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_2_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_2_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: 1.3242
- F1: {'f1': 0.8878243512974051}
- 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    | 0.6801          | {'f1': 0.253315649867374}  | {'accuracy': 0.5496} |
| No log        | 2.0   | 64    | 0.6567          | {'f1': 0.395820528580209}  | {'accuracy': 0.6068} |
| No log        | 3.0   | 96    | 0.5299          | {'f1': 0.7167362076958739} | {'accuracy': 0.7556} |
| No log        | 4.0   | 128   | 0.3719          | {'f1': 0.8450704225352113} | {'accuracy': 0.8416} |
| No log        | 5.0   | 160   | 0.3542          | {'f1': 0.8584795321637427} | {'accuracy': 0.8548} |
| No log        | 6.0   | 192   | 0.3509          | {'f1': 0.8587708587708587} | {'accuracy': 0.8612} |
| No log        | 7.0   | 224   | 0.3426          | {'f1': 0.8642370845014016} | {'accuracy': 0.8644} |
| No log        | 8.0   | 256   | 0.3844          | {'f1': 0.8569065343258891} | {'accuracy': 0.8616} |
| No log        | 9.0   | 288   | 0.3601          | {'f1': 0.8700696055684455} | {'accuracy': 0.8656} |
| No log        | 10.0  | 320   | 0.4025          | {'f1': 0.8663141993957705} | {'accuracy': 0.8584} |
| No log        | 11.0  | 352   | 0.4094          | {'f1': 0.8730600875447672} | {'accuracy': 0.8724} |
| No log        | 12.0  | 384   | 0.4316          | {'f1': 0.8725529364762286} | {'accuracy': 0.8724} |
| No log        | 13.0  | 416   | 0.4566          | {'f1': 0.8772763262074426} | {'accuracy': 0.876}  |
| No log        | 14.0  | 448   | 0.5450          | {'f1': 0.8553406223717409} | {'accuracy': 0.8624} |
| No log        | 15.0  | 480   | 0.4764          | {'f1': 0.8766692851531814} | {'accuracy': 0.8744} |
| 0.2904        | 16.0  | 512   | 0.5232          | {'f1': 0.8812600969305331} | {'accuracy': 0.8824} |
| 0.2904        | 17.0  | 544   | 0.5538          | {'f1': 0.8764302059496568} | {'accuracy': 0.8704} |
| 0.2904        | 18.0  | 576   | 0.5426          | {'f1': 0.8780487804878049} | {'accuracy': 0.874}  |
| 0.2904        | 19.0  | 608   | 0.5473          | {'f1': 0.876509544215037}  | {'accuracy': 0.8732} |
| 0.2904        | 20.0  | 640   | 0.5786          | {'f1': 0.8822605965463108} | {'accuracy': 0.88}   |
| 0.2904        | 21.0  | 672   | 0.6041          | {'f1': 0.883197516492045}  | {'accuracy': 0.8796} |
| 0.2904        | 22.0  | 704   | 0.6239          | {'f1': 0.8787061994609163} | {'accuracy': 0.874}  |
| 0.2904        | 23.0  | 736   | 0.6593          | {'f1': 0.881688018085908}  | {'accuracy': 0.8744} |
| 0.2904        | 24.0  | 768   | 0.6500          | {'f1': 0.882051282051282}  | {'accuracy': 0.8804} |
| 0.2904        | 25.0  | 800   | 0.7181          | {'f1': 0.8694581280788177} | {'accuracy': 0.8728} |
| 0.2904        | 26.0  | 832   | 0.6766          | {'f1': 0.8800940438871473} | {'accuracy': 0.8776} |
| 0.2904        | 27.0  | 864   | 0.7055          | {'f1': 0.8803789972364785} | {'accuracy': 0.8788} |
| 0.2904        | 28.0  | 896   | 0.7455          | {'f1': 0.876979293544458}  | {'accuracy': 0.8788} |
| 0.2904        | 29.0  | 928   | 0.7227          | {'f1': 0.8797443068318018} | {'accuracy': 0.8796} |
| 0.2904        | 30.0  | 960   | 0.7445          | {'f1': 0.8800635424940428} | {'accuracy': 0.8792} |
| 0.2904        | 31.0  | 992   | 0.7485          | {'f1': 0.884942084942085}  | {'accuracy': 0.8808} |
| 0.0294        | 32.0  | 1024  | 0.7603          | {'f1': 0.8833333333333332} | {'accuracy': 0.8824} |
| 0.0294        | 33.0  | 1056  | 0.7681          | {'f1': 0.8843700159489634} | {'accuracy': 0.884}  |
| 0.0294        | 34.0  | 1088  | 0.8303          | {'f1': 0.8727871552079044} | {'accuracy': 0.8764} |
| 0.0294        | 35.0  | 1120  | 0.8575          | {'f1': 0.8669991687448046} | {'accuracy': 0.872}  |
| 0.0294        | 36.0  | 1152  | 0.8227          | {'f1': 0.8755573571139035} | {'accuracy': 0.8772} |
| 0.0294        | 37.0  | 1184  | 0.8699          | {'f1': 0.8705302096177558} | {'accuracy': 0.874}  |
| 0.0294        | 38.0  | 1216  | 0.8056          | {'f1': 0.8847205939820243} | {'accuracy': 0.882}  |
| 0.0294        | 39.0  | 1248  | 0.8177          | {'f1': 0.8847058823529411} | {'accuracy': 0.8824} |
| 0.0294        | 40.0  | 1280  | 0.8988          | {'f1': 0.874031797798614}  | {'accuracy': 0.8764} |
| 0.0294        | 41.0  | 1312  | 0.9963          | {'f1': 0.8571428571428571} | {'accuracy': 0.8648} |
| 0.0294        | 42.0  | 1344  | 0.9049          | {'f1': 0.8857356235997013} | {'accuracy': 0.8776} |
| 0.0294        | 43.0  | 1376  | 0.8490          | {'f1': 0.8865820838139177} | {'accuracy': 0.882}  |
| 0.0294        | 44.0  | 1408  | 0.8760          | {'f1': 0.8744484556758926} | {'accuracy': 0.8748} |
| 0.0294        | 45.0  | 1440  | 1.0835          | {'f1': 0.8533561351004704} | {'accuracy': 0.8628} |
| 0.0294        | 46.0  | 1472  | 0.8930          | {'f1': 0.8805132317562148} | {'accuracy': 0.8808} |
| 0.0059        | 47.0  | 1504  | 0.9490          | {'f1': 0.8773507767784138} | {'accuracy': 0.88}   |
| 0.0059        | 48.0  | 1536  | 0.9000          | {'f1': 0.8845541401273885} | {'accuracy': 0.884}  |
| 0.0059        | 49.0  | 1568  | 0.9667          | {'f1': 0.8729055986922762} | {'accuracy': 0.8756} |
| 0.0059        | 50.0  | 1600  | 0.9061          | {'f1': 0.8838482596793117} | {'accuracy': 0.8812} |
| 0.0059        | 51.0  | 1632  | 0.9607          | {'f1': 0.8744412840308817} | {'accuracy': 0.8764} |
| 0.0059        | 52.0  | 1664  | 0.9181          | {'f1': 0.8868288914638857} | {'accuracy': 0.8828} |
| 0.0059        | 53.0  | 1696  | 0.9219          | {'f1': 0.88800949742778}   | {'accuracy': 0.8868} |
| 0.0059        | 54.0  | 1728  | 0.9399          | {'f1': 0.8876881512929371} | {'accuracy': 0.8836} |
| 0.0059        | 55.0  | 1760  | 0.9157          | {'f1': 0.888201160541586}  | {'accuracy': 0.8844} |
| 0.0059        | 56.0  | 1792  | 0.9330          | {'f1': 0.8840927258193446} | {'accuracy': 0.884}  |
| 0.0059        | 57.0  | 1824  | 0.9414          | {'f1': 0.8902392707937713} | {'accuracy': 0.8844} |
| 0.0059        | 58.0  | 1856  | 0.9542          | {'f1': 0.8764135702746365} | {'accuracy': 0.8776} |
| 0.0059        | 59.0  | 1888  | 0.9881          | {'f1': 0.8753056234718826} | {'accuracy': 0.8776} |
| 0.0059        | 60.0  | 1920  | 0.9599          | {'f1': 0.8808373590982287} | {'accuracy': 0.8816} |
| 0.0059        | 61.0  | 1952  | 0.9520          | {'f1': 0.8825651302605211} | {'accuracy': 0.8828} |
| 0.0059        | 62.0  | 1984  | 0.9344          | {'f1': 0.8832088084939048} | {'accuracy': 0.8812} |
| 0.0043        | 63.0  | 2016  | 0.9675          | {'f1': 0.8797748291113793} | {'accuracy': 0.8804} |
| 0.0043        | 64.0  | 2048  | 0.9444          | {'f1': 0.8871834228702994} | {'accuracy': 0.8824} |
| 0.0043        | 65.0  | 2080  | 0.9464          | {'f1': 0.882775119617225}  | {'accuracy': 0.8824} |
| 0.0043        | 66.0  | 2112  | 0.9734          | {'f1': 0.8813559322033898} | {'accuracy': 0.8824} |
| 0.0043        | 67.0  | 2144  | 0.9715          | {'f1': 0.8827309236947791} | {'accuracy': 0.8832} |
| 0.0043        | 68.0  | 2176  | 0.9423          | {'f1': 0.8898539281484406} | {'accuracy': 0.8884} |
| 0.0043        | 69.0  | 2208  | 0.9447          | {'f1': 0.886983632112237}  | {'accuracy': 0.884}  |
| 0.0043        | 70.0  | 2240  | 0.9595          | {'f1': 0.8885448916408668} | {'accuracy': 0.8848} |
| 0.0043        | 71.0  | 2272  | 0.9721          | {'f1': 0.8872180451127819} | {'accuracy': 0.886}  |
| 0.0043        | 72.0  | 2304  | 0.9750          | {'f1': 0.8873072360616844} | {'accuracy': 0.886}  |
| 0.0043        | 73.0  | 2336  | 1.0369          | {'f1': 0.8771358828315704} | {'accuracy': 0.8792} |
| 0.0043        | 74.0  | 2368  | 1.0656          | {'f1': 0.8744339234252778} | {'accuracy': 0.878}  |
| 0.0043        | 75.0  | 2400  | 1.0304          | {'f1': 0.88}               | {'accuracy': 0.8812} |
| 0.0043        | 76.0  | 2432  | 1.0651          | {'f1': 0.8744872846595569} | {'accuracy': 0.8776} |
| 0.0043        | 77.0  | 2464  | 1.0023          | {'f1': 0.8921374950612406} | {'accuracy': 0.8908} |
| 0.0043        | 78.0  | 2496  | 0.9992          | {'f1': 0.8890643505724438} | {'accuracy': 0.8876} |
| 0.0031        | 79.0  | 2528  | 0.9912          | {'f1': 0.8864696734059099} | {'accuracy': 0.8832} |
| 0.0031        | 80.0  | 2560  | 1.0876          | {'f1': 0.8821999256781866} | {'accuracy': 0.8732} |
| 0.0031        | 81.0  | 2592  | 1.0018          | {'f1': 0.887009992313605}  | {'accuracy': 0.8824} |
| 0.0031        | 82.0  | 2624  | 1.0475          | {'f1': 0.8773055332798717} | {'accuracy': 0.8776} |
| 0.0031        | 83.0  | 2656  | 1.0269          | {'f1': 0.8855445544554456} | {'accuracy': 0.8844} |
| 0.0031        | 84.0  | 2688  | 1.0180          | {'f1': 0.8863456985003947} | {'accuracy': 0.8848} |
| 0.0031        | 85.0  | 2720  | 1.2762          | {'f1': 0.8522483940042828} | {'accuracy': 0.862}  |
| 0.0031        | 86.0  | 2752  | 1.0328          | {'f1': 0.8823064770932069} | {'accuracy': 0.8808} |
| 0.0031        | 87.0  | 2784  | 1.0338          | {'f1': 0.8841201716738198} | {'accuracy': 0.8812} |
| 0.0031        | 88.0  | 2816  | 1.0630          | {'f1': 0.8797876374668184} | {'accuracy': 0.8732} |
| 0.0031        | 89.0  | 2848  | 1.0467          | {'f1': 0.8803180914512924} | {'accuracy': 0.8796} |
| 0.0031        | 90.0  | 2880  | 1.0381          | {'f1': 0.8824921135646688} | {'accuracy': 0.8808} |
| 0.0031        | 91.0  | 2912  | 1.1350          | {'f1': 0.8735632183908045} | {'accuracy': 0.8768} |
| 0.0031        | 92.0  | 2944  | 1.2254          | {'f1': 0.8589527027027027} | {'accuracy': 0.8664} |
| 0.0031        | 93.0  | 2976  | 1.0737          | {'f1': 0.879415347137637}  | {'accuracy': 0.8812} |
| 0.0079        | 94.0  | 3008  | 1.0254          | {'f1': 0.8832204065364686} | {'accuracy': 0.8828} |
| 0.0079        | 95.0  | 3040  | 1.0451          | {'f1': 0.8829190056134724} | {'accuracy': 0.8832} |
| 0.0079        | 96.0  | 3072  | 1.0376          | {'f1': 0.8876058506543494} | {'accuracy': 0.8832} |
| 0.0079        | 97.0  | 3104  | 1.0467          | {'f1': 0.8867562380038387} | {'accuracy': 0.882}  |
| 0.0079        | 98.0  | 3136  | 1.0908          | {'f1': 0.8808080808080808} | {'accuracy': 0.882}  |
| 0.0079        | 99.0  | 3168  | 1.1546          | {'f1': 0.8797047970479704} | {'accuracy': 0.8696} |
| 0.0079        | 100.0 | 3200  | 1.0611          | {'f1': 0.8873239436619718} | {'accuracy': 0.8848} |
| 0.0079        | 101.0 | 3232  | 1.1234          | {'f1': 0.872815928484356}  | {'accuracy': 0.8748} |
| 0.0079        | 102.0 | 3264  | 1.0708          | {'f1': 0.8848146671980869} | {'accuracy': 0.8844} |
| 0.0079        | 103.0 | 3296  | 1.4289          | {'f1': 0.8423344947735192} | {'accuracy': 0.8552} |
| 0.0079        | 104.0 | 3328  | 1.0982          | {'f1': 0.877079107505071}  | {'accuracy': 0.8788} |
| 0.0079        | 105.0 | 3360  | 1.2706          | {'f1': 0.8601784955376116} | {'accuracy': 0.8684} |
| 0.0079        | 106.0 | 3392  | 1.0504          | {'f1': 0.8805433479824213} | {'accuracy': 0.8804} |
| 0.0079        | 107.0 | 3424  | 1.0664          | {'f1': 0.8819725141471302} | {'accuracy': 0.8832} |
| 0.0079        | 108.0 | 3456  | 1.0435          | {'f1': 0.8888888888888888} | {'accuracy': 0.8836} |
| 0.0079        | 109.0 | 3488  | 1.0634          | {'f1': 0.878775674587193}  | {'accuracy': 0.8796} |
| 0.0038        | 110.0 | 3520  | 1.0531          | {'f1': 0.8879605013292824} | {'accuracy': 0.882}  |
| 0.0038        | 111.0 | 3552  | 1.1024          | {'f1': 0.8788732394366197} | {'accuracy': 0.8796} |
| 0.0038        | 112.0 | 3584  | 1.1009          | {'f1': 0.8837209302325582} | {'accuracy': 0.88}   |
| 0.0038        | 113.0 | 3616  | 1.1039          | {'f1': 0.885195206803247}  | {'accuracy': 0.8812} |
| 0.0038        | 114.0 | 3648  | 1.1037          | {'f1': 0.8848390849166343} | {'accuracy': 0.8812} |
| 0.0038        | 115.0 | 3680  | 1.3680          | {'f1': 0.846483704974271}  | {'accuracy': 0.8568} |
| 0.0038        | 116.0 | 3712  | 1.1014          | {'f1': 0.8790259230164964} | {'accuracy': 0.8768} |
| 0.0038        | 117.0 | 3744  | 1.1115          | {'f1': 0.8753507014028056} | {'accuracy': 0.8756} |
| 0.0038        | 118.0 | 3776  | 1.1046          | {'f1': 0.8777152051488336} | {'accuracy': 0.8784} |
| 0.0038        | 119.0 | 3808  | 1.3210          | {'f1': 0.8581109699279966} | {'accuracy': 0.866}  |
| 0.0038        | 120.0 | 3840  | 1.1407          | {'f1': 0.877001171417415}  | {'accuracy': 0.874}  |
| 0.0038        | 121.0 | 3872  | 1.2861          | {'f1': 0.873992673992674}  | {'accuracy': 0.8624} |
| 0.0038        | 122.0 | 3904  | 1.4529          | {'f1': 0.8476764199655766} | {'accuracy': 0.8584} |
| 0.0038        | 123.0 | 3936  | 1.1866          | {'f1': 0.8746968472109943} | {'accuracy': 0.876}  |
| 0.0038        | 124.0 | 3968  | 1.1406          | {'f1': 0.8884585592563905} | {'accuracy': 0.8848} |
| 0.0043        | 125.0 | 4000  | 1.2049          | {'f1': 0.8772357723577234} | {'accuracy': 0.8792} |
| 0.0043        | 126.0 | 4032  | 1.1289          | {'f1': 0.8919129082426128} | {'accuracy': 0.8888} |
| 0.0043        | 127.0 | 4064  | 1.1299          | {'f1': 0.8917445482866044} | {'accuracy': 0.8888} |
| 0.0043        | 128.0 | 4096  | 1.1307          | {'f1': 0.8919235271166601} | {'accuracy': 0.8892} |
| 0.0043        | 129.0 | 4128  | 1.1318          | {'f1': 0.8897576231430805} | {'accuracy': 0.8872} |
| 0.0043        | 130.0 | 4160  | 1.1481          | {'f1': 0.8857142857142859} | {'accuracy': 0.8848} |
| 0.0043        | 131.0 | 4192  | 1.1503          | {'f1': 0.8857142857142859} | {'accuracy': 0.8848} |
| 0.0043        | 132.0 | 4224  | 1.1934          | {'f1': 0.8803556992724333} | {'accuracy': 0.8816} |
| 0.0043        | 133.0 | 4256  | 1.1931          | {'f1': 0.88}               | {'accuracy': 0.8812} |
| 0.0043        | 134.0 | 4288  | 1.1904          | {'f1': 0.8804523424878836} | {'accuracy': 0.8816} |
| 0.0043        | 135.0 | 4320  | 1.1773          | {'f1': 0.8826366559485529} | {'accuracy': 0.8832} |
| 0.0043        | 136.0 | 4352  | 1.1680          | {'f1': 0.8852459016393444} | {'accuracy': 0.8852} |
| 0.0043        | 137.0 | 4384  | 1.1401          | {'f1': 0.8869701726844584} | {'accuracy': 0.8848} |
| 0.0043        | 138.0 | 4416  | 1.1414          | {'f1': 0.8846761453396524} | {'accuracy': 0.8832} |
| 0.0043        | 139.0 | 4448  | 1.4003          | {'f1': 0.8530038346825735} | {'accuracy': 0.862}  |
| 0.0043        | 140.0 | 4480  | 1.1447          | {'f1': 0.8835182250396196} | {'accuracy': 0.8824} |
| 0.0007        | 141.0 | 4512  | 1.2298          | {'f1': 0.8708094848732624} | {'accuracy': 0.8736} |
| 0.0007        | 142.0 | 4544  | 1.1491          | {'f1': 0.8894026974951831} | {'accuracy': 0.8852} |
| 0.0007        | 143.0 | 4576  | 1.1352          | {'f1': 0.88984375}         | {'accuracy': 0.8872} |
| 0.0007        | 144.0 | 4608  | 1.2173          | {'f1': 0.876523151909017}  | {'accuracy': 0.8784} |
| 0.0007        | 145.0 | 4640  | 1.1757          | {'f1': 0.8833667334669338} | {'accuracy': 0.8836} |
| 0.0007        | 146.0 | 4672  | 1.4335          | {'f1': 0.84796573875803}   | {'accuracy': 0.858}  |
| 0.0007        | 147.0 | 4704  | 1.5681          | {'f1': 0.8419689119170984} | {'accuracy': 0.8536} |
| 0.0007        | 148.0 | 4736  | 1.1316          | {'f1': 0.8892367906066537} | {'accuracy': 0.8868} |
| 0.0007        | 149.0 | 4768  | 1.1266          | {'f1': 0.8906189178668742} | {'accuracy': 0.8876} |
| 0.0007        | 150.0 | 4800  | 1.1379          | {'f1': 0.889063729346971}  | {'accuracy': 0.8872} |
| 0.0007        | 151.0 | 4832  | 1.1267          | {'f1': 0.8905336969224776} | {'accuracy': 0.8876} |
| 0.0007        | 152.0 | 4864  | 1.1140          | {'f1': 0.8882791062328498} | {'accuracy': 0.886}  |
| 0.0007        | 153.0 | 4896  | 1.1807          | {'f1': 0.8810679611650486} | {'accuracy': 0.8824} |
| 0.0007        | 154.0 | 4928  | 1.1753          | {'f1': 0.8841512469831053} | {'accuracy': 0.8848} |
| 0.0007        | 155.0 | 4960  | 1.3370          | {'f1': 0.8694929343308396} | {'accuracy': 0.8744} |
| 0.0007        | 156.0 | 4992  | 1.2215          | {'f1': 0.8846153846153846} | {'accuracy': 0.8848} |
| 0.0042        | 157.0 | 5024  | 1.3197          | {'f1': 0.8734593262119967} | {'accuracy': 0.8768} |
| 0.0042        | 158.0 | 5056  | 1.1845          | {'f1': 0.8859375}          | {'accuracy': 0.8832} |
| 0.0042        | 159.0 | 5088  | 1.1096          | {'f1': 0.8882812499999999} | {'accuracy': 0.8856} |
| 0.0042        | 160.0 | 5120  | 1.2496          | {'f1': 0.8753599341834636} | {'accuracy': 0.8788} |
| 0.0042        | 161.0 | 5152  | 1.1503          | {'f1': 0.8868742609381159} | {'accuracy': 0.8852} |
| 0.0042        | 162.0 | 5184  | 1.2286          | {'f1': 0.8748461222814937} | {'accuracy': 0.878}  |
| 0.0042        | 163.0 | 5216  | 1.1418          | {'f1': 0.888015717092338}  | {'accuracy': 0.886}  |
| 0.0042        | 164.0 | 5248  | 1.1096          | {'f1': 0.8815344114328695} | {'accuracy': 0.874}  |
| 0.0042        | 165.0 | 5280  | 1.2758          | {'f1': 0.8567828643427131} | {'accuracy': 0.8636} |
| 0.0042        | 166.0 | 5312  | 1.1868          | {'f1': 0.8718991459943066} | {'accuracy': 0.874}  |
| 0.0042        | 167.0 | 5344  | 1.1437          | {'f1': 0.8828685258964143} | {'accuracy': 0.8824} |
| 0.0042        | 168.0 | 5376  | 1.1945          | {'f1': 0.8734793187347932} | {'accuracy': 0.8752} |
| 0.0042        | 169.0 | 5408  | 1.2188          | {'f1': 0.8728606356968216} | {'accuracy': 0.8752} |
| 0.0042        | 170.0 | 5440  | 1.1677          | {'f1': 0.8786173633440514} | {'accuracy': 0.8792} |
| 0.0042        | 171.0 | 5472  | 1.1273          | {'f1': 0.8863366336633663} | {'accuracy': 0.8852} |
| 0.0056        | 172.0 | 5504  | 1.6021          | {'f1': 0.8369042413642326} | {'accuracy': 0.8508} |
| 0.0056        | 173.0 | 5536  | 1.1175          | {'f1': 0.8892355694227769} | {'accuracy': 0.8864} |
| 0.0056        | 174.0 | 5568  | 1.1510          | {'f1': 0.8846307385229542} | {'accuracy': 0.8844} |
| 0.0056        | 175.0 | 5600  | 1.1517          | {'f1': 0.8850758180367119} | {'accuracy': 0.8848} |
| 0.0056        | 176.0 | 5632  | 1.1507          | {'f1': 0.8853503184713376} | {'accuracy': 0.8848} |
| 0.0056        | 177.0 | 5664  | 1.1483          | {'f1': 0.886327503974563}  | {'accuracy': 0.8856} |
| 0.0056        | 178.0 | 5696  | 1.1462          | {'f1': 0.8873015873015873} | {'accuracy': 0.8864} |
| 0.0056        | 179.0 | 5728  | 1.1448          | {'f1': 0.88800949742778}   | {'accuracy': 0.8868} |
| 0.0056        | 180.0 | 5760  | 1.1447          | {'f1': 0.8877470355731224} | {'accuracy': 0.8864} |
| 0.0056        | 181.0 | 5792  | 1.1450          | {'f1': 0.8890643505724438} | {'accuracy': 0.8876} |
| 0.0056        | 182.0 | 5824  | 1.1452          | {'f1': 0.8888012618296529} | {'accuracy': 0.8872} |
| 0.0056        | 183.0 | 5856  | 1.1457          | {'f1': 0.8877510831035841} | {'accuracy': 0.886}  |
| 0.0056        | 184.0 | 5888  | 1.1459          | {'f1': 0.8867033831628639} | {'accuracy': 0.8848} |
| 0.0056        | 185.0 | 5920  | 1.1458          | {'f1': 0.8886283704572098} | {'accuracy': 0.886}  |
| 0.0056        | 186.0 | 5952  | 1.1269          | {'f1': 0.8888024883359252} | {'accuracy': 0.8856} |
| 0.0056        | 187.0 | 5984  | 1.3035          | {'f1': 0.8672199170124482} | {'accuracy': 0.872}  |
| 0.002         | 188.0 | 6016  | 1.2137          | {'f1': 0.877079107505071}  | {'accuracy': 0.8788} |
| 0.002         | 189.0 | 6048  | 1.3514          | {'f1': 0.8625472887767969} | {'accuracy': 0.8692} |
| 0.002         | 190.0 | 6080  | 1.2185          | {'f1': 0.8781478472786353} | {'accuracy': 0.88}   |
| 0.002         | 191.0 | 6112  | 1.1993          | {'f1': 0.8806451612903226} | {'accuracy': 0.8816} |
| 0.002         | 192.0 | 6144  | 1.1725          | {'f1': 0.8820023837902266} | {'accuracy': 0.8812} |
| 0.002         | 193.0 | 6176  | 1.1671          | {'f1': 0.8856351404827859} | {'accuracy': 0.8844} |
| 0.002         | 194.0 | 6208  | 1.1685          | {'f1': 0.8856351404827859} | {'accuracy': 0.8844} |
| 0.002         | 195.0 | 6240  | 1.1685          | {'f1': 0.8852848101265822} | {'accuracy': 0.884}  |
| 0.002         | 196.0 | 6272  | 1.1690          | {'f1': 0.8849347568208779} | {'accuracy': 0.8836} |
| 0.002         | 197.0 | 6304  | 1.1698          | {'f1': 0.8853754940711464} | {'accuracy': 0.884}  |
| 0.002         | 198.0 | 6336  | 1.1613          | {'f1': 0.8888027896164277} | {'accuracy': 0.8852} |
| 0.002         | 199.0 | 6368  | 1.1632          | {'f1': 0.8887165568049632} | {'accuracy': 0.8852} |
| 0.002         | 200.0 | 6400  | 1.1649          | {'f1': 0.8884570540225418} | {'accuracy': 0.8852} |
| 0.002         | 201.0 | 6432  | 1.1700          | {'f1': 0.8881064162754304} | {'accuracy': 0.8856} |
| 0.002         | 202.0 | 6464  | 1.1710          | {'f1': 0.8881064162754304} | {'accuracy': 0.8856} |
| 0.002         | 203.0 | 6496  | 1.1712          | {'f1': 0.8888021849395241} | {'accuracy': 0.886}  |
| 0.0007        | 204.0 | 6528  | 1.1717          | {'f1': 0.8891481913652275} | {'accuracy': 0.886}  |
| 0.0007        | 205.0 | 6560  | 1.1735          | {'f1': 0.8898404048267808} | {'accuracy': 0.8868} |
| 0.0007        | 206.0 | 6592  | 1.1765          | {'f1': 0.8885412592882284} | {'accuracy': 0.886}  |
| 0.0007        | 207.0 | 6624  | 1.1632          | {'f1': 0.8884585592563905} | {'accuracy': 0.8848} |
| 0.0007        | 208.0 | 6656  | 1.2059          | {'f1': 0.8844301765650081} | {'accuracy': 0.8848} |
| 0.0007        | 209.0 | 6688  | 1.2399          | {'f1': 0.8796108633968382} | {'accuracy': 0.8812} |
| 0.0007        | 210.0 | 6720  | 1.1880          | {'f1': 0.886695617844453}  | {'accuracy': 0.8852} |
| 0.0007        | 211.0 | 6752  | 1.1950          | {'f1': 0.8837209302325582} | {'accuracy': 0.884}  |
| 0.0007        | 212.0 | 6784  | 1.2185          | {'f1': 0.881807180314643}  | {'accuracy': 0.8828} |
| 0.0007        | 213.0 | 6816  | 1.1661          | {'f1': 0.8890631125049}    | {'accuracy': 0.8868} |
| 0.0007        | 214.0 | 6848  | 1.1673          | {'f1': 0.8891500195848022} | {'accuracy': 0.8868} |
| 0.0007        | 215.0 | 6880  | 1.1680          | {'f1': 0.8891500195848022} | {'accuracy': 0.8868} |
| 0.0007        | 216.0 | 6912  | 1.1734          | {'f1': 0.888803680981595}  | {'accuracy': 0.884}  |
| 0.0007        | 217.0 | 6944  | 1.4699          | {'f1': 0.8498074454428755} | {'accuracy': 0.8596} |
| 0.0007        | 218.0 | 6976  | 1.1855          | {'f1': 0.8843537414965986} | {'accuracy': 0.8844} |
| 0.0037        | 219.0 | 7008  | 1.2561          | {'f1': 0.8786885245901639} | {'accuracy': 0.8816} |
| 0.0037        | 220.0 | 7040  | 1.1845          | {'f1': 0.8856}             | {'accuracy': 0.8856} |
| 0.0037        | 221.0 | 7072  | 1.1786          | {'f1': 0.8925683480939546} | {'accuracy': 0.8884} |
| 0.0037        | 222.0 | 7104  | 1.2261          | {'f1': 0.8869824692278999} | {'accuracy': 0.8788} |
| 0.0037        | 223.0 | 7136  | 1.0965          | {'f1': 0.895800933125972}  | {'accuracy': 0.8928} |
| 0.0037        | 224.0 | 7168  | 1.1055          | {'f1': 0.8972254787026182} | {'accuracy': 0.8948} |
| 0.0037        | 225.0 | 7200  | 1.1074          | {'f1': 0.8972254787026182} | {'accuracy': 0.8948} |
| 0.0037        | 226.0 | 7232  | 1.1081          | {'f1': 0.8972254787026182} | {'accuracy': 0.8948} |
| 0.0037        | 227.0 | 7264  | 1.1086          | {'f1': 0.8972254787026182} | {'accuracy': 0.8948} |
| 0.0037        | 228.0 | 7296  | 1.1093          | {'f1': 0.8972254787026182} | {'accuracy': 0.8948} |
| 0.0037        | 229.0 | 7328  | 1.1479          | {'f1': 0.8943089430894309} | {'accuracy': 0.8908} |
| 0.0037        | 230.0 | 7360  | 1.1838          | {'f1': 0.8961287849750863} | {'accuracy': 0.8916} |
| 0.0037        | 231.0 | 7392  | 1.1900          | {'f1': 0.88844779674474}   | {'accuracy': 0.8876} |
| 0.0037        | 232.0 | 7424  | 1.2006          | {'f1': 0.8871160749900279} | {'accuracy': 0.8868} |
| 0.0037        | 233.0 | 7456  | 1.1976          | {'f1': 0.8885350318471337} | {'accuracy': 0.888}  |
| 0.0037        | 234.0 | 7488  | 1.1989          | {'f1': 0.8885350318471337} | {'accuracy': 0.888}  |
| 0.001         | 235.0 | 7520  | 1.2070          | {'f1': 0.8869356771873751} | {'accuracy': 0.8868} |
| 0.001         | 236.0 | 7552  | 1.2039          | {'f1': 0.8880031885213233} | {'accuracy': 0.8876} |
| 0.001         | 237.0 | 7584  | 1.2489          | {'f1': 0.8847703464947623} | {'accuracy': 0.8856} |
| 0.001         | 238.0 | 7616  | 1.2148          | {'f1': 0.8870259481037924} | {'accuracy': 0.8868} |
| 0.001         | 239.0 | 7648  | 1.2124          | {'f1': 0.8875598086124402} | {'accuracy': 0.8872} |
| 0.001         | 240.0 | 7680  | 1.2101          | {'f1': 0.8872958980485861} | {'accuracy': 0.8868} |
| 0.001         | 241.0 | 7712  | 1.2097          | {'f1': 0.8873855949064863} | {'accuracy': 0.8868} |
| 0.001         | 242.0 | 7744  | 1.1971          | {'f1': 0.8904705417160934} | {'accuracy': 0.8892} |
| 0.001         | 243.0 | 7776  | 1.1938          | {'f1': 0.8904649330181245} | {'accuracy': 0.8888} |
| 0.001         | 244.0 | 7808  | 1.1943          | {'f1': 0.8904649330181245} | {'accuracy': 0.8888} |
| 0.001         | 245.0 | 7840  | 1.1946          | {'f1': 0.8904649330181245} | {'accuracy': 0.8888} |
| 0.001         | 246.0 | 7872  | 1.1947          | {'f1': 0.889763779527559}  | {'accuracy': 0.888}  |
| 0.001         | 247.0 | 7904  | 1.2003          | {'f1': 0.8901185770750989} | {'accuracy': 0.8888} |
| 0.001         | 248.0 | 7936  | 1.5536          | {'f1': 0.8567774936061381} | {'accuracy': 0.8656} |
| 0.001         | 249.0 | 7968  | 1.2369          | {'f1': 0.8808545603944125} | {'accuracy': 0.884}  |
| 0.0021        | 250.0 | 8000  | 1.0997          | {'f1': 0.8914151313210507} | {'accuracy': 0.8892} |
| 0.0021        | 251.0 | 8032  | 1.1467          | {'f1': 0.8901229670765569} | {'accuracy': 0.8892} |
| 0.0021        | 252.0 | 8064  | 1.1309          | {'f1': 0.8917881811204912} | {'accuracy': 0.8872} |
| 0.0021        | 253.0 | 8096  | 1.5785          | {'f1': 0.8459530026109662} | {'accuracy': 0.8584} |
| 0.0021        | 254.0 | 8128  | 1.1817          | {'f1': 0.8932496075353219} | {'accuracy': 0.8912} |
| 0.0021        | 255.0 | 8160  | 1.1772          | {'f1': 0.8959560266980763} | {'accuracy': 0.894}  |
| 0.0021        | 256.0 | 8192  | 1.5157          | {'f1': 0.8593548387096775} | {'accuracy': 0.8692} |
| 0.0021        | 257.0 | 8224  | 1.3212          | {'f1': 0.876802637000412}  | {'accuracy': 0.8804} |
| 0.0021        | 258.0 | 8256  | 1.3042          | {'f1': 0.8783894823336073} | {'accuracy': 0.8816} |
| 0.0021        | 259.0 | 8288  | 1.1638          | {'f1': 0.8904593639575972} | {'accuracy': 0.8884} |
| 0.0021        | 260.0 | 8320  | 1.1825          | {'f1': 0.8894117647058823} | {'accuracy': 0.8872} |
| 0.0021        | 261.0 | 8352  | 1.2914          | {'f1': 0.8802931596091206} | {'accuracy': 0.8824} |
| 0.0021        | 262.0 | 8384  | 1.2355          | {'f1': 0.8896853843090401} | {'accuracy': 0.8892} |
| 0.0021        | 263.0 | 8416  | 1.2343          | {'f1': 0.8893312101910829} | {'accuracy': 0.8888} |
| 0.0021        | 264.0 | 8448  | 1.2358          | {'f1': 0.8893312101910829} | {'accuracy': 0.8888} |
| 0.0021        | 265.0 | 8480  | 1.2360          | {'f1': 0.8893312101910829} | {'accuracy': 0.8888} |
| 0.0024        | 266.0 | 8512  | 1.2368          | {'f1': 0.8893312101910829} | {'accuracy': 0.8888} |
| 0.0024        | 267.0 | 8544  | 1.2375          | {'f1': 0.8893312101910829} | {'accuracy': 0.8888} |
| 0.0024        | 268.0 | 8576  | 1.2349          | {'f1': 0.8898608349900597} | {'accuracy': 0.8892} |
| 0.0024        | 269.0 | 8608  | 1.2160          | {'f1': 0.8925180402582605} | {'accuracy': 0.8868} |
| 0.0024        | 270.0 | 8640  | 1.3519          | {'f1': 0.8769922353902738} | {'accuracy': 0.8796} |
| 0.0024        | 271.0 | 8672  | 1.3701          | {'f1': 0.8771498771498771} | {'accuracy': 0.88}   |
| 0.0024        | 272.0 | 8704  | 1.3574          | {'f1': 0.8784665579119086} | {'accuracy': 0.8808} |
| 0.0024        | 273.0 | 8736  | 1.3564          | {'f1': 0.8789237668161436} | {'accuracy': 0.8812} |
| 0.0024        | 274.0 | 8768  | 1.3554          | {'f1': 0.8789237668161436} | {'accuracy': 0.8812} |
| 0.0024        | 275.0 | 8800  | 1.3547          | {'f1': 0.8789237668161436} | {'accuracy': 0.8812} |
| 0.0024        | 276.0 | 8832  | 1.3524          | {'f1': 0.8790224032586559} | {'accuracy': 0.8812} |
| 0.0024        | 277.0 | 8864  | 1.3515          | {'f1': 0.8790224032586559} | {'accuracy': 0.8812} |
| 0.0024        | 278.0 | 8896  | 1.3154          | {'f1': 0.8849557522123893} | {'accuracy': 0.8856} |
| 0.0024        | 279.0 | 8928  | 1.3096          | {'f1': 0.8861267040898154} | {'accuracy': 0.8864} |
| 0.0024        | 280.0 | 8960  | 1.3097          | {'f1': 0.8865731462925852} | {'accuracy': 0.8868} |
| 0.0024        | 281.0 | 8992  | 1.3094          | {'f1': 0.8874649579495395} | {'accuracy': 0.8876} |
| 0.0           | 282.0 | 9024  | 1.3096          | {'f1': 0.8874649579495395} | {'accuracy': 0.8876} |
| 0.0           | 283.0 | 9056  | 1.3097          | {'f1': 0.8867547018807522} | {'accuracy': 0.8868} |
| 0.0           | 284.0 | 9088  | 1.3096          | {'f1': 0.8876449420231907} | {'accuracy': 0.8876} |
| 0.0           | 285.0 | 9120  | 1.3098          | {'f1': 0.8876449420231907} | {'accuracy': 0.8876} |
| 0.0           | 286.0 | 9152  | 1.3097          | {'f1': 0.8876449420231907} | {'accuracy': 0.8876} |
| 0.0           | 287.0 | 9184  | 1.3098          | {'f1': 0.8876449420231907} | {'accuracy': 0.8876} |
| 0.0           | 288.0 | 9216  | 1.3100          | {'f1': 0.8876449420231907} | {'accuracy': 0.8876} |
| 0.0           | 289.0 | 9248  | 1.3102          | {'f1': 0.8876449420231907} | {'accuracy': 0.8876} |
| 0.0           | 290.0 | 9280  | 1.3103          | {'f1': 0.8872901678657075} | {'accuracy': 0.8872} |
| 0.0           | 291.0 | 9312  | 1.3107          | {'f1': 0.8869356771873751} | {'accuracy': 0.8868} |
| 0.0           | 292.0 | 9344  | 1.3110          | {'f1': 0.8869356771873751} | {'accuracy': 0.8868} |
| 0.0           | 293.0 | 9376  | 1.3210          | {'f1': 0.8861267040898154} | {'accuracy': 0.8864} |
| 0.0           | 294.0 | 9408  | 1.3223          | {'f1': 0.8856799037304453} | {'accuracy': 0.886}  |
| 0.0           | 295.0 | 9440  | 1.3209          | {'f1': 0.8870192307692307} | {'accuracy': 0.8872} |
| 0.0           | 296.0 | 9472  | 1.3204          | {'f1': 0.8872}             | {'accuracy': 0.8872} |
| 0.0           | 297.0 | 9504  | 1.3208          | {'f1': 0.8872}             | {'accuracy': 0.8872} |
| 0.0           | 298.0 | 9536  | 1.3210          | {'f1': 0.8872}             | {'accuracy': 0.8872} |
| 0.0           | 299.0 | 9568  | 1.3215          | {'f1': 0.8876449420231907} | {'accuracy': 0.8876} |
| 0.0           | 300.0 | 9600  | 1.3208          | {'f1': 0.8872901678657075} | {'accuracy': 0.8872} |
| 0.0           | 301.0 | 9632  | 1.3199          | {'f1': 0.8869356771873751} | {'accuracy': 0.8868} |
| 0.0           | 302.0 | 9664  | 1.3201          | {'f1': 0.8870259481037924} | {'accuracy': 0.8868} |
| 0.0           | 303.0 | 9696  | 1.3205          | {'f1': 0.8870259481037924} | {'accuracy': 0.8868} |
| 0.0           | 304.0 | 9728  | 1.3208          | {'f1': 0.8870259481037924} | {'accuracy': 0.8868} |
| 0.0           | 305.0 | 9760  | 1.3212          | {'f1': 0.8870259481037924} | {'accuracy': 0.8868} |
| 0.0           | 306.0 | 9792  | 1.3216          | {'f1': 0.8870259481037924} | {'accuracy': 0.8868} |
| 0.0           | 307.0 | 9824  | 1.3220          | {'f1': 0.8870259481037924} | {'accuracy': 0.8868} |
| 0.0           | 308.0 | 9856  | 1.3225          | {'f1': 0.8870259481037924} | {'accuracy': 0.8868} |
| 0.0           | 309.0 | 9888  | 1.3230          | {'f1': 0.8870259481037924} | {'accuracy': 0.8868} |
| 0.0           | 310.0 | 9920  | 1.3231          | {'f1': 0.8859649122807017} | {'accuracy': 0.8856} |
| 0.0           | 311.0 | 9952  | 1.3233          | {'f1': 0.8859649122807017} | {'accuracy': 0.8856} |
| 0.0           | 312.0 | 9984  | 1.3239          | {'f1': 0.8859649122807017} | {'accuracy': 0.8856} |
| 0.0           | 313.0 | 10016 | 1.3244          | {'f1': 0.885611797528896}  | {'accuracy': 0.8852} |
| 0.0           | 314.0 | 10048 | 1.3247          | {'f1': 0.885611797528896}  | {'accuracy': 0.8852} |
| 0.0           | 315.0 | 10080 | 1.3251          | {'f1': 0.8860557768924302} | {'accuracy': 0.8856} |
| 0.0           | 316.0 | 10112 | 1.3256          | {'f1': 0.8860557768924302} | {'accuracy': 0.8856} |
| 0.0           | 317.0 | 10144 | 1.3263          | {'f1': 0.8860557768924302} | {'accuracy': 0.8856} |
| 0.0           | 318.0 | 10176 | 1.3258          | {'f1': 0.8860557768924302} | {'accuracy': 0.8856} |
| 0.0           | 319.0 | 10208 | 1.3301          | {'f1': 0.8863183087355405} | {'accuracy': 0.886}  |
| 0.0           | 320.0 | 10240 | 1.3351          | {'f1': 0.8865814696485623} | {'accuracy': 0.8864} |
| 0.0           | 321.0 | 10272 | 1.3356          | {'f1': 0.8865814696485623} | {'accuracy': 0.8864} |
| 0.0           | 322.0 | 10304 | 1.3360          | {'f1': 0.8865814696485623} | {'accuracy': 0.8864} |
| 0.0           | 323.0 | 10336 | 1.3361          | {'f1': 0.8870259481037924} | {'accuracy': 0.8868} |
| 0.0           | 324.0 | 10368 | 1.3364          | {'f1': 0.8870259481037924} | {'accuracy': 0.8868} |
| 0.0           | 325.0 | 10400 | 1.3361          | {'f1': 0.8870259481037924} | {'accuracy': 0.8868} |
| 0.0           | 326.0 | 10432 | 1.3366          | {'f1': 0.8863183087355405} | {'accuracy': 0.886}  |
| 0.0           | 327.0 | 10464 | 1.3153          | {'f1': 0.8893219017926735} | {'accuracy': 0.8864} |
| 0.0           | 328.0 | 10496 | 1.3104          | {'f1': 0.8912959381044487} | {'accuracy': 0.8876} |
| 0.0           | 329.0 | 10528 | 1.3165          | {'f1': 0.8901823826154442} | {'accuracy': 0.8868} |
| 0.0           | 330.0 | 10560 | 1.3179          | {'f1': 0.8904428904428903} | {'accuracy': 0.8872} |
| 0.0           | 331.0 | 10592 | 1.3185          | {'f1': 0.8904428904428903} | {'accuracy': 0.8872} |
| 0.0           | 332.0 | 10624 | 1.3194          | {'f1': 0.8895800933125971} | {'accuracy': 0.8864} |
| 0.0           | 333.0 | 10656 | 1.3214          | {'f1': 0.8886292834890965} | {'accuracy': 0.8856} |
| 0.0           | 334.0 | 10688 | 1.3448          | {'f1': 0.8876538308852719} | {'accuracy': 0.8868} |
| 0.0           | 335.0 | 10720 | 1.2584          | {'f1': 0.8893922234805588} | {'accuracy': 0.8828} |
| 0.0           | 336.0 | 10752 | 1.1870          | {'f1': 0.8826396700412449} | {'accuracy': 0.8748} |
| 0.0           | 337.0 | 10784 | 1.2820          | {'f1': 0.8679716784673053} | {'accuracy': 0.8732} |
| 0.0           | 338.0 | 10816 | 1.2112          | {'f1': 0.873469387755102}  | {'accuracy': 0.876}  |
| 0.0           | 339.0 | 10848 | 1.2083          | {'f1': 0.8742368742368742} | {'accuracy': 0.8764} |
| 0.0           | 340.0 | 10880 | 1.1499          | {'f1': 0.885193982581156}  | {'accuracy': 0.884}  |
| 0.0           | 341.0 | 10912 | 1.1507          | {'f1': 0.8861660079051383} | {'accuracy': 0.8848} |
| 0.0           | 342.0 | 10944 | 1.1527          | {'f1': 0.8861660079051383} | {'accuracy': 0.8848} |
| 0.0           | 343.0 | 10976 | 1.3684          | {'f1': 0.8636363636363636} | {'accuracy': 0.8704} |
| 0.0075        | 344.0 | 11008 | 1.2650          | {'f1': 0.8759785743716522} | {'accuracy': 0.8796} |
| 0.0075        | 345.0 | 11040 | 1.2528          | {'f1': 0.8766447368421053} | {'accuracy': 0.88}   |
| 0.0075        | 346.0 | 11072 | 1.2504          | {'f1': 0.8772073921971254} | {'accuracy': 0.8804} |
| 0.0075        | 347.0 | 11104 | 1.2335          | {'f1': 0.8800978792822185} | {'accuracy': 0.8824} |
| 0.0075        | 348.0 | 11136 | 1.2280          | {'f1': 0.8804878048780488} | {'accuracy': 0.8824} |
| 0.0075        | 349.0 | 11168 | 1.2268          | {'f1': 0.880942706216985}  | {'accuracy': 0.8828} |
| 0.0075        | 350.0 | 11200 | 1.2258          | {'f1': 0.8805848903330626} | {'accuracy': 0.8824} |
| 0.0075        | 351.0 | 11232 | 1.2216          | {'f1': 0.8823291548726244} | {'accuracy': 0.8836} |
| 0.0075        | 352.0 | 11264 | 1.2205          | {'f1': 0.8816161616161616} | {'accuracy': 0.8828} |
| 0.0075        | 353.0 | 11296 | 1.4858          | {'f1': 0.8540955631399317} | {'accuracy': 0.8632} |
| 0.0075        | 354.0 | 11328 | 1.1999          | {'f1': 0.8842611133360032} | {'accuracy': 0.8844} |
| 0.0075        | 355.0 | 11360 | 1.1904          | {'f1': 0.886408927859705}  | {'accuracy': 0.886}  |
| 0.0075        | 356.0 | 11392 | 1.1867          | {'f1': 0.8859753675009933} | {'accuracy': 0.8852} |
| 0.0075        | 357.0 | 11424 | 1.1843          | {'f1': 0.8874801901743266} | {'accuracy': 0.8864} |
| 0.0075        | 358.0 | 11456 | 1.1857          | {'f1': 0.8874801901743266} | {'accuracy': 0.8864} |
| 0.0075        | 359.0 | 11488 | 1.1880          | {'f1': 0.887390959555908}  | {'accuracy': 0.8864} |
| 0.0           | 360.0 | 11520 | 1.1902          | {'f1': 0.8869496231654106} | {'accuracy': 0.886}  |
| 0.0           | 361.0 | 11552 | 1.1923          | {'f1': 0.8869496231654106} | {'accuracy': 0.886}  |
| 0.0           | 362.0 | 11584 | 1.1933          | {'f1': 0.8869496231654106} | {'accuracy': 0.886}  |
| 0.0           | 363.0 | 11616 | 1.1948          | {'f1': 0.8869496231654106} | {'accuracy': 0.886}  |
| 0.0           | 364.0 | 11648 | 1.1965          | {'f1': 0.8869496231654106} | {'accuracy': 0.886}  |
| 0.0           | 365.0 | 11680 | 1.1970          | {'f1': 0.887390959555908}  | {'accuracy': 0.8864} |
| 0.0           | 366.0 | 11712 | 1.1992          | {'f1': 0.8869496231654106} | {'accuracy': 0.886}  |
| 0.0           | 367.0 | 11744 | 1.2001          | {'f1': 0.8869496231654106} | {'accuracy': 0.886}  |
| 0.0           | 368.0 | 11776 | 1.2011          | {'f1': 0.887390959555908}  | {'accuracy': 0.8864} |
| 0.0           | 369.0 | 11808 | 1.2020          | {'f1': 0.887390959555908}  | {'accuracy': 0.8864} |
| 0.0           | 370.0 | 11840 | 1.2041          | {'f1': 0.8865079365079365} | {'accuracy': 0.8856} |
| 0.0           | 371.0 | 11872 | 1.2059          | {'f1': 0.8865079365079365} | {'accuracy': 0.8856} |
| 0.0           | 372.0 | 11904 | 1.2011          | {'f1': 0.889589905362776}  | {'accuracy': 0.888}  |
| 0.0           | 373.0 | 11936 | 1.2017          | {'f1': 0.8889763779527559} | {'accuracy': 0.8872} |
| 0.0           | 374.0 | 11968 | 1.2027          | {'f1': 0.8889763779527559} | {'accuracy': 0.8872} |
| 0.0           | 375.0 | 12000 | 1.2139          | {'f1': 0.8865079365079365} | {'accuracy': 0.8856} |
| 0.0           | 376.0 | 12032 | 1.2154          | {'f1': 0.8865079365079365} | {'accuracy': 0.8856} |
| 0.0           | 377.0 | 12064 | 1.2161          | {'f1': 0.8865079365079365} | {'accuracy': 0.8856} |
| 0.0           | 378.0 | 12096 | 1.2171          | {'f1': 0.8865079365079365} | {'accuracy': 0.8856} |
| 0.0           | 379.0 | 12128 | 1.2188          | {'f1': 0.8865079365079365} | {'accuracy': 0.8856} |
| 0.0           | 380.0 | 12160 | 1.2281          | {'f1': 0.8872958980485861} | {'accuracy': 0.8868} |
| 0.0           | 381.0 | 12192 | 1.2291          | {'f1': 0.8872958980485861} | {'accuracy': 0.8868} |
| 0.0           | 382.0 | 12224 | 1.2491          | {'f1': 0.8843373493975905} | {'accuracy': 0.8848} |
| 0.0           | 383.0 | 12256 | 1.2260          | {'f1': 0.8906311250490004} | {'accuracy': 0.8884} |
| 0.0           | 384.0 | 12288 | 1.3156          | {'f1': 0.8826634185952092} | {'accuracy': 0.8844} |
| 0.0           | 385.0 | 12320 | 1.3269          | {'f1': 0.8797390949857318} | {'accuracy': 0.882}  |
| 0.0           | 386.0 | 12352 | 1.3158          | {'f1': 0.8826634185952092} | {'accuracy': 0.8844} |
| 0.0           | 387.0 | 12384 | 1.3105          | {'f1': 0.8845686512758202} | {'accuracy': 0.886}  |
| 0.0           | 388.0 | 12416 | 1.2943          | {'f1': 0.8855761482675262} | {'accuracy': 0.8864} |
| 0.0           | 389.0 | 12448 | 1.2896          | {'f1': 0.8845070422535211} | {'accuracy': 0.8852} |
| 0.0           | 390.0 | 12480 | 1.2891          | {'f1': 0.885048231511254}  | {'accuracy': 0.8856} |
| 0.0013        | 391.0 | 12512 | 1.2894          | {'f1': 0.885048231511254}  | {'accuracy': 0.8856} |
| 0.0013        | 392.0 | 12544 | 1.2898          | {'f1': 0.8846926476496585} | {'accuracy': 0.8852} |
| 0.0013        | 393.0 | 12576 | 1.2905          | {'f1': 0.8846926476496585} | {'accuracy': 0.8852} |
| 0.0013        | 394.0 | 12608 | 1.2910          | {'f1': 0.8846926476496585} | {'accuracy': 0.8852} |
| 0.0013        | 395.0 | 12640 | 1.2916          | {'f1': 0.8846926476496585} | {'accuracy': 0.8852} |
| 0.0013        | 396.0 | 12672 | 1.2921          | {'f1': 0.8846926476496585} | {'accuracy': 0.8852} |
| 0.0013        | 397.0 | 12704 | 1.2923          | {'f1': 0.8851405622489958} | {'accuracy': 0.8856} |
| 0.0013        | 398.0 | 12736 | 1.2925          | {'f1': 0.8855881172219991} | {'accuracy': 0.886}  |
| 0.0013        | 399.0 | 12768 | 1.2929          | {'f1': 0.8856799037304453} | {'accuracy': 0.886}  |
| 0.0013        | 400.0 | 12800 | 1.2927          | {'f1': 0.8866639967961554} | {'accuracy': 0.8868} |
| 0.0013        | 401.0 | 12832 | 1.2922          | {'f1': 0.8859543817527011} | {'accuracy': 0.886}  |
| 0.0013        | 402.0 | 12864 | 1.2922          | {'f1': 0.8864}             | {'accuracy': 0.8864} |
| 0.0013        | 403.0 | 12896 | 1.2921          | {'f1': 0.8860455817672931} | {'accuracy': 0.886}  |
| 0.0013        | 404.0 | 12928 | 1.2923          | {'f1': 0.8860455817672931} | {'accuracy': 0.886}  |
| 0.0013        | 405.0 | 12960 | 1.2929          | {'f1': 0.8860455817672931} | {'accuracy': 0.886}  |
| 0.0013        | 406.0 | 12992 | 1.2933          | {'f1': 0.8860455817672931} | {'accuracy': 0.886}  |
| 0.0           | 407.0 | 13024 | 1.2937          | {'f1': 0.8860455817672931} | {'accuracy': 0.886}  |
| 0.0           | 408.0 | 13056 | 1.2942          | {'f1': 0.8860455817672931} | {'accuracy': 0.886}  |
| 0.0           | 409.0 | 13088 | 1.2946          | {'f1': 0.8864908073541168} | {'accuracy': 0.8864} |
| 0.0           | 410.0 | 13120 | 1.2953          | {'f1': 0.8864908073541168} | {'accuracy': 0.8864} |
| 0.0           | 411.0 | 13152 | 1.3014          | {'f1': 0.8863090472377902} | {'accuracy': 0.8864} |
| 0.0           | 412.0 | 13184 | 1.3020          | {'f1': 0.8863090472377902} | {'accuracy': 0.8864} |
| 0.0           | 413.0 | 13216 | 1.3022          | {'f1': 0.8859543817527011} | {'accuracy': 0.886}  |
| 0.0           | 414.0 | 13248 | 1.3024          | {'f1': 0.8864}             | {'accuracy': 0.8864} |
| 0.0           | 415.0 | 13280 | 1.3028          | {'f1': 0.8864}             | {'accuracy': 0.8864} |
| 0.0           | 416.0 | 13312 | 1.3030          | {'f1': 0.8864}             | {'accuracy': 0.8864} |
| 0.0           | 417.0 | 13344 | 1.3035          | {'f1': 0.8864}             | {'accuracy': 0.8864} |
| 0.0           | 418.0 | 13376 | 1.3057          | {'f1': 0.8864}             | {'accuracy': 0.8864} |
| 0.0           | 419.0 | 13408 | 1.3062          | {'f1': 0.8864}             | {'accuracy': 0.8864} |
| 0.0           | 420.0 | 13440 | 1.3062          | {'f1': 0.8864}             | {'accuracy': 0.8864} |
| 0.0           | 421.0 | 13472 | 1.3064          | {'f1': 0.8860455817672931} | {'accuracy': 0.886}  |
| 0.0           | 422.0 | 13504 | 1.3068          | {'f1': 0.8860455817672931} | {'accuracy': 0.886}  |
| 0.0           | 423.0 | 13536 | 1.3068          | {'f1': 0.8864908073541168} | {'accuracy': 0.8864} |
| 0.0           | 424.0 | 13568 | 1.3069          | {'f1': 0.8861366360367559} | {'accuracy': 0.886}  |
| 0.0           | 425.0 | 13600 | 1.3074          | {'f1': 0.8861366360367559} | {'accuracy': 0.886}  |
| 0.0           | 426.0 | 13632 | 1.3078          | {'f1': 0.8861366360367559} | {'accuracy': 0.886}  |
| 0.0           | 427.0 | 13664 | 1.3081          | {'f1': 0.8861366360367559} | {'accuracy': 0.886}  |
| 0.0           | 428.0 | 13696 | 1.3085          | {'f1': 0.8861366360367559} | {'accuracy': 0.886}  |
| 0.0           | 429.0 | 13728 | 1.3089          | {'f1': 0.8861366360367559} | {'accuracy': 0.886}  |
| 0.0           | 430.0 | 13760 | 1.3093          | {'f1': 0.8861366360367559} | {'accuracy': 0.886}  |
| 0.0           | 431.0 | 13792 | 1.3098          | {'f1': 0.8861366360367559} | {'accuracy': 0.886}  |
| 0.0           | 432.0 | 13824 | 1.3103          | {'f1': 0.8865814696485623} | {'accuracy': 0.8864} |
| 0.0           | 433.0 | 13856 | 1.3108          | {'f1': 0.8865814696485623} | {'accuracy': 0.8864} |
| 0.0           | 434.0 | 13888 | 1.3111          | {'f1': 0.8865814696485623} | {'accuracy': 0.8864} |
| 0.0           | 435.0 | 13920 | 1.3325          | {'f1': 0.8860249697946033} | {'accuracy': 0.8868} |
| 0.0           | 436.0 | 13952 | 1.3348          | {'f1': 0.8859330914953648} | {'accuracy': 0.8868} |
| 0.0           | 437.0 | 13984 | 1.3347          | {'f1': 0.8859330914953648} | {'accuracy': 0.8868} |
| 0.0           | 438.0 | 14016 | 1.3350          | {'f1': 0.8863819500402902} | {'accuracy': 0.8872} |
| 0.0           | 439.0 | 14048 | 1.3356          | {'f1': 0.8863819500402902} | {'accuracy': 0.8872} |
| 0.0           | 440.0 | 14080 | 1.3356          | {'f1': 0.8860249697946033} | {'accuracy': 0.8868} |
| 0.0           | 441.0 | 14112 | 1.3358          | {'f1': 0.8860249697946033} | {'accuracy': 0.8868} |
| 0.0           | 442.0 | 14144 | 1.3361          | {'f1': 0.8860249697946033} | {'accuracy': 0.8868} |
| 0.0           | 443.0 | 14176 | 1.3365          | {'f1': 0.8860249697946033} | {'accuracy': 0.8868} |
| 0.0           | 444.0 | 14208 | 1.3371          | {'f1': 0.8860249697946033} | {'accuracy': 0.8868} |
| 0.0           | 445.0 | 14240 | 1.3372          | {'f1': 0.8860249697946033} | {'accuracy': 0.8868} |
| 0.0           | 446.0 | 14272 | 1.3370          | {'f1': 0.8860249697946033} | {'accuracy': 0.8868} |
| 0.0           | 447.0 | 14304 | 1.3374          | {'f1': 0.8860249697946033} | {'accuracy': 0.8868} |
| 0.0           | 448.0 | 14336 | 1.3377          | {'f1': 0.8860249697946033} | {'accuracy': 0.8868} |
| 0.0           | 449.0 | 14368 | 1.3378          | {'f1': 0.8856682769726248} | {'accuracy': 0.8864} |
| 0.0           | 450.0 | 14400 | 1.3389          | {'f1': 0.8860249697946033} | {'accuracy': 0.8868} |
| 0.0           | 451.0 | 14432 | 1.3398          | {'f1': 0.8860249697946033} | {'accuracy': 0.8868} |
| 0.0           | 452.0 | 14464 | 1.3398          | {'f1': 0.8853118712273642} | {'accuracy': 0.886}  |
| 0.0           | 453.0 | 14496 | 1.4733          | {'f1': 0.8717948717948717} | {'accuracy': 0.876}  |
| 0.0           | 454.0 | 14528 | 1.2690          | {'f1': 0.8940809968847352} | {'accuracy': 0.8912} |
| 0.0           | 455.0 | 14560 | 1.2784          | {'f1': 0.8932562620423893} | {'accuracy': 0.8892} |
| 0.0           | 456.0 | 14592 | 1.2703          | {'f1': 0.8930669800235017} | {'accuracy': 0.8908} |
| 0.0           | 457.0 | 14624 | 1.2847          | {'f1': 0.8900316455696203} | {'accuracy': 0.8888} |
| 0.0           | 458.0 | 14656 | 1.2967          | {'f1': 0.8888888888888887} | {'accuracy': 0.888}  |
| 0.0           | 459.0 | 14688 | 1.3012          | {'f1': 0.8883591577274532} | {'accuracy': 0.8876} |
| 0.0           | 460.0 | 14720 | 1.3181          | {'f1': 0.8892443022790882} | {'accuracy': 0.8892} |
| 0.0           | 461.0 | 14752 | 1.3198          | {'f1': 0.8883553421368547} | {'accuracy': 0.8884} |
| 0.0           | 462.0 | 14784 | 1.3201          | {'f1': 0.8883553421368547} | {'accuracy': 0.8884} |
| 0.0           | 463.0 | 14816 | 1.3203          | {'f1': 0.8883553421368547} | {'accuracy': 0.8884} |
| 0.0           | 464.0 | 14848 | 1.3205          | {'f1': 0.8883553421368547} | {'accuracy': 0.8884} |
| 0.0           | 465.0 | 14880 | 1.3196          | {'f1': 0.8888888888888888} | {'accuracy': 0.8888} |
| 0.0           | 466.0 | 14912 | 1.3196          | {'f1': 0.8885337594886136} | {'accuracy': 0.8884} |
| 0.0           | 467.0 | 14944 | 1.3198          | {'f1': 0.8885337594886136} | {'accuracy': 0.8884} |
| 0.0           | 468.0 | 14976 | 1.3201          | {'f1': 0.8885337594886136} | {'accuracy': 0.8884} |
| 0.0007        | 469.0 | 15008 | 1.3204          | {'f1': 0.8885337594886136} | {'accuracy': 0.8884} |
| 0.0007        | 470.0 | 15040 | 1.3205          | {'f1': 0.8885337594886136} | {'accuracy': 0.8884} |
| 0.0007        | 471.0 | 15072 | 1.3207          | {'f1': 0.8885337594886136} | {'accuracy': 0.8884} |
| 0.0007        | 472.0 | 15104 | 1.3209          | {'f1': 0.8885337594886136} | {'accuracy': 0.8884} |
| 0.0007        | 473.0 | 15136 | 1.3210          | {'f1': 0.8885337594886136} | {'accuracy': 0.8884} |
| 0.0007        | 474.0 | 15168 | 1.3212          | {'f1': 0.8885337594886136} | {'accuracy': 0.8884} |
| 0.0007        | 475.0 | 15200 | 1.3214          | {'f1': 0.8885337594886136} | {'accuracy': 0.8884} |
| 0.0007        | 476.0 | 15232 | 1.3215          | {'f1': 0.8885337594886136} | {'accuracy': 0.8884} |
| 0.0007        | 477.0 | 15264 | 1.3217          | {'f1': 0.8885337594886136} | {'accuracy': 0.8884} |
| 0.0007        | 478.0 | 15296 | 1.3219          | {'f1': 0.8885337594886136} | {'accuracy': 0.8884} |
| 0.0007        | 479.0 | 15328 | 1.3220          | {'f1': 0.8885337594886136} | {'accuracy': 0.8884} |
| 0.0007        | 480.0 | 15360 | 1.3222          | {'f1': 0.8885337594886136} | {'accuracy': 0.8884} |
| 0.0007        | 481.0 | 15392 | 1.3221          | {'f1': 0.8878243512974051} | {'accuracy': 0.8876} |
| 0.0007        | 482.0 | 15424 | 1.3221          | {'f1': 0.888268156424581}  | {'accuracy': 0.888}  |
| 0.0007        | 483.0 | 15456 | 1.3223          | {'f1': 0.888268156424581}  | {'accuracy': 0.888}  |
| 0.0007        | 484.0 | 15488 | 1.3224          | {'f1': 0.888268156424581}  | {'accuracy': 0.888}  |
| 0.0           | 485.0 | 15520 | 1.3226          | {'f1': 0.888268156424581}  | {'accuracy': 0.888}  |
| 0.0           | 486.0 | 15552 | 1.3227          | {'f1': 0.888268156424581}  | {'accuracy': 0.888}  |
| 0.0           | 487.0 | 15584 | 1.3228          | {'f1': 0.888268156424581}  | {'accuracy': 0.888}  |
| 0.0           | 488.0 | 15616 | 1.3230          | {'f1': 0.888268156424581}  | {'accuracy': 0.888}  |
| 0.0           | 489.0 | 15648 | 1.3231          | {'f1': 0.888268156424581}  | {'accuracy': 0.888}  |
| 0.0           | 490.0 | 15680 | 1.3232          | {'f1': 0.888268156424581}  | {'accuracy': 0.888}  |
| 0.0           | 491.0 | 15712 | 1.3233          | {'f1': 0.888268156424581}  | {'accuracy': 0.888}  |
| 0.0           | 492.0 | 15744 | 1.3233          | {'f1': 0.888268156424581}  | {'accuracy': 0.888}  |
| 0.0           | 493.0 | 15776 | 1.3234          | {'f1': 0.888268156424581}  | {'accuracy': 0.888}  |
| 0.0           | 494.0 | 15808 | 1.3235          | {'f1': 0.888268156424581}  | {'accuracy': 0.888}  |
| 0.0           | 495.0 | 15840 | 1.3235          | {'f1': 0.888268156424581}  | {'accuracy': 0.888}  |
| 0.0           | 496.0 | 15872 | 1.3236          | {'f1': 0.888268156424581}  | {'accuracy': 0.888}  |
| 0.0           | 497.0 | 15904 | 1.3240          | {'f1': 0.8878243512974051} | {'accuracy': 0.8876} |
| 0.0           | 498.0 | 15936 | 1.3242          | {'f1': 0.8878243512974051} | {'accuracy': 0.8876} |
| 0.0           | 499.0 | 15968 | 1.3242          | {'f1': 0.8878243512974051} | {'accuracy': 0.8876} |
| 0.0           | 500.0 | 16000 | 1.3242          | {'f1': 0.8878243512974051} | {'accuracy': 0.8876} |


### Framework versions

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