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bert-finetuned-token-reqsolvgencat

mnavas / bert-finetuned-token-reqsolvgencat

Run on huggingface.co
huggingface.co
Total runs: 1
24-hour runs: 0
7-day runs: 0
30-day runs: 0
Model's Last Updated: June 28 2023
token-classification

Introduction of bert-finetuned-token-reqsolvgencat

Model Details of bert-finetuned-token-reqsolvgencat

beto-finetuned-token-reqsolvgencat

This model is a fine-tuned version of bert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 2.0573
  • Precision: 0.1111
  • Recall: 0.5
  • F1: 0.1818
  • Accuracy: 0.7765
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: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 200
Training results
Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
0.8551 1.0 3 1.1478 0.0 0.0 0.0 0.4696
1.4354 2.0 6 0.7403 0.0 0.0 0.0 0.6088
0.6532 3.0 9 0.6900 0.0 0.0 0.0 0.6010
0.406 4.0 12 2.0318 0.0 0.0 0.0 0.5284
1.3514 5.0 15 1.3364 0.0 0.0 0.0 0.6186
0.419 6.0 18 0.9463 0.0 0.0 0.0 0.6
0.4816 7.0 21 0.9409 0.0 0.0 0.0 0.6314
0.8621 8.0 24 0.9034 0.0 0.0 0.0 0.7010
0.2981 9.0 27 0.9617 0.0 0.0 0.0 0.6039
0.5882 10.0 30 0.5289 0.0 0.0 0.0 0.8
0.4327 11.0 33 0.6573 0.2 0.5 0.2857 0.7882
0.2076 12.0 36 0.9207 0.0 0.0 0.0 0.6784
0.1454 13.0 39 0.7729 0.0 0.0 0.0 0.7882
0.2339 14.0 42 0.9067 0.0 0.0 0.0 0.7608
0.2281 15.0 45 0.4732 0.0 0.0 0.0 0.7892
0.1058 16.0 48 0.8219 0.0667 0.5 0.1176 0.7961
0.0577 17.0 51 0.9698 0.1429 0.5 0.2222 0.8147
0.0354 18.0 54 1.3158 0.0714 0.5 0.125 0.7549
0.0258 19.0 57 2.2414 0.1667 0.5 0.25 0.6941
0.0456 20.0 60 1.2596 0.0667 0.5 0.1176 0.7520
0.0339 21.0 63 1.8941 0.1667 0.5 0.25 0.7069
0.02 22.0 66 1.0201 0.1 0.5 0.1667 0.7941
0.0257 23.0 69 1.4716 0.0909 0.5 0.1538 0.7716
0.0148 24.0 72 2.6551 0.0 0.0 0.0 0.6853
0.0257 25.0 75 1.7904 0.125 0.5 0.2 0.7324
0.0183 26.0 78 2.2579 0.2 0.5 0.2857 0.7078
0.0218 27.0 81 1.3332 0.1667 0.5 0.25 0.7137
0.0148 28.0 84 0.7506 0.0769 0.5 0.1333 0.8696
0.0081 29.0 87 2.2165 0.1667 0.5 0.25 0.7059
0.0098 30.0 90 2.5291 0.2 0.5 0.2857 0.7
0.0072 31.0 93 2.5877 0.25 0.5 0.3333 0.6990
0.0162 32.0 96 2.7463 0.1667 0.5 0.25 0.6941
0.0073 33.0 99 2.2100 0.1429 0.5 0.2222 0.7176
0.0057 34.0 102 1.5509 0.0769 0.5 0.1333 0.7814
0.0077 35.0 105 1.8449 0.1111 0.5 0.1818 0.7578
0.0071 36.0 108 2.3808 0.3333 0.5 0.4 0.7127
0.0063 37.0 111 1.1188 0.125 0.5 0.2 0.8598
0.0067 38.0 114 1.7108 0.0 0.0 0.0 0.7892
0.0063 39.0 117 1.8995 0.1 0.5 0.1667 0.7363
0.0086 40.0 120 2.0472 0.1667 0.5 0.25 0.7137
0.0028 41.0 123 1.8879 0.1111 0.5 0.1818 0.7245
0.0084 42.0 126 1.9545 0.1667 0.5 0.25 0.7157
0.0018 43.0 129 2.5274 0.0 0.0 0.0 0.6922
0.0031 44.0 132 2.0330 0.0909 0.5 0.1538 0.7245
0.0034 45.0 135 0.9381 0.1 0.5 0.1667 0.8569
0.0016 46.0 138 0.6307 0.1111 0.5 0.1818 0.8980
0.0011 47.0 141 0.7823 0.0667 0.5 0.1176 0.8676
0.0021 48.0 144 1.1034 0.0909 0.5 0.1538 0.8373
0.0025 49.0 147 1.4482 0.2 0.5 0.2857 0.8108
0.0023 50.0 150 1.5541 0.1667 0.5 0.25 0.8069
0.0007 51.0 153 1.7164 0.1667 0.5 0.25 0.8010
0.0002 52.0 156 1.8291 0.1667 0.5 0.25 0.7941
0.0002 53.0 159 1.8918 0.1429 0.5 0.2222 0.7892
0.0016 54.0 162 1.8814 0.2 0.5 0.2857 0.7961
0.0013 55.0 165 1.8920 0.1 0.5 0.1667 0.7873
0.0009 56.0 168 1.8802 0.1 0.5 0.1667 0.7843
0.0017 57.0 171 1.7839 0.1111 0.5 0.1818 0.8
0.0028 58.0 174 1.7409 0.1 0.5 0.1667 0.7961
0.0029 59.0 177 2.1381 0.1 0.5 0.1667 0.7196
0.0008 60.0 180 2.4554 0.125 0.5 0.2 0.6922
0.0012 61.0 183 2.7071 0.125 0.5 0.2 0.6676
0.0011 62.0 186 2.5624 0.125 0.5 0.2 0.6814
0.0009 63.0 189 2.1029 0.2 0.5 0.2857 0.7363
0.0011 64.0 192 1.5984 0.125 0.5 0.2 0.7804
0.0005 65.0 195 1.4155 0.0909 0.5 0.1538 0.8088
0.001 66.0 198 1.3276 0.1111 0.5 0.1818 0.8225
0.0002 67.0 201 1.2844 0.1429 0.5 0.2222 0.8255
0.0076 68.0 204 1.2601 0.1667 0.5 0.25 0.8275
0.0003 69.0 207 1.3359 0.1429 0.5 0.2222 0.8343
0.0027 70.0 210 1.2452 0.25 0.5 0.3333 0.8363
0.004 71.0 213 1.7228 0.1 0.5 0.1667 0.7775
0.0004 72.0 216 2.7878 0.5 0.5 0.5 0.6804
1.1257 73.0 219 2.5785 0.5 0.5 0.5 0.6804
0.0209 74.0 222 0.1081 0.1111 0.5 0.1818 0.9775
0.0486 75.0 225 1.5039 0.0667 0.5 0.1176 0.7784
0.0012 76.0 228 3.2975 0.0 0.0 0.0 0.6098
0.0929 77.0 231 2.4796 0.3333 0.5 0.4 0.6618
0.0006 78.0 234 1.6117 0.125 0.5 0.2 0.7951
0.0077 79.0 237 1.8651 0.125 0.5 0.2 0.7127
0.0032 80.0 240 2.0187 0.1667 0.5 0.25 0.6873
0.0007 81.0 243 1.9540 0.1 0.5 0.1667 0.6902
0.0011 82.0 246 1.8161 0.0714 0.5 0.125 0.7275
0.0009 83.0 249 1.7688 0.1111 0.5 0.1818 0.7657
0.0006 84.0 252 1.7025 0.1667 0.5 0.25 0.7912
0.0003 85.0 255 1.6924 0.2 0.5 0.2857 0.7980
0.0004 86.0 258 1.7019 0.1667 0.5 0.25 0.7980
0.0008 87.0 261 1.7386 0.2 0.5 0.2857 0.7971
0.0002 88.0 264 1.7882 0.1667 0.5 0.25 0.7961
0.0001 89.0 267 1.8405 0.0833 0.5 0.1429 0.7833
0.0004 90.0 270 1.8319 0.125 0.5 0.2 0.7931
0.0003 91.0 273 1.8520 0.125 0.5 0.2 0.7931
0.0001 92.0 276 1.8876 0.0909 0.5 0.1538 0.7873
0.0001 93.0 279 1.9220 0.1 0.5 0.1667 0.7814
0.0004 94.0 282 2.0870 0.1 0.5 0.1667 0.7333
0.0004 95.0 285 2.1469 0.1111 0.5 0.1818 0.7225
0.0009 96.0 288 2.1726 0.1429 0.5 0.2222 0.7196
0.0007 97.0 291 1.9247 0.1 0.5 0.1667 0.7667
0.0012 98.0 294 1.8172 0.1111 0.5 0.1818 0.7902
0.0002 99.0 297 1.7789 0.1 0.5 0.1667 0.7980
0.0109 100.0 300 1.8386 0.0909 0.5 0.1538 0.7843
0.0008 101.0 303 2.0800 0.1 0.5 0.1667 0.7314
0.0002 102.0 306 2.5253 0.3333 0.5 0.4 0.6804
0.001 103.0 309 2.2149 0.1 0.5 0.1667 0.7118
0.0001 104.0 312 1.8607 0.1 0.5 0.1667 0.8020
0.0002 105.0 315 1.7786 0.1 0.5 0.1667 0.8127
0.0009 106.0 318 1.8432 0.125 0.5 0.2 0.8078
0.0001 107.0 321 2.0339 0.1111 0.5 0.1818 0.7784
0.0001 108.0 324 2.2628 0.0769 0.5 0.1333 0.7392
0.0007 109.0 327 2.3649 0.0714 0.5 0.125 0.7265
0.0001 110.0 330 2.4330 0.0714 0.5 0.125 0.7137
0.0001 111.0 333 2.4918 0.1 0.5 0.1667 0.7059
0.0002 112.0 336 2.2853 0.0909 0.5 0.1538 0.7647
0.0001 113.0 339 2.1945 0.1 0.5 0.1667 0.7765
0.0001 114.0 342 2.1446 0.1111 0.5 0.1818 0.7824
0.0008 115.0 345 2.1037 0.1111 0.5 0.1818 0.7863
0.0001 116.0 348 2.0753 0.1 0.5 0.1667 0.7902
0.0001 117.0 351 2.0617 0.1 0.5 0.1667 0.7902
0.0014 118.0 354 1.9908 0.1111 0.5 0.1818 0.7961
0.0009 119.0 357 1.9134 0.1111 0.5 0.1818 0.8
0.0009 120.0 360 1.8651 0.1111 0.5 0.1818 0.8020
0.0002 121.0 363 1.8480 0.1111 0.5 0.1818 0.8
0.0001 122.0 366 1.8558 0.0909 0.5 0.1538 0.7961
0.0001 123.0 369 1.8727 0.1111 0.5 0.1818 0.7892
0.0001 124.0 372 1.8951 0.125 0.5 0.2 0.7863
0.0007 125.0 375 1.8971 0.1667 0.5 0.25 0.7833
0.0011 126.0 378 1.8479 0.1667 0.5 0.25 0.7814
0.0002 127.0 381 1.7985 0.1429 0.5 0.2222 0.7804
0.0001 128.0 384 1.7712 0.125 0.5 0.2 0.7794
0.0001 129.0 387 1.7929 0.1111 0.5 0.1818 0.7755
0.0002 130.0 390 1.8551 0.1111 0.5 0.1818 0.7725
0.0001 131.0 393 1.9030 0.125 0.5 0.2 0.7716
0.0001 132.0 396 1.9421 0.125 0.5 0.2 0.7686
0.0009 133.0 399 1.9440 0.125 0.5 0.2 0.7686
0.0001 134.0 402 1.9455 0.125 0.5 0.2 0.7686
0.0001 135.0 405 1.9527 0.125 0.5 0.2 0.7686
0.0004 136.0 408 1.9493 0.125 0.5 0.2 0.7706
0.0001 137.0 411 1.9432 0.125 0.5 0.2 0.7706
0.0001 138.0 414 1.9491 0.125 0.5 0.2 0.7706
0.0002 139.0 417 1.9434 0.1 0.5 0.1667 0.7735
0.0006 140.0 420 1.9363 0.1111 0.5 0.1818 0.7784
0.0001 141.0 423 1.9330 0.1111 0.5 0.1818 0.7804
0.0001 142.0 426 1.9334 0.1111 0.5 0.1818 0.7833
0.0001 143.0 429 1.9366 0.125 0.5 0.2 0.7843
0.0001 144.0 432 1.9417 0.1111 0.5 0.1818 0.7843
0.0001 145.0 435 1.9467 0.1111 0.5 0.1818 0.7843
0.0001 146.0 438 1.9518 0.1111 0.5 0.1818 0.7843
0.0001 147.0 441 1.9574 0.1111 0.5 0.1818 0.7853
0.0001 148.0 444 1.9635 0.1111 0.5 0.1818 0.7853
0.0003 149.0 447 1.9643 0.1111 0.5 0.1818 0.7853
0.0001 150.0 450 1.9664 0.125 0.5 0.2 0.7853
0.0008 151.0 453 1.9830 0.125 0.5 0.2 0.7843
0.0001 152.0 456 1.9974 0.125 0.5 0.2 0.7824
0.0001 153.0 459 2.0083 0.125 0.5 0.2 0.7824
0.0007 154.0 462 2.0066 0.1111 0.5 0.1818 0.7833
0.0001 155.0 465 2.0047 0.1111 0.5 0.1818 0.7833
0.0001 156.0 468 2.0042 0.1111 0.5 0.1818 0.7833
0.0001 157.0 471 2.0075 0.1111 0.5 0.1818 0.7833
0.0008 158.0 474 2.0217 0.1111 0.5 0.1818 0.7824
0.0001 159.0 477 2.0326 0.125 0.5 0.2 0.7814
0.0001 160.0 480 2.0422 0.125 0.5 0.2 0.7814
0.0001 161.0 483 2.0493 0.125 0.5 0.2 0.7804
0.0001 162.0 486 2.0568 0.125 0.5 0.2 0.7804
0.0002 163.0 489 2.0818 0.125 0.5 0.2 0.7755
0.0001 164.0 492 2.0997 0.125 0.5 0.2 0.7755
0.0001 165.0 495 2.1127 0.125 0.5 0.2 0.7745
0.0001 166.0 498 2.1226 0.125 0.5 0.2 0.7745
0.0001 167.0 501 2.1311 0.1111 0.5 0.1818 0.7716
0.0001 168.0 504 2.1377 0.1111 0.5 0.1818 0.7716
0.0003 169.0 507 2.1296 0.1111 0.5 0.1818 0.7716
0.0001 170.0 510 2.1180 0.125 0.5 0.2 0.7745
0.0 171.0 513 2.1095 0.125 0.5 0.2 0.7745
0.0 172.0 516 2.1035 0.125 0.5 0.2 0.7745
0.0001 173.0 519 2.0999 0.125 0.5 0.2 0.7745
0.0 174.0 522 2.0984 0.125 0.5 0.2 0.7745
0.0004 175.0 525 2.0930 0.125 0.5 0.2 0.7755
0.0 176.0 528 2.0874 0.125 0.5 0.2 0.7755
0.006 177.0 531 2.0807 0.125 0.5 0.2 0.7755
0.0001 178.0 534 2.0717 0.125 0.5 0.2 0.7755
0.0001 179.0 537 2.0721 0.125 0.5 0.2 0.7755
0.0001 180.0 540 2.0731 0.125 0.5 0.2 0.7755
0.001 181.0 543 2.0712 0.125 0.5 0.2 0.7745
0.0001 182.0 546 2.0700 0.125 0.5 0.2 0.7745
0.0001 183.0 549 2.0692 0.125 0.5 0.2 0.7745
0.0001 184.0 552 2.0622 0.125 0.5 0.2 0.7755
0.0006 185.0 555 2.0582 0.125 0.5 0.2 0.7755
0.0001 186.0 558 2.0564 0.125 0.5 0.2 0.7755
0.0001 187.0 561 2.0562 0.125 0.5 0.2 0.7745
0.0001 188.0 564 2.0571 0.125 0.5 0.2 0.7745
0.0001 189.0 567 2.0587 0.125 0.5 0.2 0.7745
0.0001 190.0 570 2.0597 0.1111 0.5 0.1818 0.7735
0.0041 191.0 573 2.0555 0.125 0.5 0.2 0.7745
0.0002 192.0 576 2.0473 0.1111 0.5 0.1818 0.7765
0.0001 193.0 579 2.0480 0.1111 0.5 0.1818 0.7765
0.0002 194.0 582 2.0507 0.1111 0.5 0.1818 0.7765
0.0001 195.0 585 2.0541 0.1111 0.5 0.1818 0.7765
0.0001 196.0 588 2.0562 0.1111 0.5 0.1818 0.7765
0.0001 197.0 591 2.0586 0.1111 0.5 0.1818 0.7765
0.0001 198.0 594 2.0596 0.1111 0.5 0.1818 0.7765
0.0001 199.0 597 2.0604 0.1111 0.5 0.1818 0.7765
0.0003 200.0 600 2.0573 0.1111 0.5 0.1818 0.7765
Framework versions
  • Transformers 4.31.0.dev0
  • Pytorch 2.0.0
  • Datasets 2.1.0
  • Tokenizers 0.13.3

Runs of mnavas bert-finetuned-token-reqsolvgencat on huggingface.co

1
Total runs
0
24-hour runs
0
3-day runs
0
7-day runs
0
30-day runs

More Information About bert-finetuned-token-reqsolvgencat huggingface.co Model

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https://choosealicense.com/licenses/apache-2.0

bert-finetuned-token-reqsolvgencat huggingface.co

bert-finetuned-token-reqsolvgencat huggingface.co is an AI model on huggingface.co that provides bert-finetuned-token-reqsolvgencat's model effect (), which can be used instantly with this mnavas bert-finetuned-token-reqsolvgencat model. huggingface.co supports a free trial of the bert-finetuned-token-reqsolvgencat model, and also provides paid use of the bert-finetuned-token-reqsolvgencat. Support call bert-finetuned-token-reqsolvgencat model through api, including Node.js, Python, http.

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https://huggingface.co/mnavas/bert-finetuned-token-reqsolvgencat

mnavas bert-finetuned-token-reqsolvgencat online free

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mnavas bert-finetuned-token-reqsolvgencat online free url in huggingface.co:

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bert-finetuned-token-reqsolvgencat install

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bert-finetuned-token-reqsolvgencat install url in huggingface.co:

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bert-finetuned-token-reqsolvgencat huggingface.co Url

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mnavas
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