |
| 0.0042        | 209.0 | 6688  | 1.0673          | {'f1': 0.8939628482972137} | {'accuracy': 0.8904} |
| 0.0042        | 210.0 | 6720  | 1.0674          | {'f1': 0.8941450174486235} | {'accuracy': 0.8908} |
| 0.0042        | 211.0 | 6752  | 1.0677          | {'f1': 0.8943278943278943} | {'accuracy': 0.8912} |
| 0.0042        | 212.0 | 6784  | 1.0793          | {'f1': 0.8924148606811146} | {'accuracy': 0.8888} |
| 0.0042        | 213.0 | 6816  | 1.0959          | {'f1': 0.8902532617037606} | {'accuracy': 0.8856} |
| 0.0042        | 214.0 | 6848  | 1.2329          | {'f1': 0.8674399337199669} | {'accuracy': 0.872}  |
| 0.0042        | 215.0 | 6880  | 1.1383          | {'f1': 0.8819024586860137} | {'accuracy': 0.8828} |
| 0.0042        | 216.0 | 6912  | 1.1344          | {'f1': 0.8846926476496585} | {'accuracy': 0.8852} |
| 0.0042        | 217.0 | 6944  | 1.1316          | {'f1': 0.8860353130016051} | {'accuracy': 0.8864} |
| 0.0042        | 218.0 | 6976  | 1.1284          | {'f1': 0.8866639967961554} | {'accuracy': 0.8868} |
| 0.0009        | 219.0 | 7008  | 1.1253          | {'f1': 0.8864908073541168} | {'accuracy': 0.8864} |
| 0.0009        | 220.0 | 7040  | 1.1245          | {'f1': 0.8857827476038339} | {'accuracy': 0.8856} |
| 0.0009        | 221.0 | 7072  | 1.1242          | {'f1': 0.8857827476038339} | {'accuracy': 0.8856} |
| 0.0009        | 222.0 | 7104  | 1.1136          | {'f1': 0.8857142857142859} | {'accuracy': 0.8848} |
| 0.0009        | 223.0 | 7136  | 1.1104          | {'f1': 0.8873128447596532} | {'accuracy': 0.8856} |
| 0.0009        | 224.0 | 7168  | 1.1184          | {'f1': 0.8867699642431466} | {'accuracy': 0.886}  |
| 0.0009        | 225.0 | 7200  | 1.1197          | {'f1': 0.8858846918489065} | {'accuracy': 0.8852} |
| 0.0009        | 226.0 | 7232  | 1.1202          | {'f1': 0.8858846918489065} | {'accuracy': 0.8852} |
| 0.0009        | 227.0 | 7264  | 1.1212          | {'f1': 0.8854415274463007} | {'accuracy': 0.8848} |
| 0.0009        | 228.0 | 7296  | 1.1214          | {'f1': 0.8858846918489065} | {'accuracy': 0.8852} |
| 0.0009        | 229.0 | 7328  | 1.1217          | {'f1': 0.8858846918489065} | {'accuracy': 0.8852} |
| 0.0009        | 230.0 | 7360  | 1.2362          | {'f1': 0.8856502242152466} | {'accuracy': 0.8776} |
| 0.0009        | 231.0 | 7392  | 1.2124          | {'f1': 0.8763769889840881} | {'accuracy': 0.8788} |
| 0.0009        | 232.0 | 7424  | 1.1419          | {'f1': 0.8844779674473997} | {'accuracy': 0.8836} |
| 0.0009        | 233.0 | 7456  | 1.1410          | {'f1': 0.8842188739095956} | {'accuracy': 0.8832} |
| 0.0009        | 234.0 | 7488  | 1.1424          | {'f1': 0.8849206349206349} | {'accuracy': 0.884}  |
| 0.0004        | 235.0 | 7520  | 1.1459          | {'f1': 0.8830548926014321} | {'accuracy': 0.8824} |
| 0.0004        | 236.0 | 7552  | 1.1737          | {'f1': 0.8801287208366854} | {'accuracy': 0.8808} |
| 0.0004        | 237.0 | 7584  | 1.1743          | {'f1': 0.8804828973843059} | {'accuracy': 0.8812} |
| 0.0004        | 238.0 | 7616  | 1.1412          | {'f1': 0.8854660347551343} | {'accuracy': 0.884}  |
| 0.0004        | 239.0 | 7648  | 1.1411          | {'f1': 0.8854660347551343} | {'accuracy': 0.884}  |
| 0.0004        | 240.0 | 7680  | 1.3032          | {'f1': 0.867109634551495}  | {'accuracy': 0.872}  |
| 0.0004        | 241.0 | 7712  | 1.3155          | {'f1': 0.86511240632806}   | {'accuracy': 0.8704} |
| 0.0004        | 242.0 | 7744  | 1.3813          | {'f1': 0.8608659100462379} | {'accuracy': 0.8676} |
| 0.0004        | 243.0 | 7776  | 1.5158          | {'f1': 0.8496110630942092} | {'accuracy': 0.8608} |
| 0.0004        | 244.0 | 7808  | 1.3354          | {'f1': 0.875724937862469}  | {'accuracy': 0.88}   |
| 0.0004        | 245.0 | 7840  | 1.2804          | {'f1': 0.8803905614320586} | {'accuracy': 0.8824} |
| 0.0004        | 246.0 | 7872  | 1.2878          | {'f1': 0.8794442174090723} | {'accuracy': 0.882}  |
| 0.0004        | 247.0 | 7904  | 1.3296          | {'f1': 0.8722612649855312} | {'accuracy': 0.8764} |
| 0.0004        | 248.0 | 7936  | 1.2071          | {'f1': 0.8958093041138023} | {'accuracy': 0.8916} |
| 0.0004        | 249.0 | 7968  | 1.2093          | {'f1': 0.8963133640552995} | {'accuracy': 0.892}  |
| 0.0022        | 250.0 | 8000  | 1.1794          | {'f1': 0.8939628482972137} | {'accuracy': 0.8904} |
| 0.0022        | 251.0 | 8032  | 1.1944          | {'f1': 0.895648825567963}  | {'accuracy': 0.8916} |
| 0.0022        | 252.0 | 8064  | 1.1748          | {'f1': 0.8941450174486235} | {'accuracy': 0.8908} |
| 0.0022        | 253.0 | 8096  | 1.1720          | {'f1': 0.8939805825242718} | {'accuracy': 0.8908} |
| 0.0022        | 254.0 | 8128  | 1.2334          | {'f1': 0.8792822185970636} | {'accuracy': 0.8816} |
| 0.0022        | 255.0 | 8160  | 1.1558          | {'f1': 0.8971672487388436} | {'accuracy': 0.894}  |
| 0.0022        | 256.0 | 8192  | 1.1672          | {'f1': 0.8983050847457628} | {'accuracy': 0.8944} |
| 0.0022        | 257.0 | 8224  | 1.1623          | {'f1': 0.8991109393119444} | {'accuracy': 0.8956} |
| 0.0022        | 258.0 | 8256  | 1.1615          | {'f1': 0.8990328820116054} | {'accuracy': 0.8956} |
| 0.0022        | 259.0 | 8288  | 1.1585          | {'f1': 0.8984496124031008} | {'accuracy': 0.8952} |
| 0.0022        | 260.0 | 8320  | 1.1550          | {'f1': 0.8968470221876217} | {'accuracy': 0.894}  |
| 0.0022        | 261.0 | 8352  | 1.1552          | {'f1': 0.8968470221876217} | {'accuracy': 0.894}  |
| 0.0022        | 262.0 | 8384  | 1.1553          | {'f1': 0.8964174454828661} | {'accuracy': 0.8936} |
| 0.0022        | 263.0 | 8416  | 1.1555          | {'f1': 0.8964174454828661} | {'accuracy': 0.8936} |
| 0.0022        | 264.0 | 8448  | 1.2035          | {'f1': 0.8860145513338723} | {'accuracy': 0.8872} |
| 0.0022        | 265.0 | 8480  | 1.2186          | {'f1': 0.8840227088402272} | {'accuracy': 0.8856} |
| 0.0007        | 266.0 | 8512  | 1.2153          | {'f1': 0.8845686512758202} | {'accuracy': 0.886}  |
| 0.0007        | 267.0 | 8544  | 1.2144          | {'f1': 0.8850202429149797} | {'accuracy': 0.8864} |
| 0.0007        | 268.0 | 8576  | 1.2137          | {'f1': 0.8850202429149797} | {'accuracy': 0.8864} |
| 0.0007        | 269.0 | 8608  | 1.2133          | {'f1': 0.8850202429149797} | {'accuracy': 0.8864} |
| 0.0007        | 270.0 | 8640  | 1.2131          | {'f1': 0.8850202429149797} | {'accuracy': 0.8864} |
| 0.0007        | 271.0 | 8672  | 1.2128          | {'f1': 0.8854714690408741} | {'accuracy': 0.8868} |
| 0.0007        | 272.0 | 8704  | 1.2123          | {'f1': 0.8855640921957139} | {'accuracy': 0.8868} |
| 0.0007        | 273.0 | 8736  | 1.2120          | {'f1': 0.8855640921957139} | {'accuracy': 0.8868} |
| 0.0007        | 274.0 | 8768  | 1.2055          | {'f1': 0.8850342880193627} | {'accuracy': 0.886}  |
| 0.0007        | 275.0 | 8800  | 1.2049          | {'f1': 0.885483870967742}  | {'accuracy': 0.8864} |
| 0.0007        | 276.0 | 8832  | 1.1718          | {'f1': 0.888178913738019}  | {'accuracy': 0.888}  |
| 0.0007        | 277.0 | 8864  | 1.1650          | {'f1': 0.8901273885350319} | {'accuracy': 0.8896} |
| 0.0007        | 278.0 | 8896  | 1.1606          | {'f1': 0.89179548156956}   | {'accuracy': 0.8908} |
| 0.0007        | 279.0 | 8928  | 1.1608          | {'f1': 0.8914421553090333} | {'accuracy': 0.8904} |
| 0.0007        | 280.0 | 8960  | 1.1609          | {'f1': 0.8914421553090333} | {'accuracy': 0.8904} |
| 0.0007        | 281.0 | 8992  | 1.1613          | {'f1': 0.8914421553090333} | {'accuracy': 0.8904} |
| 0.0           | 282.0 | 9024  | 1.1623          | {'f1': 0.8913560666137985} | {'accuracy': 0.8904} |
| 0.0           | 283.0 | 9056  | 1.1636          | {'f1': 0.8913560666137985} | {'accuracy': 0.8904} |
| 0.0           | 284.0 | 9088  | 1.1638          | {'f1': 0.8913560666137985} | {'accuracy': 0.8904} |
| 0.0           | 285.0 | 9120  | 1.1642          | {'f1': 0.8913560666137985} | {'accuracy': 0.8904} |
| 0.0           | 286.0 | 9152  | 1.1645          | {'f1': 0.8913560666137985} | {'accuracy': 0.8904} |
| 0.0           | 287.0 | 9184  | 1.1647          | {'f1': 0.8913560666137985} | {'accuracy': 0.8904} |
| 0.0           | 288.0 | 9216  | 1.1649          | {'f1': 0.8913560666137985} | {'accuracy': 0.8904} |
| 0.0           | 289.0 | 9248  | 1.1652          | {'f1': 0.8913560666137985} | {'accuracy': 0.8904} |
| 0.0           | 290.0 | 9280  | 1.1657          | {'f1': 0.8913560666137985} | {'accuracy': 0.8904} |
| 0.0           | 291.0 | 9312  | 1.1659          | {'f1': 0.8913560666137985} | {'accuracy': 0.8904} |
| 0.0           | 292.0 | 9344  | 1.1661          | {'f1': 0.8913560666137985} | {'accuracy': 0.8904} |
| 0.0           | 293.0 | 9376  | 1.1812          | {'f1': 0.888178913738019}  | {'accuracy': 0.888}  |
| 0.0           | 294.0 | 9408  | 1.1723          | {'f1': 0.8900357284636761} | {'accuracy': 0.8892} |
| 0.0           | 295.0 | 9440  | 1.1702          | {'f1': 0.8912613681296955} | {'accuracy': 0.89}   |
| 0.0           | 296.0 | 9472  | 1.1705          | {'f1': 0.8912613681296955} | {'accuracy': 0.89}   |
| 0.0           | 297.0 | 9504  | 1.1708          | {'f1': 0.891699604743083}  | {'accuracy': 0.8904} |
| 0.0           | 298.0 | 9536  | 1.1712          | {'f1': 0.891699604743083}  | {'accuracy': 0.8904} |
| 0.0           | 299.0 | 9568  | 1.1715          | {'f1': 0.891699604743083}  | {'accuracy': 0.8904} |
| 0.0           | 300.0 | 9600  | 1.1717          | {'f1': 0.891699604743083}  | {'accuracy': 0.8904} |
| 0.0           | 301.0 | 9632  | 1.1851          | {'f1': 0.8887116074990027} | {'accuracy': 0.8884} |
| 0.0           | 302.0 | 9664  | 1.1968          | {'f1': 0.8879103282626101} | {'accuracy': 0.888}  |
| 0.0           | 303.0 | 9696  | 1.1972          | {'f1': 0.8879103282626101} | {'accuracy': 0.888}  |
| 0.0           | 304.0 | 9728  | 1.1972          | {'f1': 0.8879103282626101} | {'accuracy': 0.888}  |
| 0.0           | 305.0 | 9760  | 1.1968          | {'f1': 0.8883553421368547} | {'accuracy': 0.8884} |
| 0.0           | 306.0 | 9792  | 1.1966          | {'f1': 0.8883553421368547} | {'accuracy': 0.8884} |
| 0.0           | 307.0 | 9824  | 1.1965          | {'f1': 0.8883553421368547} | {'accuracy': 0.8884} |
| 0.0           | 308.0 | 9856  | 1.1963          | {'f1': 0.888}              | {'accuracy': 0.888}  |
| 0.0           | 309.0 | 9888  | 1.1968          | {'f1': 0.888}              | {'accuracy': 0.888}  |
| 0.0           | 310.0 | 9920  | 1.1967          | {'f1': 0.888}              | {'accuracy': 0.888}  |
| 0.0           | 311.0 | 9952  | 1.1967          | {'f1': 0.888}              | {'accuracy': 0.888}  |
| 0.0           | 312.0 | 9984  | 1.1955          | {'f1': 0.888178913738019}  | {'accuracy': 0.888}  |
| 0.0           | 313.0 | 10016 | 1.1928          | {'f1': 0.8886227544910179} | {'accuracy': 0.8884} |
| 0.0           | 314.0 | 10048 | 1.1926          | {'f1': 0.8886227544910179} | {'accuracy': 0.8884} |
| 0.0           | 315.0 | 10080 | 1.1930          | {'f1': 0.8886227544910179} | {'accuracy': 0.8884} |
| 0.0           | 316.0 | 10112 | 1.1934          | {'f1': 0.8886227544910179} | {'accuracy': 0.8884} |
| 0.0           | 317.0 | 10144 | 1.1932          | {'f1': 0.8887116074990027} | {'accuracy': 0.8884} |
| 0.0           | 318.0 | 10176 | 1.1932          | {'f1': 0.8891547049441787} | {'accuracy': 0.8888} |
| 0.0           | 319.0 | 10208 | 1.1933          | {'f1': 0.8891547049441787} | {'accuracy': 0.8888} |
| 0.0           | 320.0 | 10240 | 1.1934          | {'f1': 0.8891547049441787} | {'accuracy': 0.8888} |
| 0.0           | 321.0 | 10272 | 1.1935          | {'f1': 0.8888003188521324} | {'accuracy': 0.8884} |
| 0.0           | 322.0 | 10304 | 1.1936          | {'f1': 0.8888003188521324} | {'accuracy': 0.8884} |
| 0.0           | 323.0 | 10336 | 1.1857          | {'f1': 0.8922226608764311} | {'accuracy': 0.8908} |
| 0.0           | 324.0 | 10368 | 1.1834          | {'f1': 0.8939334637964774} | {'accuracy': 0.8916} |
| 0.0           | 325.0 | 10400 | 1.1840          | {'f1': 0.8940164254986311} | {'accuracy': 0.8916} |
| 0.0           | 326.0 | 10432 | 1.3728          | {'f1': 0.8917910447761194} | {'accuracy': 0.884}  |
| 0.0           | 327.0 | 10464 | 1.3580          | {'f1': 0.8761354252683732} | {'accuracy': 0.88}   |
| 0.0           | 328.0 | 10496 | 1.3400          | {'f1': 0.8796714579055441} | {'accuracy': 0.8828} |
| 0.0011        | 329.0 | 10528 | 1.2114          | {'f1': 0.8901229670765569} | {'accuracy': 0.8892} |
| 0.0011        | 330.0 | 10560 | 1.1982          | {'f1': 0.8939512961508248} | {'accuracy': 0.892}  |
| 0.0011        | 331.0 | 10592 | 1.1982          | {'f1': 0.894385551629368}  | {'accuracy': 0.8924} |
| 0.0011        | 332.0 | 10624 | 1.1985          | {'f1': 0.894385551629368}  | {'accuracy': 0.8924} |
| 0.0011        | 333.0 | 10656 | 1.1988          | {'f1': 0.8939512961508248} | {'accuracy': 0.892}  |
| 0.0011        | 334.0 | 10688 | 1.1991          | {'f1': 0.8939512961508248} | {'accuracy': 0.892}  |
| 0.0011        | 335.0 | 10720 | 1.1994          | {'f1': 0.8939512961508248} | {'accuracy': 0.892}  |
| 0.0011        | 336.0 | 10752 | 1.1996          | {'f1': 0.8939512961508248} | {'accuracy': 0.892}  |
| 0.0011        | 337.0 | 10784 | 1.1998          | {'f1': 0.8939512961508248} | {'accuracy': 0.892}  |
| 0.0011        | 338.0 | 10816 | 1.2000          | {'f1': 0.8939512961508248} | {'accuracy': 0.892}  |
| 0.0011        | 339.0 | 10848 | 1.2004          | {'f1': 0.8939512961508248} | {'accuracy': 0.892}  |
| 0.0011        | 340.0 | 10880 | 1.2012          | {'f1': 0.893432953204876}  | {'accuracy': 0.8916} |
| 0.0011        | 341.0 | 10912 | 1.2018          | {'f1': 0.8925619834710744} | {'accuracy': 0.8908} |
| 0.0011        | 342.0 | 10944 | 1.2020          | {'f1': 0.8925619834710744} | {'accuracy': 0.8908} |
| 0.0011        | 343.0 | 10976 | 1.2029          | {'f1': 0.8924773532886963} | {'accuracy': 0.8908} |
| 0.0           | 344.0 | 11008 | 1.2033          | {'f1': 0.8920409771473602} | {'accuracy': 0.8904} |
| 0.0           | 345.0 | 11040 | 1.2037          | {'f1': 0.892392589672842}  | {'accuracy': 0.8908} |
| 0.0           | 346.0 | 11072 | 1.2039          | {'f1': 0.892392589672842}  | {'accuracy': 0.8908} |
| 0.0           | 347.0 | 11104 | 1.2042          | {'f1': 0.892392589672842}  | {'accuracy': 0.8908} |
| 0.0           | 348.0 | 11136 | 1.2049          | {'f1': 0.8919558359621451} | {'accuracy': 0.8904} |
| 0.0           | 349.0 | 11168 | 1.2057          | {'f1': 0.8919558359621451} | {'accuracy': 0.8904} |
| 0.0           | 350.0 | 11200 | 1.2060          | {'f1': 0.8919558359621451} | {'accuracy': 0.8904} |
| 0.0           | 351.0 | 11232 | 1.2066          | {'f1': 0.8919558359621451} | {'accuracy': 0.8904} |
| 0.0           | 352.0 | 11264 | 1.2069          | {'f1': 0.8919558359621451} | {'accuracy': 0.8904} |
| 0.0           | 353.0 | 11296 | 1.2071          | {'f1': 0.8919558359621451} | {'accuracy': 0.8904} |
| 0.0           | 354.0 | 11328 | 1.3487          | {'f1': 0.8800328677074775} | {'accuracy': 0.8832} |
| 0.0           | 355.0 | 11360 | 1.3550          | {'f1': 0.8800328677074775} | {'accuracy': 0.8832} |
| 0.0           | 356.0 | 11392 | 1.3537          | {'f1': 0.8800328677074775} | {'accuracy': 0.8832} |
| 0.0           | 357.0 | 11424 | 1.3524          | {'f1': 0.8800328677074775} | {'accuracy': 0.8832} |
| 0.0           | 358.0 | 11456 | 1.3508          | {'f1': 0.8800328677074775} | {'accuracy': 0.8832} |
| 0.0           | 359.0 | 11488 | 1.3490          | {'f1': 0.8800328677074775} | {'accuracy': 0.8832} |
| 0.0           | 360.0 | 11520 | 1.3446          | {'f1': 0.8805908904390645} | {'accuracy': 0.8836} |
| 0.0           | 361.0 | 11552 | 1.2418          | {'f1': 0.8881814564265818} | {'accuracy': 0.8876} |
| 0.0           | 362.0 | 11584 | 1.2392          | {'f1': 0.8891537544696066} | {'accuracy': 0.8884} |
| 0.0           | 363.0 | 11616 | 1.2392          | {'f1': 0.8891537544696066} | {'accuracy': 0.8884} |
| 0.0           | 364.0 | 11648 | 1.6402          | {'f1': 0.8736955739474631} | {'accuracy': 0.8596} |
| 0.0           | 365.0 | 11680 | 1.3830          | {'f1': 0.8876488095238095} | {'accuracy': 0.8792} |
| 0.0           | 366.0 | 11712 | 1.4854          | {'f1': 0.8601694915254238} | {'accuracy': 0.868}  |
| 0.0           | 367.0 | 11744 | 1.3072          | {'f1': 0.8802961744138215} | {'accuracy': 0.8836} |
| 0.0           | 368.0 | 11776 | 1.2977          | {'f1': 0.8811475409836066} | {'accuracy': 0.884}  |
| 0.0           | 369.0 | 11808 | 1.2923          | {'f1': 0.8805237315875615} | {'accuracy': 0.8832} |
| 0.0           | 370.0 | 11840 | 1.4240          | {'f1': 0.8644997889404812} | {'accuracy': 0.8716} |
| 0.0           | 371.0 | 11872 | 1.1734          | {'f1': 0.8884462151394423} | {'accuracy': 0.888}  |
| 0.0           | 372.0 | 11904 | 1.1621          | {'f1': 0.888888888888889}  | {'accuracy': 0.8876} |
| 0.0           | 373.0 | 11936 | 1.1620          | {'f1': 0.888888888888889}  | {'accuracy': 0.8876} |
| 0.0           | 374.0 | 11968 | 1.1630          | {'f1': 0.888888888888889}  | {'accuracy': 0.8876} |
| 0.0044        | 375.0 | 12000 | 1.1642          | {'f1': 0.8892405063291139} | {'accuracy': 0.888}  |
| 0.0044        | 376.0 | 12032 | 1.1644          | {'f1': 0.8892405063291139} | {'accuracy': 0.888}  |
| 0.0044        | 377.0 | 12064 | 1.1646          | {'f1': 0.8892405063291139} | {'accuracy': 0.888}  |
| 0.0044        | 378.0 | 12096 | 1.1645          | {'f1': 0.8892405063291139} | {'accuracy': 0.888}  |
| 0.0044        | 379.0 | 12128 | 1.1651          | {'f1': 0.8892405063291139} | {'accuracy': 0.888}  |
| 0.0044        | 380.0 | 12160 | 1.1641          | {'f1': 0.8889766890557091} | {'accuracy': 0.8876} |
| 0.0044        | 381.0 | 12192 | 1.1641          | {'f1': 0.8889766890557091} | {'accuracy': 0.8876} |
| 0.0044        | 382.0 | 12224 | 1.1643          | {'f1': 0.8889766890557091} | {'accuracy': 0.8876} |
| 0.0044        | 383.0 | 12256 | 1.1638          | {'f1': 0.8889766890557091} | {'accuracy': 0.8876} |
| 0.0044        | 384.0 | 12288 | 1.1636          | {'f1': 0.888713496448303}  | {'accuracy': 0.8872} |
| 0.0044        | 385.0 | 12320 | 1.1643          | {'f1': 0.8886255924170617} | {'accuracy': 0.8872} |
| 0.0044        | 386.0 | 12352 | 1.1657          | {'f1': 0.8889766890557091} | {'accuracy': 0.8876} |
| 0.0044        | 387.0 | 12384 | 1.1661          | {'f1': 0.8889766890557091} | {'accuracy': 0.8876} |
| 0.0044        | 388.0 | 12416 | 1.1664          | {'f1': 0.8889766890557091} | {'accuracy': 0.8876} |
| 0.0044        | 389.0 | 12448 | 1.1666          | {'f1': 0.8889766890557091} | {'accuracy': 0.8876} |
| 0.0044        | 390.0 | 12480 | 1.1680          | {'f1': 0.888888888888889}  | {'accuracy': 0.8876} |
| 0.0           | 391.0 | 12512 | 1.1694          | {'f1': 0.888888888888889}  | {'accuracy': 0.8876} |
| 0.0           | 392.0 | 12544 | 1.1705          | {'f1': 0.8892405063291139} | {'accuracy': 0.888}  |
| 0.0           | 393.0 | 12576 | 1.1708          | {'f1': 0.8892405063291139} | {'accuracy': 0.888}  |
| 0.0           | 394.0 | 12608 | 1.1710          | {'f1': 0.888888888888889}  | {'accuracy': 0.8876} |
| 0.0           | 395.0 | 12640 | 1.1718          | {'f1': 0.889944576405384}  | {'accuracy': 0.8888} |
| 0.0           | 396.0 | 12672 | 1.1720          | {'f1': 0.889944576405384}  | {'accuracy': 0.8888} |
| 0.0           | 397.0 | 12704 | 1.1724          | {'f1': 0.889944576405384}  | {'accuracy': 0.8888} |
| 0.0           | 398.0 | 12736 | 1.1727          | {'f1': 0.889944576405384}  | {'accuracy': 0.8888} |
| 0.0           | 399.0 | 12768 | 1.1728          | {'f1': 0.889944576405384}  | {'accuracy': 0.8888} |
| 0.0           | 400.0 | 12800 | 1.1731          | {'f1': 0.889592402057776}  | {'accuracy': 0.8884} |
| 0.0           | 401.0 | 12832 | 1.1733          | {'f1': 0.889592402057776}  | {'accuracy': 0.8884} |
| 0.0           | 402.0 | 12864 | 1.1735          | {'f1': 0.8892405063291139} | {'accuracy': 0.888}  |
| 0.0           | 403.0 | 12896 | 1.1731          | {'f1': 0.888888888888889}  | {'accuracy': 0.8876} |
| 0.0           | 404.0 | 12928 | 1.1707          | {'f1': 0.888713496448303}  | {'accuracy': 0.8872} |
| 0.0           | 405.0 | 12960 | 1.1709          | {'f1': 0.8891518737672585} | {'accuracy': 0.8876} |
| 0.0           | 406.0 | 12992 | 1.3069          | {'f1': 0.880922950144211}  | {'accuracy': 0.8844} |
| 0.0009        | 407.0 | 13024 | 1.1802          | {'f1': 0.8900398406374502} | {'accuracy': 0.8896} |
| 0.0009        | 408.0 | 13056 | 1.1781          | {'f1': 0.8914512922465209} | {'accuracy': 0.8908} |
| 0.0009        | 409.0 | 13088 | 1.1782          | {'f1': 0.8914512922465209} | {'accuracy': 0.8908} |
| 0.0009        | 410.0 | 13120 | 1.1784          | {'f1': 0.8914512922465209} | {'accuracy': 0.8908} |
| 0.0009        | 411.0 | 13152 | 1.1790          | {'f1': 0.8914512922465209} | {'accuracy': 0.8908} |
| 0.0009        | 412.0 | 13184 | 1.1791          | {'f1': 0.8914512922465209} | {'accuracy': 0.8908} |
| 0.0009        | 413.0 | 13216 | 1.1792          | {'f1': 0.8914512922465209} | {'accuracy': 0.8908} |
| 0.0009        | 414.0 | 13248 | 1.1793          | {'f1': 0.8914512922465209} | {'accuracy': 0.8908} |
| 0.0009        | 415.0 | 13280 | 1.1795          | {'f1': 0.8914512922465209} | {'accuracy': 0.8908} |
| 0.0009        | 416.0 | 13312 | 1.1796          | {'f1': 0.8914512922465209} | {'accuracy': 0.8908} |
| 0.0009        | 417.0 | 13344 | 1.1800          | {'f1': 0.8914512922465209} | {'accuracy': 0.8908} |
| 0.0009        | 418.0 | 13376 | 1.1803          | {'f1': 0.8914512922465209} | {'accuracy': 0.8908} |
| 0.0009        | 419.0 | 13408 | 1.1809          | {'f1': 0.8914512922465209} | {'accuracy': 0.8908} |
| 0.0009        | 420.0 | 13440 | 1.1823          | {'f1': 0.8910103420843277} | {'accuracy': 0.8904} |
| 0.0009        | 421.0 | 13472 | 1.1827          | {'f1': 0.8910103420843277} | {'accuracy': 0.8904} |
| 0.0           | 422.0 | 13504 | 1.1829          | {'f1': 0.8910103420843277} | {'accuracy': 0.8904} |
| 0.0           | 423.0 | 13536 | 1.1830          | {'f1': 0.8910103420843277} | {'accuracy': 0.8904} |
| 0.0           | 424.0 | 13568 | 1.1831          | {'f1': 0.8910103420843277} | {'accuracy': 0.8904} |
| 0.0           | 425.0 | 13600 | 1.1834          | {'f1': 0.8910103420843277} | {'accuracy': 0.8904} |
| 0.0           | 426.0 | 13632 | 1.1893          | {'f1': 0.8905750798722045} | {'accuracy': 0.8904} |
| 0.0           | 427.0 | 13664 | 1.1982          | {'f1': 0.891025641025641}  | {'accuracy': 0.8912} |
| 0.0           | 428.0 | 13696 | 1.1986          | {'f1': 0.891025641025641}  | {'accuracy': 0.8912} |
| 0.0           | 429.0 | 13728 | 1.1987          | {'f1': 0.891025641025641}  | {'accuracy': 0.8912} |
| 0.0           | 430.0 | 13760 | 1.1988          | {'f1': 0.891025641025641}  | {'accuracy': 0.8912} |
| 0.0           | 431.0 | 13792 | 1.1990          | {'f1': 0.891025641025641}  | {'accuracy': 0.8912} |
| 0.0           | 432.0 | 13824 | 1.1991          | {'f1': 0.8906688025630758} | {'accuracy': 0.8908} |
| 0.0           | 433.0 | 13856 | 1.1987          | {'f1': 0.8906688025630758} | {'accuracy': 0.8908} |
| 0.0           | 434.0 | 13888 | 1.1988          | {'f1': 0.8906688025630758} | {'accuracy': 0.8908} |
| 0.0           | 435.0 | 13920 | 1.1990          | {'f1': 0.8906688025630758} | {'accuracy': 0.8908} |
| 0.0           | 436.0 | 13952 | 1.1992          | {'f1': 0.8906688025630758} | {'accuracy': 0.8908} |
| 0.0           | 437.0 | 13984 | 1.1993          | {'f1': 0.8906688025630758} | {'accuracy': 0.8908} |
| 0.0           | 438.0 | 14016 | 1.1994          | {'f1': 0.8906688025630758} | {'accuracy': 0.8908} |
| 0.0           | 439.0 | 14048 | 1.1995          | {'f1': 0.8906688025630758} | {'accuracy': 0.8908} |
| 0.0           | 440.0 | 14080 | 1.1996          | {'f1': 0.8906688025630758} | {'accuracy': 0.8908} |
| 0.0           | 441.0 | 14112 | 1.1997          | {'f1': 0.8906688025630758} | {'accuracy': 0.8908} |
| 0.0           | 442.0 | 14144 | 1.2000          | {'f1': 0.8906688025630758} | {'accuracy': 0.8908} |
| 0.0           | 443.0 | 14176 | 1.2001          | {'f1': 0.8906688025630758} | {'accuracy': 0.8908} |
| 0.0           | 444.0 | 14208 | 1.2001          | {'f1': 0.8906688025630758} | {'accuracy': 0.8908} |
| 0.0           | 445.0 | 14240 | 1.2001          | {'f1': 0.8903122497998398} | {'accuracy': 0.8904} |
| 0.0           | 446.0 | 14272 | 1.2669          | {'f1': 0.8821603927986906} | {'accuracy': 0.8848} |
| 0.0           | 447.0 | 14304 | 1.3329          | {'f1': 0.8768595041322313} | {'accuracy': 0.8808} |
| 0.0           | 448.0 | 14336 | 1.3344          | {'f1': 0.8768595041322313} | {'accuracy': 0.8808} |
| 0.0           | 449.0 | 14368 | 1.3297          | {'f1': 0.8787128712871287} | {'accuracy': 0.8824} |
| 0.0           | 450.0 | 14400 | 1.3272          | {'f1': 0.8791752577319588} | {'accuracy': 0.8828} |
| 0.0           | 451.0 | 14432 | 1.3263          | {'f1': 0.8791752577319588} | {'accuracy': 0.8828} |
| 0.0           | 452.0 | 14464 | 1.3250          | {'f1': 0.8788128606760098} | {'accuracy': 0.8824} |
| 0.0           | 453.0 | 14496 | 1.3243          | {'f1': 0.8792748248866915} | {'accuracy': 0.8828} |
| 0.0           | 454.0 | 14528 | 1.3203          | {'f1': 0.8806584362139918} | {'accuracy': 0.884}  |
| 0.0           | 455.0 | 14560 | 1.3188          | {'f1': 0.8806584362139918} | {'accuracy': 0.884}  |
| 0.0           | 456.0 | 14592 | 1.3106          | {'f1': 0.8812166050143855} | {'accuracy': 0.8844} |
| 0.0           | 457.0 | 14624 | 1.3076          | {'f1': 0.8812166050143855} | {'accuracy': 0.8844} |
| 0.0           | 458.0 | 14656 | 1.3068          | {'f1': 0.8812166050143855} | {'accuracy': 0.8844} |
| 0.0           | 459.0 | 14688 | 1.3061          | {'f1': 0.8812166050143855} | {'accuracy': 0.8844} |
| 0.0           | 460.0 | 14720 | 1.3026          | {'f1': 0.8804928131416838} | {'accuracy': 0.8836} |
| 0.0           | 461.0 | 14752 | 1.3008          | {'f1': 0.8809523809523809} | {'accuracy': 0.884}  |
| 0.0           | 462.0 | 14784 | 1.3000          | {'f1': 0.8809523809523809} | {'accuracy': 0.884}  |
| 0.0           | 463.0 | 14816 | 1.2993          | {'f1': 0.8809523809523809} | {'accuracy': 0.884}  |
| 0.0           | 464.0 | 14848 | 1.2959          | {'f1': 0.8809523809523809} | {'accuracy': 0.884}  |
| 0.0           | 465.0 | 14880 | 1.2951          | {'f1': 0.8809523809523809} | {'accuracy': 0.884}  |
| 0.0           | 466.0 | 14912 | 1.2948          | {'f1': 0.8809523809523809} | {'accuracy': 0.884}  |
| 0.0           | 467.0 | 14944 | 1.2941          | {'f1': 0.8805908904390645} | {'accuracy': 0.8836} |
| 0.0           | 468.0 | 14976 | 1.2933          | {'f1': 0.8805908904390645} | {'accuracy': 0.8836} |
| 0.0           | 469.0 | 15008 | 1.2930          | {'f1': 0.8805908904390645} | {'accuracy': 0.8836} |
| 0.0           | 470.0 | 15040 | 1.2729          | {'f1': 0.8841761827079934} | {'accuracy': 0.8864} |
| 0.0           | 471.0 | 15072 | 1.2600          | {'f1': 0.8853658536585366} | {'accuracy': 0.8872} |
| 0.0           | 472.0 | 15104 | 1.2595          | {'f1': 0.8853658536585366} | {'accuracy': 0.8872} |
| 0.0           | 473.0 | 15136 | 1.2593          | {'f1': 0.8853658536585366} | {'accuracy': 0.8872} |
| 0.0           | 474.0 | 15168 | 1.2594          | {'f1': 0.8853658536585366} | {'accuracy': 0.8872} |
| 0.0           | 475.0 | 15200 | 1.2592          | {'f1': 0.8853658536585366} | {'accuracy': 0.8872} |
| 0.0           | 476.0 | 15232 | 1.2584          | {'f1': 0.8853658536585366} | {'accuracy': 0.8872} |
| 0.0           | 477.0 | 15264 | 1.2578          | {'f1': 0.8853658536585366} | {'accuracy': 0.8872} |
| 0.0           | 478.0 | 15296 | 1.2578          | {'f1': 0.8853658536585366} | {'accuracy': 0.8872} |
| 0.0           | 479.0 | 15328 | 1.2577          | {'f1': 0.8853658536585366} | {'accuracy': 0.8872} |
| 0.0           | 480.0 | 15360 | 1.2578          | {'f1': 0.8853658536585366} | {'accuracy': 0.8872} |
| 0.0           | 481.0 | 15392 | 1.2575          | {'f1': 0.8858187728565624} | {'accuracy': 0.8876} |
| 0.0           | 482.0 | 15424 | 1.2575          | {'f1': 0.8858187728565624} | {'accuracy': 0.8876} |
| 0.0           | 483.0 | 15456 | 1.2574          | {'f1': 0.8858187728565624} | {'accuracy': 0.8876} |
| 0.0           | 484.0 | 15488 | 1.2574          | {'f1': 0.8858187728565624} | {'accuracy': 0.8876} |
| 0.0           | 485.0 | 15520 | 1.2596          | {'f1': 0.8853658536585366} | {'accuracy': 0.8872} |
| 0.0           | 486.0 | 15552 | 1.2595          | {'f1': 0.8853658536585366} | {'accuracy': 0.8872} |
| 0.0           | 487.0 | 15584 | 1.2592          | {'f1': 0.8853658536585366} | {'accuracy': 0.8872} |
| 0.0           | 488.0 | 15616 | 1.2589          | {'f1': 0.8853658536585366} | {'accuracy': 0.8872} |
| 0.0           | 489.0 | 15648 | 1.2589          | {'f1': 0.8858187728565624} | {'accuracy': 0.8876} |
| 0.0           | 490.0 | 15680 | 1.2588          | {'f1': 0.8858187728565624} | {'accuracy': 0.8876} |
| 0.0           | 491.0 | 15712 | 1.2588          | {'f1': 0.8858187728565624} | {'accuracy': 0.8876} |
| 0.0           | 492.0 | 15744 | 1.2584          | {'f1': 0.8858187728565624} | {'accuracy': 0.8876} |
| 0.0           | 493.0 | 15776 | 1.2580          | {'f1': 0.8858187728565624} | {'accuracy': 0.8876} |
| 0.0           | 494.0 | 15808 | 1.2580          | {'f1': 0.8858187728565624} | {'accuracy': 0.8876} |
| 0.0           | 495.0 | 15840 | 1.2566          | {'f1': 0.8858187728565624} | {'accuracy': 0.8876} |
| 0.0           | 496.0 | 15872 | 1.2564          | {'f1': 0.8858187728565624} | {'accuracy': 0.8876} |
| 0.0           | 497.0 | 15904 | 1.2564          | {'f1': 0.8858187728565624} | {'accuracy': 0.8876} |
| 0.0           | 498.0 | 15936 | 1.2564          | {'f1': 0.8858187728565624} | {'accuracy': 0.8876} |
| 0.0           | 499.0 | 15968 | 1.2564          | {'f1': 0.8858187728565624} | {'accuracy': 0.8876} |
| 0.0           | 500.0 | 16000 | 1.2555          | {'f1': 0.8858187728565624} | {'accuracy': 0.8876} |


### Framework versions

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