2020-Q2-75p-filtered-random
This model is a fine-tuned version of cardiffnlp/twitter-roberta-base-2019-90m on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.9264
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: 4.1e-07
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 2400000
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
No log | 0.07 | 8000 | 2.2326 |
2.407 | 0.13 | 16000 | 2.1532 |
2.407 | 0.2 | 24000 | 2.1195 |
2.23 | 0.27 | 32000 | 2.0944 |
2.23 | 0.34 | 40000 | 2.0626 |
2.1798 | 0.4 | 48000 | 2.0517 |
2.1798 | 0.47 | 56000 | 2.0355 |
2.1621 | 0.54 | 64000 | 2.0469 |
2.1621 | 0.61 | 72000 | 2.0306 |
2.1419 | 0.67 | 80000 | 2.0182 |
2.1419 | 0.74 | 88000 | 2.0107 |
2.1264 | 0.81 | 96000 | 2.0096 |
2.1264 | 0.88 | 104000 | 2.0104 |
2.1203 | 0.94 | 112000 | 2.0037 |
2.1203 | 1.01 | 120000 | 2.0078 |
2.1116 | 1.08 | 128000 | 1.9965 |
2.1116 | 1.15 | 136000 | 2.0025 |
2.1041 | 1.21 | 144000 | 1.9929 |
2.1041 | 1.28 | 152000 | 1.9870 |
2.1058 | 1.35 | 160000 | 1.9895 |
2.1058 | 1.41 | 168000 | 1.9795 |
2.1064 | 1.48 | 176000 | 1.9893 |
2.1064 | 1.55 | 184000 | 1.9877 |
2.098 | 1.62 | 192000 | 1.9920 |
2.098 | 1.68 | 200000 | 1.9801 |
2.0916 | 1.75 | 208000 | 1.9778 |
2.0916 | 1.82 | 216000 | 1.9745 |
2.0951 | 1.89 | 224000 | 1.9831 |
2.0951 | 1.95 | 232000 | 1.9749 |
2.092 | 2.02 | 240000 | 1.9754 |
2.092 | 2.09 | 248000 | 1.9794 |
2.0968 | 2.16 | 256000 | 1.9675 |
2.0968 | 2.22 | 264000 | 1.9710 |
2.0942 | 2.29 | 272000 | 1.9712 |
2.0942 | 2.36 | 280000 | 1.9662 |
2.0929 | 2.43 | 288000 | 1.9672 |
2.0929 | 2.49 | 296000 | 1.9830 |
2.092 | 2.56 | 304000 | 1.9804 |
2.092 | 2.63 | 312000 | 1.9661 |
2.0886 | 2.69 | 320000 | 1.9668 |
2.0886 | 2.76 | 328000 | 1.9643 |
2.0883 | 2.83 | 336000 | 1.9710 |
2.0883 | 2.9 | 344000 | 1.9678 |
2.0937 | 2.96 | 352000 | 1.9737 |
2.0937 | 3.03 | 360000 | 1.9638 |
2.0899 | 3.1 | 368000 | 1.9599 |
2.0899 | 3.17 | 376000 | 1.9570 |
2.0839 | 3.23 | 384000 | 1.9688 |
2.0839 | 3.3 | 392000 | 1.9613 |
2.0862 | 3.37 | 400000 | 1.9686 |
2.0862 | 3.44 | 408000 | 1.9690 |
2.0844 | 3.5 | 416000 | 1.9665 |
2.0844 | 3.57 | 424000 | 1.9512 |
2.0802 | 3.64 | 432000 | 1.9652 |
2.0802 | 3.71 | 440000 | 1.9594 |
2.0882 | 3.77 | 448000 | 1.9543 |
2.0882 | 3.84 | 456000 | 1.9635 |
2.0794 | 3.91 | 464000 | 1.9618 |
2.0794 | 3.97 | 472000 | 1.9617 |
2.0848 | 4.04 | 480000 | 1.9597 |
2.0848 | 4.11 | 488000 | 1.9586 |
2.0814 | 4.18 | 496000 | 1.9587 |
2.0814 | 4.24 | 504000 | 1.9510 |
2.0765 | 4.31 | 512000 | 1.9643 |
2.0765 | 4.38 | 520000 | 1.9586 |
2.0887 | 4.45 | 528000 | 1.9476 |
2.0887 | 4.51 | 536000 | 1.9539 |
2.0857 | 4.58 | 544000 | 1.9538 |
2.0857 | 4.65 | 552000 | 1.9528 |
2.0798 | 4.72 | 560000 | 1.9586 |
2.0798 | 4.78 | 568000 | 1.9660 |
2.0752 | 4.85 | 576000 | 1.9639 |
2.0752 | 4.92 | 584000 | 1.9505 |
2.0771 | 4.99 | 592000 | 1.9551 |
2.0771 | 5.05 | 600000 | 1.9495 |
2.0772 | 5.12 | 608000 | 1.9536 |
2.0772 | 5.19 | 616000 | 1.9567 |
2.0836 | 5.25 | 624000 | 1.9534 |
2.0836 | 5.32 | 632000 | 1.9663 |
2.0851 | 5.39 | 640000 | 1.9535 |
2.0851 | 5.46 | 648000 | 1.9554 |
2.0842 | 5.52 | 656000 | 1.9539 |
2.0842 | 5.59 | 664000 | 1.9589 |
2.088 | 5.66 | 672000 | 1.9572 |
2.088 | 5.73 | 680000 | 1.9603 |
2.075 | 5.79 | 688000 | 1.9639 |
2.075 | 5.86 | 696000 | 1.9537 |
2.077 | 5.93 | 704000 | 1.9612 |
2.077 | 6.0 | 712000 | 1.9571 |
2.0692 | 6.06 | 720000 | 1.9545 |
2.0692 | 6.13 | 728000 | 1.9494 |
2.087 | 6.2 | 736000 | 1.9555 |
2.087 | 6.27 | 744000 | 1.9566 |
2.0783 | 6.33 | 752000 | 1.9447 |
2.0783 | 6.4 | 760000 | 1.9518 |
2.0771 | 6.47 | 768000 | 1.9429 |
2.0771 | 6.53 | 776000 | 1.9603 |
2.0794 | 6.6 | 784000 | 1.9503 |
2.0794 | 6.67 | 792000 | 1.9572 |
2.0777 | 6.74 | 800000 | 1.9607 |
2.0777 | 6.8 | 808000 | 1.9525 |
2.0725 | 6.87 | 816000 | 1.9495 |
2.0725 | 6.94 | 824000 | 1.9517 |
2.0863 | 7.01 | 832000 | 1.9523 |
2.0863 | 7.07 | 840000 | 1.9441 |
2.0735 | 7.14 | 848000 | 1.9430 |
2.0735 | 7.21 | 856000 | 1.9517 |
2.0808 | 7.28 | 864000 | 1.9442 |
2.0808 | 7.34 | 872000 | 1.9414 |
2.0756 | 7.41 | 880000 | 1.9439 |
2.0756 | 7.48 | 888000 | 1.9428 |
2.0799 | 7.55 | 896000 | 1.9472 |
2.0799 | 7.61 | 904000 | 1.9426 |
2.0717 | 7.68 | 912000 | 1.9461 |
2.0717 | 7.75 | 920000 | 1.9583 |
2.0799 | 7.81 | 928000 | 1.9433 |
2.0799 | 7.88 | 936000 | 1.9442 |
2.0704 | 7.95 | 944000 | 1.9396 |
2.0704 | 8.02 | 952000 | 1.9409 |
2.0785 | 8.08 | 960000 | 1.9520 |
2.0785 | 8.15 | 968000 | 1.9409 |
2.0761 | 8.22 | 976000 | 1.9469 |
2.0761 | 8.29 | 984000 | 1.9372 |
2.0739 | 8.35 | 992000 | 1.9385 |
2.0739 | 8.42 | 1000000 | 1.9540 |
2.0761 | 8.49 | 1008000 | 1.9488 |
2.0761 | 8.56 | 1016000 | 1.9464 |
2.0725 | 8.62 | 1024000 | 1.9466 |
2.0725 | 8.69 | 1032000 | 1.9460 |
2.0704 | 8.76 | 1040000 | 1.9449 |
2.0704 | 8.83 | 1048000 | 1.9493 |
2.0734 | 8.89 | 1056000 | 1.9463 |
2.0734 | 8.96 | 1064000 | 1.9403 |
2.0744 | 9.03 | 1072000 | 1.9467 |
2.0744 | 9.09 | 1080000 | 1.9406 |
2.0776 | 9.16 | 1088000 | 1.9492 |
2.0776 | 9.23 | 1096000 | 1.9433 |
2.068 | 9.3 | 1104000 | 1.9450 |
2.068 | 9.36 | 1112000 | 1.9473 |
2.0755 | 9.43 | 1120000 | 1.9459 |
2.0755 | 9.5 | 1128000 | 1.9563 |
2.0783 | 9.57 | 1136000 | 1.9369 |
2.0783 | 9.63 | 1144000 | 1.9461 |
2.0776 | 9.7 | 1152000 | 1.9494 |
2.0776 | 9.77 | 1160000 | 1.9312 |
2.0757 | 9.84 | 1168000 | 1.9452 |
2.0757 | 9.9 | 1176000 | 1.9425 |
2.0776 | 9.97 | 1184000 | 1.9536 |
2.0776 | 10.04 | 1192000 | 1.9351 |
2.0769 | 10.11 | 1200000 | 1.9301 |
2.0769 | 10.17 | 1208000 | 1.9464 |
2.071 | 10.24 | 1216000 | 1.9410 |
2.071 | 10.31 | 1224000 | 1.9321 |
2.0702 | 10.37 | 1232000 | 1.9406 |
2.0702 | 10.44 | 1240000 | 1.9525 |
2.0716 | 10.51 | 1248000 | 1.9418 |
2.0716 | 10.58 | 1256000 | 1.9373 |
2.0753 | 10.64 | 1264000 | 1.9363 |
2.0753 | 10.71 | 1272000 | 1.9504 |
2.0757 | 10.78 | 1280000 | 1.9376 |
2.0757 | 10.85 | 1288000 | 1.9351 |
2.0656 | 10.91 | 1296000 | 1.9445 |
2.0656 | 10.98 | 1304000 | 1.9282 |
2.0732 | 11.05 | 1312000 | 1.9437 |
2.0732 | 11.12 | 1320000 | 1.9501 |
2.0756 | 11.18 | 1328000 | 1.9379 |
2.0756 | 11.25 | 1336000 | 1.9430 |
2.0885 | 11.32 | 1344000 | 1.9392 |
2.0885 | 11.39 | 1352000 | 1.9344 |
2.0758 | 11.45 | 1360000 | 1.9364 |
2.0758 | 11.52 | 1368000 | 1.9404 |
2.0693 | 11.59 | 1376000 | 1.9347 |
2.0693 | 11.65 | 1384000 | 1.9438 |
2.0675 | 11.72 | 1392000 | 1.9367 |
2.0675 | 11.79 | 1400000 | 1.9438 |
2.0731 | 11.86 | 1408000 | 1.9327 |
2.0731 | 11.92 | 1416000 | 1.9341 |
2.0774 | 11.99 | 1424000 | 1.9390 |
2.0774 | 12.06 | 1432000 | 1.9457 |
2.0738 | 12.13 | 1440000 | 1.9437 |
2.0738 | 12.19 | 1448000 | 1.9353 |
2.0667 | 12.26 | 1456000 | 1.9424 |
2.0667 | 12.33 | 1464000 | 1.9435 |
2.0674 | 12.4 | 1472000 | 1.9336 |
2.0674 | 12.46 | 1480000 | 1.9461 |
2.0704 | 12.53 | 1488000 | 1.9458 |
2.0704 | 12.6 | 1496000 | 1.9397 |
2.0691 | 12.67 | 1504000 | 1.9438 |
2.0691 | 12.73 | 1512000 | 1.9325 |
2.0727 | 12.8 | 1520000 | 1.9359 |
2.0727 | 12.87 | 1528000 | 1.9427 |
2.0715 | 12.93 | 1536000 | 1.9491 |
2.0715 | 13.0 | 1544000 | 1.9351 |
2.0692 | 13.07 | 1552000 | 1.9246 |
2.0692 | 13.14 | 1560000 | 1.9457 |
2.0711 | 13.2 | 1568000 | 1.9406 |
2.0711 | 13.27 | 1576000 | 1.9458 |
2.0735 | 13.34 | 1584000 | 1.9356 |
2.0735 | 13.41 | 1592000 | 1.9443 |
2.0707 | 13.47 | 1600000 | 1.9309 |
2.0707 | 13.54 | 1608000 | 1.9367 |
2.0776 | 13.61 | 1616000 | 1.9390 |
2.0776 | 13.68 | 1624000 | 1.9391 |
2.074 | 13.74 | 1632000 | 1.9459 |
2.074 | 13.81 | 1640000 | 1.9316 |
2.0681 | 13.88 | 1648000 | 1.9355 |
2.0681 | 13.95 | 1656000 | 1.9428 |
2.0671 | 14.01 | 1664000 | 1.9286 |
2.0671 | 14.08 | 1672000 | 1.9374 |
2.0672 | 14.15 | 1680000 | 1.9413 |
2.0672 | 14.21 | 1688000 | 1.9372 |
2.0675 | 14.28 | 1696000 | 1.9317 |
2.0675 | 14.35 | 1704000 | 1.9432 |
2.0665 | 14.42 | 1712000 | 1.9444 |
2.0665 | 14.48 | 1720000 | 1.9393 |
2.0645 | 14.55 | 1728000 | 1.9462 |
2.0645 | 14.62 | 1736000 | 1.9374 |
2.0712 | 14.69 | 1744000 | 1.9367 |
2.0712 | 14.75 | 1752000 | 1.9407 |
2.0689 | 14.82 | 1760000 | 1.9361 |
2.0689 | 14.89 | 1768000 | 1.9395 |
2.0657 | 14.96 | 1776000 | 1.9389 |
2.0657 | 15.02 | 1784000 | 1.9396 |
2.0781 | 15.09 | 1792000 | 1.9406 |
2.0781 | 15.16 | 1800000 | 1.9366 |
2.0631 | 15.23 | 1808000 | 1.9357 |
2.0631 | 15.29 | 1816000 | 1.9456 |
2.0738 | 15.36 | 1824000 | 1.9325 |
2.0738 | 15.43 | 1832000 | 1.9377 |
2.0726 | 15.49 | 1840000 | 1.9405 |
2.0726 | 15.56 | 1848000 | 1.9333 |
2.0699 | 15.63 | 1856000 | 1.9369 |
2.0699 | 15.7 | 1864000 | 1.9418 |
2.0764 | 15.76 | 1872000 | 1.9363 |
2.0764 | 15.83 | 1880000 | 1.9375 |
2.0779 | 15.9 | 1888000 | 1.9335 |
2.0779 | 15.97 | 1896000 | 1.9455 |
2.0693 | 16.03 | 1904000 | 1.9447 |
2.0693 | 16.1 | 1912000 | 1.9349 |
2.0716 | 16.17 | 1920000 | 1.9339 |
2.0716 | 16.24 | 1928000 | 1.9426 |
2.075 | 16.3 | 1936000 | 1.9439 |
2.075 | 16.37 | 1944000 | 1.9334 |
2.0751 | 16.44 | 1952000 | 1.9466 |
2.0751 | 16.51 | 1960000 | 1.9397 |
2.0734 | 16.57 | 1968000 | 1.9367 |
2.0734 | 16.64 | 1976000 | 1.9349 |
2.0685 | 16.71 | 1984000 | 1.9510 |
2.0685 | 16.77 | 1992000 | 1.9428 |
2.0706 | 16.84 | 2000000 | 1.9509 |
2.0706 | 16.91 | 2008000 | 1.9403 |
2.0716 | 16.98 | 2016000 | 1.9384 |
2.0716 | 17.04 | 2024000 | 1.9355 |
2.0741 | 17.11 | 2032000 | 1.9308 |
2.0741 | 17.18 | 2040000 | 1.9395 |
2.0714 | 17.25 | 2048000 | 1.9502 |
2.0714 | 17.31 | 2056000 | 1.9337 |
2.0696 | 17.38 | 2064000 | 1.9383 |
2.0696 | 17.45 | 2072000 | 1.9451 |
2.0729 | 17.52 | 2080000 | 1.9373 |
2.0729 | 17.58 | 2088000 | 1.9366 |
2.0716 | 17.65 | 2096000 | 1.9334 |
2.0716 | 17.72 | 2104000 | 1.9417 |
2.074 | 17.79 | 2112000 | 1.9408 |
2.074 | 17.85 | 2120000 | 1.9258 |
2.0745 | 17.92 | 2128000 | 1.9385 |
2.0745 | 17.99 | 2136000 | 1.9409 |
2.074 | 18.05 | 2144000 | 1.9342 |
2.074 | 18.12 | 2152000 | 1.9437 |
2.0666 | 18.19 | 2160000 | 1.9406 |
2.0666 | 18.26 | 2168000 | 1.9382 |
2.0657 | 18.32 | 2176000 | 1.9398 |
2.0657 | 18.39 | 2184000 | 1.9247 |
2.0692 | 18.46 | 2192000 | 1.9377 |
2.0692 | 18.53 | 2200000 | 1.9423 |
2.0726 | 18.59 | 2208000 | 1.9395 |
2.0726 | 18.66 | 2216000 | 1.9286 |
2.0688 | 18.73 | 2224000 | 1.9357 |
2.0688 | 18.8 | 2232000 | 1.9267 |
2.0732 | 18.86 | 2240000 | 1.9293 |
2.0732 | 18.93 | 2248000 | 1.9415 |
2.0697 | 19.0 | 2256000 | 1.9456 |
2.0697 | 19.07 | 2264000 | 1.9331 |
2.0747 | 19.13 | 2272000 | 1.9439 |
2.0747 | 19.2 | 2280000 | 1.9294 |
2.072 | 19.27 | 2288000 | 1.9305 |
2.072 | 19.33 | 2296000 | 1.9401 |
2.0609 | 19.4 | 2304000 | 1.9362 |
2.0609 | 19.47 | 2312000 | 1.9451 |
2.073 | 19.54 | 2320000 | 1.9352 |
2.073 | 19.6 | 2328000 | 1.9380 |
2.0793 | 19.67 | 2336000 | 1.9392 |
2.0793 | 19.74 | 2344000 | 1.9438 |
2.0787 | 19.81 | 2352000 | 1.9403 |
2.0787 | 19.87 | 2360000 | 1.9380 |
2.0694 | 19.94 | 2368000 | 1.9275 |
2.0694 | 20.01 | 2376000 | 1.9344 |
2.0649 | 20.08 | 2384000 | 1.9443 |
2.0649 | 20.14 | 2392000 | 1.9401 |
2.0727 | 20.21 | 2400000 | 1.9447 |
Framework versions
- Transformers 4.35.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.0
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Model tree for DouglasPontes/2020-Q2-75p-filtered-random
Base model
cardiffnlp/twitter-roberta-base-2019-90m