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# bert-small-nan-labels-500

This model is a fine-tuned version of [google/bert_uncased_L-4_H-512_A-8](https://huggingface.co/google/bert_uncased_L-4_H-512_A-8) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 8.1664

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 8
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 4.9422        | 1.0   | 14   | 5.5730          |
| 4.4976        | 2.0   | 28   | 5.4533          |
| 4.2684        | 3.0   | 42   | 5.4158          |
| 4.2673        | 4.0   | 56   | 5.4162          |
| 4.0978        | 5.0   | 70   | 5.4121          |
| 3.8972        | 6.0   | 84   | 5.4649          |
| 3.7728        | 7.0   | 98   | 5.4233          |
| 3.7557        | 8.0   | 112  | 5.4381          |
| 3.693         | 9.0   | 126  | 5.4673          |
| 3.5627        | 10.0  | 140  | 5.5277          |
| 3.6456        | 11.0  | 154  | 5.4351          |
| 3.5487        | 12.0  | 168  | 5.4846          |
| 3.4018        | 13.0  | 182  | 5.5763          |
| 3.3807        | 14.0  | 196  | 5.5674          |
| 3.4219        | 15.0  | 210  | 5.6129          |
| 3.3481        | 16.0  | 224  | 5.5470          |
| 3.2522        | 17.0  | 238  | 5.6078          |
| 3.3047        | 18.0  | 252  | 5.6274          |
| 3.1542        | 19.0  | 266  | 5.6517          |
| 3.0939        | 20.0  | 280  | 5.6088          |
| 3.0951        | 21.0  | 294  | 5.6768          |
| 3.0876        | 22.0  | 308  | 5.6796          |
| 3.0098        | 23.0  | 322  | 5.6938          |
| 3.061         | 24.0  | 336  | 5.7355          |
| 2.8711        | 25.0  | 350  | 5.6882          |
| 2.7414        | 26.0  | 364  | 5.7694          |
| 2.8273        | 27.0  | 378  | 5.7295          |
| 2.8497        | 28.0  | 392  | 5.7976          |
| 2.8469        | 29.0  | 406  | 5.7935          |
| 2.8367        | 30.0  | 420  | 5.8076          |
| 2.6975        | 31.0  | 434  | 5.7854          |
| 2.7496        | 32.0  | 448  | 5.8664          |
| 2.638         | 33.0  | 462  | 5.8900          |
| 2.6511        | 34.0  | 476  | 5.8628          |
| 2.6228        | 35.0  | 490  | 5.8544          |
| 2.617         | 36.0  | 504  | 5.8830          |
| 2.498         | 37.0  | 518  | 5.9080          |
| 2.4956        | 38.0  | 532  | 6.0102          |
| 2.445         | 39.0  | 546  | 5.9869          |
| 2.4493        | 40.0  | 560  | 6.0824          |
| 2.3935        | 41.0  | 574  | 5.9724          |
| 2.3559        | 42.0  | 588  | 5.9515          |
| 2.3444        | 43.0  | 602  | 5.9968          |
| 2.2707        | 44.0  | 616  | 6.0433          |
| 2.1095        | 45.0  | 630  | 6.0700          |
| 2.1573        | 46.0  | 644  | 6.1757          |
| 2.2504        | 47.0  | 658  | 6.0801          |
| 2.25          | 48.0  | 672  | 6.1659          |
| 2.1047        | 49.0  | 686  | 6.1564          |
| 2.1563        | 50.0  | 700  | 6.2225          |
| 2.0882        | 51.0  | 714  | 6.2024          |
| 2.1818        | 52.0  | 728  | 6.1418          |
| 2.1141        | 53.0  | 742  | 6.2118          |
| 2.0647        | 54.0  | 756  | 6.2645          |
| 1.9779        | 55.0  | 770  | 6.3598          |
| 2.053         | 56.0  | 784  | 6.2241          |
| 1.9884        | 57.0  | 798  | 6.2838          |
| 1.8604        | 58.0  | 812  | 6.3798          |
| 1.882         | 59.0  | 826  | 6.3210          |
| 1.9414        | 60.0  | 840  | 6.3404          |
| 1.7435        | 61.0  | 854  | 6.3332          |
| 1.8813        | 62.0  | 868  | 6.3616          |
| 1.7517        | 63.0  | 882  | 6.4093          |
| 1.8046        | 64.0  | 896  | 6.4665          |
| 1.7258        | 65.0  | 910  | 6.4227          |
| 1.7862        | 66.0  | 924  | 6.3705          |
| 1.5828        | 67.0  | 938  | 6.5138          |
| 1.7249        | 68.0  | 952  | 6.4484          |
| 1.692         | 69.0  | 966  | 6.4739          |
| 1.575         | 70.0  | 980  | 6.4886          |
| 1.6542        | 71.0  | 994  | 6.4457          |
| 1.515         | 72.0  | 1008 | 6.5828          |
| 1.6127        | 73.0  | 1022 | 6.5665          |
| 1.6343        | 74.0  | 1036 | 6.5662          |
| 1.4653        | 75.0  | 1050 | 6.5909          |
| 1.5358        | 76.0  | 1064 | 6.5909          |
| 1.6009        | 77.0  | 1078 | 6.5865          |
| 1.5644        | 78.0  | 1092 | 6.5422          |
| 1.4766        | 79.0  | 1106 | 6.6528          |
| 1.4215        | 80.0  | 1120 | 6.6389          |
| 1.4787        | 81.0  | 1134 | 6.6737          |
| 1.4586        | 82.0  | 1148 | 6.6836          |
| 1.4559        | 83.0  | 1162 | 6.6922          |
| 1.4451        | 84.0  | 1176 | 6.6856          |
| 1.3502        | 85.0  | 1190 | 6.6594          |
| 1.3425        | 86.0  | 1204 | 6.6404          |
| 1.3091        | 87.0  | 1218 | 6.7316          |
| 1.3213        | 88.0  | 1232 | 6.7641          |
| 1.2274        | 89.0  | 1246 | 6.7828          |
| 1.247         | 90.0  | 1260 | 6.8646          |
| 1.3159        | 91.0  | 1274 | 6.7969          |
| 1.2061        | 92.0  | 1288 | 6.7785          |
| 1.214         | 93.0  | 1302 | 6.7910          |
| 1.2165        | 94.0  | 1316 | 6.9408          |
| 1.1849        | 95.0  | 1330 | 6.7925          |
| 1.1905        | 96.0  | 1344 | 6.8021          |
| 1.1714        | 97.0  | 1358 | 6.8445          |
| 1.1092        | 98.0  | 1372 | 6.8426          |
| 1.1682        | 99.0  | 1386 | 6.8331          |
| 1.1552        | 100.0 | 1400 | 6.8933          |
| 1.1374        | 101.0 | 1414 | 6.8102          |
| 1.1124        | 102.0 | 1428 | 6.8749          |
| 1.1017        | 103.0 | 1442 | 6.8993          |
| 1.0072        | 104.0 | 1456 | 6.8475          |
| 1.1771        | 105.0 | 1470 | 6.8908          |
| 1.0643        | 106.0 | 1484 | 6.8985          |
| 1.0038        | 107.0 | 1498 | 6.8714          |
| 0.9974        | 108.0 | 1512 | 6.9881          |
| 1.1195        | 109.0 | 1526 | 6.8764          |
| 0.9957        | 110.0 | 1540 | 6.9969          |
| 0.9766        | 111.0 | 1554 | 7.0525          |
| 0.9621        | 112.0 | 1568 | 6.9676          |
| 0.9562        | 113.0 | 1582 | 7.0268          |
| 0.9473        | 114.0 | 1596 | 6.9466          |
| 1.0357        | 115.0 | 1610 | 7.0968          |
| 0.9385        | 116.0 | 1624 | 7.0544          |
| 0.9579        | 117.0 | 1638 | 7.0054          |
| 0.9223        | 118.0 | 1652 | 7.0393          |
| 0.8862        | 119.0 | 1666 | 6.9770          |
| 0.9275        | 120.0 | 1680 | 7.0608          |
| 0.8642        | 121.0 | 1694 | 7.0661          |
| 0.8752        | 122.0 | 1708 | 7.0933          |
| 0.8687        | 123.0 | 1722 | 7.1004          |
| 0.8962        | 124.0 | 1736 | 7.0945          |
| 0.8157        | 125.0 | 1750 | 7.0379          |
| 0.903         | 126.0 | 1764 | 7.1082          |
| 0.9249        | 127.0 | 1778 | 7.0555          |
| 0.8624        | 128.0 | 1792 | 7.1230          |
| 0.7936        | 129.0 | 1806 | 7.1269          |
| 0.8292        | 130.0 | 1820 | 7.1401          |
| 0.7382        | 131.0 | 1834 | 7.1299          |
| 0.8284        | 132.0 | 1848 | 7.1820          |
| 0.7993        | 133.0 | 1862 | 7.2175          |
| 0.8493        | 134.0 | 1876 | 7.2064          |
| 0.8126        | 135.0 | 1890 | 7.1438          |
| 0.7831        | 136.0 | 1904 | 7.2746          |
| 0.8011        | 137.0 | 1918 | 7.2374          |
| 0.7512        | 138.0 | 1932 | 7.2725          |
| 0.7695        | 139.0 | 1946 | 7.2721          |
| 0.7216        | 140.0 | 1960 | 7.2482          |
| 0.744         | 141.0 | 1974 | 7.2467          |
| 0.7366        | 142.0 | 1988 | 7.2893          |
| 0.7214        | 143.0 | 2002 | 7.3204          |
| 0.7456        | 144.0 | 2016 | 7.2928          |
| 0.6891        | 145.0 | 2030 | 7.3215          |
| 0.6306        | 146.0 | 2044 | 7.2637          |
| 0.6763        | 147.0 | 2058 | 7.2491          |
| 0.6558        | 148.0 | 2072 | 7.3143          |
| 0.7562        | 149.0 | 2086 | 7.2424          |
| 0.7019        | 150.0 | 2100 | 7.2770          |
| 0.6251        | 151.0 | 2114 | 7.2743          |
| 0.6857        | 152.0 | 2128 | 7.3607          |
| 0.7037        | 153.0 | 2142 | 7.3243          |
| 0.6398        | 154.0 | 2156 | 7.3276          |
| 0.6231        | 155.0 | 2170 | 7.3595          |
| 0.6368        | 156.0 | 2184 | 7.4406          |
| 0.6653        | 157.0 | 2198 | 7.3381          |
| 0.6189        | 158.0 | 2212 | 7.3217          |
| 0.616         | 159.0 | 2226 | 7.3374          |
| 0.6029        | 160.0 | 2240 | 7.3500          |
| 0.6516        | 161.0 | 2254 | 7.3383          |
| 0.5725        | 162.0 | 2268 | 7.3815          |
| 0.6032        | 163.0 | 2282 | 7.3521          |
| 0.6228        | 164.0 | 2296 | 7.3883          |
| 0.5797        | 165.0 | 2310 | 7.4235          |
| 0.61          | 166.0 | 2324 | 7.4864          |
| 0.581         | 167.0 | 2338 | 7.4154          |
| 0.6213        | 168.0 | 2352 | 7.4857          |
| 0.5709        | 169.0 | 2366 | 7.4169          |
| 0.5898        | 170.0 | 2380 | 7.4947          |
| 0.5106        | 171.0 | 2394 | 7.4307          |
| 0.605         | 172.0 | 2408 | 7.4011          |
| 0.5613        | 173.0 | 2422 | 7.5032          |
| 0.5767        | 174.0 | 2436 | 7.4852          |
| 0.5344        | 175.0 | 2450 | 7.5135          |
| 0.5091        | 176.0 | 2464 | 7.4926          |
| 0.6127        | 177.0 | 2478 | 7.4273          |
| 0.5862        | 178.0 | 2492 | 7.4611          |
| 0.5571        | 179.0 | 2506 | 7.4977          |
| 0.496         | 180.0 | 2520 | 7.4286          |
| 0.5544        | 181.0 | 2534 | 7.4946          |
| 0.5686        | 182.0 | 2548 | 7.5279          |
| 0.5292        | 183.0 | 2562 | 7.5432          |
| 0.5372        | 184.0 | 2576 | 7.5062          |
| 0.5333        | 185.0 | 2590 | 7.6077          |
| 0.5574        | 186.0 | 2604 | 7.6172          |
| 0.5172        | 187.0 | 2618 | 7.5257          |
| 0.5379        | 188.0 | 2632 | 7.5016          |
| 0.513         | 189.0 | 2646 | 7.5428          |
| 0.5631        | 190.0 | 2660 | 7.5116          |
| 0.483         | 191.0 | 2674 | 7.5440          |
| 0.5084        | 192.0 | 2688 | 7.4654          |
| 0.4796        | 193.0 | 2702 | 7.4820          |
| 0.5265        | 194.0 | 2716 | 7.6189          |
| 0.4927        | 195.0 | 2730 | 7.6519          |
| 0.4656        | 196.0 | 2744 | 7.5037          |
| 0.5565        | 197.0 | 2758 | 7.5008          |
| 0.4415        | 198.0 | 2772 | 7.6129          |
| 0.4394        | 199.0 | 2786 | 7.6478          |
| 0.4704        | 200.0 | 2800 | 7.5704          |
| 0.4789        | 201.0 | 2814 | 7.5958          |
| 0.5131        | 202.0 | 2828 | 7.6163          |
| 0.4741        | 203.0 | 2842 | 7.6735          |
| 0.4602        | 204.0 | 2856 | 7.6717          |
| 0.4706        | 205.0 | 2870 | 7.6067          |
| 0.4978        | 206.0 | 2884 | 7.6456          |
| 0.5176        | 207.0 | 2898 | 7.6414          |
| 0.5036        | 208.0 | 2912 | 7.5815          |
| 0.4437        | 209.0 | 2926 | 7.6549          |
| 0.4844        | 210.0 | 2940 | 7.7083          |
| 0.4472        | 211.0 | 2954 | 7.6823          |
| 0.4604        | 212.0 | 2968 | 7.6570          |
| 0.4622        | 213.0 | 2982 | 7.7083          |
| 0.4588        | 214.0 | 2996 | 7.6794          |
| 0.4742        | 215.0 | 3010 | 7.6624          |
| 0.4447        | 216.0 | 3024 | 7.6996          |
| 0.4245        | 217.0 | 3038 | 7.6295          |
| 0.5189        | 218.0 | 3052 | 7.6853          |
| 0.4182        | 219.0 | 3066 | 7.6120          |
| 0.4294        | 220.0 | 3080 | 7.7448          |
| 0.4644        | 221.0 | 3094 | 7.6821          |
| 0.3955        | 222.0 | 3108 | 7.6801          |
| 0.4769        | 223.0 | 3122 | 7.7343          |
| 0.4138        | 224.0 | 3136 | 7.7135          |
| 0.3893        | 225.0 | 3150 | 7.7137          |
| 0.4479        | 226.0 | 3164 | 7.6837          |
| 0.4367        | 227.0 | 3178 | 7.6080          |
| 0.3846        | 228.0 | 3192 | 7.6737          |
| 0.4124        | 229.0 | 3206 | 7.7446          |
| 0.3533        | 230.0 | 3220 | 7.7186          |
| 0.4635        | 231.0 | 3234 | 7.6979          |
| 0.4096        | 232.0 | 3248 | 7.6931          |
| 0.4301        | 233.0 | 3262 | 7.6302          |
| 0.3656        | 234.0 | 3276 | 7.7928          |
| 0.4512        | 235.0 | 3290 | 7.8027          |
| 0.3671        | 236.0 | 3304 | 7.8594          |
| 0.3967        | 237.0 | 3318 | 7.7333          |
| 0.3829        | 238.0 | 3332 | 7.7669          |
| 0.3985        | 239.0 | 3346 | 7.7922          |
| 0.375         | 240.0 | 3360 | 7.8020          |
| 0.3425        | 241.0 | 3374 | 7.8508          |
| 0.4128        | 242.0 | 3388 | 7.7871          |
| 0.4449        | 243.0 | 3402 | 7.8075          |
| 0.4176        | 244.0 | 3416 | 7.7721          |
| 0.4145        | 245.0 | 3430 | 7.7644          |
| 0.4142        | 246.0 | 3444 | 7.8276          |
| 0.3336        | 247.0 | 3458 | 7.8112          |
| 0.3668        | 248.0 | 3472 | 7.8272          |
| 0.384         | 249.0 | 3486 | 7.7916          |
| 0.3873        | 250.0 | 3500 | 7.7770          |
| 0.4032        | 251.0 | 3514 | 7.7633          |
| 0.3166        | 252.0 | 3528 | 7.7615          |
| 0.3897        | 253.0 | 3542 | 7.7801          |
| 0.3916        | 254.0 | 3556 | 7.7710          |
| 0.3462        | 255.0 | 3570 | 7.8086          |
| 0.3705        | 256.0 | 3584 | 7.8322          |
| 0.3781        | 257.0 | 3598 | 7.7828          |
| 0.3466        | 258.0 | 3612 | 7.7830          |
| 0.3986        | 259.0 | 3626 | 7.8720          |
| 0.3335        | 260.0 | 3640 | 7.8438          |
| 0.3698        | 261.0 | 3654 | 7.8200          |
| 0.3715        | 262.0 | 3668 | 7.8205          |
| 0.3553        | 263.0 | 3682 | 7.8782          |
| 0.3664        | 264.0 | 3696 | 7.8409          |
| 0.3548        | 265.0 | 3710 | 7.8220          |
| 0.3671        | 266.0 | 3724 | 7.8378          |
| 0.3809        | 267.0 | 3738 | 7.8346          |
| 0.3595        | 268.0 | 3752 | 7.8602          |
| 0.317         | 269.0 | 3766 | 7.7957          |
| 0.3329        | 270.0 | 3780 | 7.8356          |
| 0.3097        | 271.0 | 3794 | 7.8749          |
| 0.3263        | 272.0 | 3808 | 7.8206          |
| 0.3278        | 273.0 | 3822 | 7.8923          |
| 0.3064        | 274.0 | 3836 | 7.8501          |
| 0.3066        | 275.0 | 3850 | 7.8099          |
| 0.3108        | 276.0 | 3864 | 7.9305          |
| 0.36          | 277.0 | 3878 | 7.8377          |
| 0.3743        | 278.0 | 3892 | 7.8080          |
| 0.3864        | 279.0 | 3906 | 7.8541          |
| 0.292         | 280.0 | 3920 | 7.9087          |
| 0.3183        | 281.0 | 3934 | 7.9080          |
| 0.343         | 282.0 | 3948 | 7.8776          |
| 0.35          | 283.0 | 3962 | 7.8961          |
| 0.3355        | 284.0 | 3976 | 7.8549          |
| 0.3684        | 285.0 | 3990 | 7.8964          |
| 0.3454        | 286.0 | 4004 | 7.9754          |
| 0.3496        | 287.0 | 4018 | 7.8902          |
| 0.3247        | 288.0 | 4032 | 7.9092          |
| 0.2945        | 289.0 | 4046 | 7.9472          |
| 0.3456        | 290.0 | 4060 | 8.0057          |
| 0.4058        | 291.0 | 4074 | 7.9345          |
| 0.3198        | 292.0 | 4088 | 7.9976          |
| 0.3459        | 293.0 | 4102 | 7.9268          |
| 0.3084        | 294.0 | 4116 | 7.8680          |
| 0.2868        | 295.0 | 4130 | 7.8889          |
| 0.2909        | 296.0 | 4144 | 7.9068          |
| 0.3799        | 297.0 | 4158 | 7.9200          |
| 0.3316        | 298.0 | 4172 | 7.9104          |
| 0.3012        | 299.0 | 4186 | 7.8893          |
| 0.309         | 300.0 | 4200 | 7.9324          |
| 0.2663        | 301.0 | 4214 | 7.8847          |
| 0.2809        | 302.0 | 4228 | 7.9753          |
| 0.2871        | 303.0 | 4242 | 7.9208          |
| 0.2717        | 304.0 | 4256 | 7.8918          |
| 0.2871        | 305.0 | 4270 | 7.9883          |
| 0.2763        | 306.0 | 4284 | 7.9588          |
| 0.3047        | 307.0 | 4298 | 7.9780          |
| 0.3463        | 308.0 | 4312 | 7.9802          |
| 0.3279        | 309.0 | 4326 | 7.9799          |
| 0.3224        | 310.0 | 4340 | 7.9768          |
| 0.2568        | 311.0 | 4354 | 7.9846          |
| 0.3027        | 312.0 | 4368 | 7.9537          |
| 0.2415        | 313.0 | 4382 | 7.9870          |
| 0.3115        | 314.0 | 4396 | 7.9839          |
| 0.3022        | 315.0 | 4410 | 7.9722          |
| 0.2975        | 316.0 | 4424 | 7.9705          |
| 0.2944        | 317.0 | 4438 | 8.0632          |
| 0.3164        | 318.0 | 4452 | 8.0619          |
| 0.2764        | 319.0 | 4466 | 7.9667          |
| 0.2558        | 320.0 | 4480 | 8.0001          |
| 0.274         | 321.0 | 4494 | 7.9672          |
| 0.3069        | 322.0 | 4508 | 8.0369          |
| 0.2984        | 323.0 | 4522 | 8.0224          |
| 0.2944        | 324.0 | 4536 | 8.0200          |
| 0.2889        | 325.0 | 4550 | 8.0656          |
| 0.2596        | 326.0 | 4564 | 7.9612          |
| 0.2624        | 327.0 | 4578 | 7.9776          |
| 0.2851        | 328.0 | 4592 | 8.0496          |
| 0.2821        | 329.0 | 4606 | 8.0301          |
| 0.3091        | 330.0 | 4620 | 8.0032          |
| 0.2426        | 331.0 | 4634 | 7.9657          |
| 0.2867        | 332.0 | 4648 | 7.9114          |
| 0.2757        | 333.0 | 4662 | 8.0189          |
| 0.2671        | 334.0 | 4676 | 8.0285          |
| 0.2651        | 335.0 | 4690 | 8.0251          |
| 0.2544        | 336.0 | 4704 | 8.0092          |
| 0.2842        | 337.0 | 4718 | 8.0765          |
| 0.2548        | 338.0 | 4732 | 8.0409          |
| 0.2953        | 339.0 | 4746 | 8.0289          |
| 0.2814        | 340.0 | 4760 | 8.0667          |
| 0.2605        | 341.0 | 4774 | 8.0425          |
| 0.2701        | 342.0 | 4788 | 8.0451          |
| 0.2279        | 343.0 | 4802 | 8.0257          |
| 0.2348        | 344.0 | 4816 | 8.0239          |
| 0.264         | 345.0 | 4830 | 8.0553          |
| 0.2533        | 346.0 | 4844 | 8.0384          |
| 0.25          | 347.0 | 4858 | 8.0648          |
| 0.2515        | 348.0 | 4872 | 8.0934          |
| 0.2235        | 349.0 | 4886 | 8.0480          |
| 0.2289        | 350.0 | 4900 | 8.0747          |
| 0.3048        | 351.0 | 4914 | 8.0854          |
| 0.2463        | 352.0 | 4928 | 8.0728          |
| 0.2984        | 353.0 | 4942 | 8.0424          |
| 0.2718        | 354.0 | 4956 | 8.0761          |
| 0.2761        | 355.0 | 4970 | 8.0684          |
| 0.2347        | 356.0 | 4984 | 8.0769          |
| 0.2683        | 357.0 | 4998 | 8.0191          |
| 0.2837        | 358.0 | 5012 | 8.0605          |
| 0.2623        | 359.0 | 5026 | 8.0554          |
| 0.2581        | 360.0 | 5040 | 8.0864          |
| 0.3162        | 361.0 | 5054 | 8.1435          |
| 0.2388        | 362.0 | 5068 | 8.0557          |
| 0.236         | 363.0 | 5082 | 8.1043          |
| 0.2668        | 364.0 | 5096 | 8.1299          |
| 0.2559        | 365.0 | 5110 | 8.1116          |
| 0.2523        | 366.0 | 5124 | 8.0916          |
| 0.2719        | 367.0 | 5138 | 8.0192          |
| 0.289         | 368.0 | 5152 | 8.1314          |
| 0.237         | 369.0 | 5166 | 8.0493          |
| 0.2401        | 370.0 | 5180 | 8.1385          |
| 0.2905        | 371.0 | 5194 | 8.2075          |
| 0.2806        | 372.0 | 5208 | 8.1328          |
| 0.2986        | 373.0 | 5222 | 8.1489          |
| 0.27          | 374.0 | 5236 | 8.0748          |
| 0.2365        | 375.0 | 5250 | 8.1267          |
| 0.2532        | 376.0 | 5264 | 8.1494          |
| 0.2142        | 377.0 | 5278 | 8.1415          |
| 0.2288        | 378.0 | 5292 | 8.1203          |
| 0.2425        | 379.0 | 5306 | 8.1433          |
| 0.2443        | 380.0 | 5320 | 8.1238          |
| 0.2516        | 381.0 | 5334 | 8.1401          |
| 0.2083        | 382.0 | 5348 | 8.1223          |
| 0.2525        | 383.0 | 5362 | 8.1361          |
| 0.2558        | 384.0 | 5376 | 8.0958          |
| 0.2491        | 385.0 | 5390 | 8.0831          |
| 0.2898        | 386.0 | 5404 | 8.0593          |
| 0.2361        | 387.0 | 5418 | 8.1167          |
| 0.2466        | 388.0 | 5432 | 8.1083          |
| 0.2386        | 389.0 | 5446 | 8.0997          |
| 0.2985        | 390.0 | 5460 | 8.1217          |
| 0.2219        | 391.0 | 5474 | 8.1535          |
| 0.2509        | 392.0 | 5488 | 8.1498          |
| 0.24          | 393.0 | 5502 | 8.1509          |
| 0.2282        | 394.0 | 5516 | 8.2027          |
| 0.2141        | 395.0 | 5530 | 8.1303          |
| 0.2306        | 396.0 | 5544 | 8.1602          |
| 0.2406        | 397.0 | 5558 | 8.1269          |
| 0.2253        | 398.0 | 5572 | 8.0594          |
| 0.2648        | 399.0 | 5586 | 8.1279          |
| 0.2293        | 400.0 | 5600 | 8.0930          |
| 0.2429        | 401.0 | 5614 | 8.1050          |
| 0.2143        | 402.0 | 5628 | 8.1141          |
| 0.2052        | 403.0 | 5642 | 8.1325          |
| 0.222         | 404.0 | 5656 | 8.1627          |
| 0.2076        | 405.0 | 5670 | 8.1566          |
| 0.244         | 406.0 | 5684 | 8.0679          |
| 0.2245        | 407.0 | 5698 | 8.0288          |
| 0.1934        | 408.0 | 5712 | 8.0412          |
| 0.2669        | 409.0 | 5726 | 8.0897          |
| 0.2427        | 410.0 | 5740 | 8.1550          |
| 0.2496        | 411.0 | 5754 | 8.1105          |
| 0.1992        | 412.0 | 5768 | 8.1120          |
| 0.2154        | 413.0 | 5782 | 8.1502          |
| 0.2344        | 414.0 | 5796 | 8.1257          |
| 0.2151        | 415.0 | 5810 | 8.1625          |
| 0.212         | 416.0 | 5824 | 8.1495          |
| 0.2031        | 417.0 | 5838 | 8.1356          |
| 0.2599        | 418.0 | 5852 | 8.2282          |
| 0.1984        | 419.0 | 5866 | 8.1940          |
| 0.2838        | 420.0 | 5880 | 8.1552          |
| 0.2143        | 421.0 | 5894 | 8.1256          |
| 0.2308        | 422.0 | 5908 | 8.1128          |
| 0.2479        | 423.0 | 5922 | 8.1015          |
| 0.2517        | 424.0 | 5936 | 8.1913          |
| 0.1897        | 425.0 | 5950 | 8.1807          |
| 0.2432        | 426.0 | 5964 | 8.1400          |
| 0.2508        | 427.0 | 5978 | 8.1429          |
| 0.2411        | 428.0 | 5992 | 8.1560          |
| 0.2125        | 429.0 | 6006 | 8.1515          |
| 0.2201        | 430.0 | 6020 | 8.1448          |
| 0.2017        | 431.0 | 6034 | 8.1316          |
| 0.2191        | 432.0 | 6048 | 8.1408          |
| 0.2201        | 433.0 | 6062 | 8.1918          |
| 0.243         | 434.0 | 6076 | 8.2030          |
| 0.2523        | 435.0 | 6090 | 8.1573          |
| 0.1696        | 436.0 | 6104 | 8.1757          |
| 0.1939        | 437.0 | 6118 | 8.1383          |
| 0.2103        | 438.0 | 6132 | 8.1768          |
| 0.1882        | 439.0 | 6146 | 8.1340          |
| 0.2183        | 440.0 | 6160 | 8.1488          |
| 0.2005        | 441.0 | 6174 | 8.2002          |
| 0.229         | 442.0 | 6188 | 8.1437          |
| 0.1998        | 443.0 | 6202 | 8.1717          |
| 0.2387        | 444.0 | 6216 | 8.1613          |
| 0.1886        | 445.0 | 6230 | 8.2194          |
| 0.2324        | 446.0 | 6244 | 8.1381          |
| 0.1908        | 447.0 | 6258 | 8.1834          |
| 0.1912        | 448.0 | 6272 | 8.1746          |
| 0.2274        | 449.0 | 6286 | 8.1759          |
| 0.2375        | 450.0 | 6300 | 8.1489          |
| 0.2202        | 451.0 | 6314 | 8.1356          |
| 0.241         | 452.0 | 6328 | 8.1379          |
| 0.2078        | 453.0 | 6342 | 8.1447          |
| 0.2368        | 454.0 | 6356 | 8.1741          |
| 0.1857        | 455.0 | 6370 | 8.1927          |
| 0.1854        | 456.0 | 6384 | 8.1514          |
| 0.1726        | 457.0 | 6398 | 8.0745          |
| 0.181         | 458.0 | 6412 | 8.1332          |
| 0.2198        | 459.0 | 6426 | 8.1616          |
| 0.2014        | 460.0 | 6440 | 8.1878          |
| 0.2341        | 461.0 | 6454 | 8.2081          |
| 0.1932        | 462.0 | 6468 | 8.1799          |
| 0.1867        | 463.0 | 6482 | 8.1591          |
| 0.2366        | 464.0 | 6496 | 8.1363          |
| 0.2169        | 465.0 | 6510 | 8.2088          |
| 0.2248        | 466.0 | 6524 | 8.1332          |
| 0.1948        | 467.0 | 6538 | 8.1625          |
| 0.1834        | 468.0 | 6552 | 8.1572          |
| 0.254         | 469.0 | 6566 | 8.1402          |
| 0.2015        | 470.0 | 6580 | 8.0961          |
| 0.2295        | 471.0 | 6594 | 8.1255          |
| 0.1892        | 472.0 | 6608 | 8.1812          |
| 0.1939        | 473.0 | 6622 | 8.1552          |
| 0.2081        | 474.0 | 6636 | 8.1145          |
| 0.2032        | 475.0 | 6650 | 8.1686          |
| 0.1844        | 476.0 | 6664 | 8.1529          |
| 0.2436        | 477.0 | 6678 | 8.1436          |
| 0.2618        | 478.0 | 6692 | 8.1719          |
| 0.1845        | 479.0 | 6706 | 8.0935          |
| 0.1955        | 480.0 | 6720 | 8.1796          |
| 0.2116        | 481.0 | 6734 | 8.1296          |
| 0.2261        | 482.0 | 6748 | 8.1882          |
| 0.2057        | 483.0 | 6762 | 8.1474          |
| 0.2117        | 484.0 | 6776 | 8.1679          |
| 0.1901        | 485.0 | 6790 | 8.1736          |
| 0.2001        | 486.0 | 6804 | 8.1548          |
| 0.2016        | 487.0 | 6818 | 8.1237          |
| 0.1444        | 488.0 | 6832 | 8.1330          |
| 0.1707        | 489.0 | 6846 | 8.1509          |
| 0.1731        | 490.0 | 6860 | 8.1368          |
| 0.2358        | 491.0 | 6874 | 8.1815          |
| 0.2013        | 492.0 | 6888 | 8.1404          |
| 0.2101        | 493.0 | 6902 | 8.1702          |
| 0.1833        | 494.0 | 6916 | 8.1405          |
| 0.2173        | 495.0 | 6930 | 8.1338          |
| 0.2011        | 496.0 | 6944 | 8.1291          |
| 0.1824        | 497.0 | 6958 | 8.1452          |
| 0.2303        | 498.0 | 6972 | 8.1726          |
| 0.2131        | 499.0 | 6986 | 8.1510          |
| 0.2012        | 500.0 | 7000 | 8.1664          |


### Framework versions

- Transformers 4.13.0
- Pytorch 1.12.1+cu113
- Datasets 1.16.1
- Tokenizers 0.10.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "bert-small-nan-labels-500", "results": []}]}
transformers pytorch bert fill-mask generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #fill-mask #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

bert-small-nan-labels-500
=========================


This model is a fine-tuned version of google/bert\_uncased\_L-4\_H-512\_A-8 on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 8.1664


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: 5e-05
* train\_batch\_size: 32
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 500


### Training results



### Framework versions


* Transformers 4.13.0
* Pytorch 1.12.1+cu113
* Datasets 1.16.1
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 32
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 500 ### Training results ### Framework versions


* Transformers 4.13.0
* Pytorch 1.12.1+cu113
* Datasets 1.16.1
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #bert #fill-mask #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 32
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 500 ### Training results ### Framework versions


* Transformers 4.13.0
* Pytorch 1.12.1+cu113
* Datasets 1.16.1
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #bert #fill-mask #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 32
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 500### Training results### Framework versions


* Transformers 4.13.0
* Pytorch 1.12.1+cu113
* Datasets 1.16.1
* Tokenizers 0.10.3