<!-- 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. -->
2020-Q1-full_tweets
This model is a fine-tuned version of ./model_tweets_2020_full_Q1 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.9725
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: 3.6e-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 | 0.02 | 8000 | 2.2672 |
2.4371 | 0.03 | 16000 | 2.1833 |
2.4371 | 0.05 | 24000 | 2.1433 |
2.2336 | 0.07 | 32000 | 2.1114 |
2.2336 | 0.08 | 40000 | 2.0954 |
2.181 | 0.1 | 48000 | 2.0750 |
2.181 | 0.11 | 56000 | 2.0664 |
2.1553 | 0.13 | 64000 | 2.0569 |
2.1553 | 0.15 | 72000 | 2.0540 |
2.1321 | 0.16 | 80000 | 2.0405 |
2.1321 | 0.18 | 88000 | 2.0337 |
2.1249 | 0.2 | 96000 | 2.0336 |
2.1249 | 0.21 | 104000 | 2.0284 |
2.1127 | 0.23 | 112000 | 2.0238 |
2.1127 | 0.25 | 120000 | 2.0200 |
2.1049 | 0.26 | 128000 | 2.0201 |
2.1049 | 0.28 | 136000 | 2.0145 |
2.099 | 0.3 | 144000 | 2.0094 |
2.099 | 0.31 | 152000 | 2.0080 |
2.0896 | 0.33 | 160000 | 2.0121 |
2.0896 | 0.34 | 168000 | 2.0086 |
2.0859 | 0.36 | 176000 | 2.0072 |
2.0859 | 0.38 | 184000 | 2.0053 |
2.086 | 0.39 | 192000 | 2.0015 |
2.086 | 0.41 | 200000 | 2.0021 |
2.0742 | 0.43 | 208000 | 1.9942 |
2.0742 | 0.44 | 216000 | 1.9983 |
2.0777 | 0.46 | 224000 | 2.0000 |
2.0777 | 0.48 | 232000 | 1.9983 |
2.0781 | 0.49 | 240000 | 1.9971 |
2.0781 | 0.51 | 248000 | 1.9951 |
2.0695 | 0.52 | 256000 | 1.9953 |
2.0695 | 0.54 | 264000 | 1.9983 |
2.0767 | 0.56 | 272000 | 1.9923 |
2.0767 | 0.57 | 280000 | 1.9947 |
2.0694 | 0.59 | 288000 | 1.9892 |
2.0694 | 0.61 | 296000 | 1.9908 |
2.0679 | 0.62 | 304000 | 1.9927 |
2.0679 | 0.64 | 312000 | 1.9948 |
2.0754 | 0.66 | 320000 | 1.9922 |
2.0754 | 0.67 | 328000 | 1.9916 |
2.0572 | 0.69 | 336000 | 1.9912 |
2.0572 | 0.7 | 344000 | 1.9875 |
2.0652 | 0.72 | 352000 | 1.9935 |
2.0652 | 0.74 | 360000 | 1.9859 |
2.0662 | 0.75 | 368000 | 1.9912 |
2.0662 | 0.77 | 376000 | 1.9916 |
2.06 | 0.79 | 384000 | 1.9943 |
2.06 | 0.8 | 392000 | 1.9894 |
2.0688 | 0.82 | 400000 | 1.9861 |
2.0688 | 0.84 | 408000 | 1.9876 |
2.0668 | 0.85 | 416000 | 1.9848 |
2.0668 | 0.87 | 424000 | 1.9855 |
2.0686 | 0.89 | 432000 | 1.9920 |
2.0686 | 0.9 | 440000 | 1.9825 |
2.0677 | 0.92 | 448000 | 1.9886 |
2.0677 | 0.93 | 456000 | 1.9914 |
2.0649 | 0.95 | 464000 | 1.9864 |
2.0649 | 0.97 | 472000 | 1.9866 |
2.0665 | 0.98 | 480000 | 1.9869 |
2.0665 | 1.0 | 488000 | 1.9853 |
2.0586 | 1.02 | 496000 | 1.9900 |
2.0586 | 1.03 | 504000 | 1.9859 |
2.0609 | 1.05 | 512000 | 1.9851 |
2.0609 | 1.07 | 520000 | 1.9795 |
2.0647 | 1.08 | 528000 | 1.9859 |
2.0647 | 1.1 | 536000 | 1.9813 |
2.0568 | 1.11 | 544000 | 1.9843 |
2.0568 | 1.13 | 552000 | 1.9871 |
2.0538 | 1.15 | 560000 | 1.9815 |
2.0538 | 1.16 | 568000 | 1.9774 |
2.0569 | 1.18 | 576000 | 1.9896 |
2.0569 | 1.2 | 584000 | 1.9813 |
2.0619 | 1.21 | 592000 | 1.9865 |
2.0619 | 1.23 | 600000 | 1.9780 |
2.06 | 1.25 | 608000 | 1.9861 |
2.06 | 1.26 | 616000 | 1.9843 |
2.057 | 1.28 | 624000 | 1.9829 |
2.057 | 1.29 | 632000 | 1.9843 |
2.0581 | 1.31 | 640000 | 1.9765 |
2.0581 | 1.33 | 648000 | 1.9796 |
2.0466 | 1.34 | 656000 | 1.9807 |
2.0466 | 1.36 | 664000 | 1.9814 |
2.0561 | 1.38 | 672000 | 1.9844 |
2.0561 | 1.39 | 680000 | 1.9829 |
2.0536 | 1.41 | 688000 | 1.9855 |
2.0536 | 1.43 | 696000 | 1.9843 |
2.0468 | 1.44 | 704000 | 1.9824 |
2.0468 | 1.46 | 712000 | 1.9776 |
2.0454 | 1.48 | 720000 | 1.9799 |
2.0454 | 1.49 | 728000 | 1.9845 |
2.0529 | 1.51 | 736000 | 1.9683 |
2.0529 | 1.52 | 744000 | 1.9847 |
2.0529 | 1.54 | 752000 | 1.9838 |
2.0529 | 1.56 | 760000 | 1.9772 |
2.0551 | 1.57 | 768000 | 1.9751 |
2.0551 | 1.59 | 776000 | 1.9825 |
2.0535 | 1.61 | 784000 | 1.9835 |
2.0535 | 1.62 | 792000 | 1.9798 |
2.0494 | 1.64 | 800000 | 1.9811 |
2.0494 | 1.66 | 808000 | 1.9803 |
2.0479 | 1.67 | 816000 | 1.9783 |
2.0479 | 1.69 | 824000 | 1.9752 |
2.0485 | 1.7 | 832000 | 1.9735 |
2.0485 | 1.72 | 840000 | 1.9773 |
2.0481 | 1.74 | 848000 | 1.9755 |
2.0481 | 1.75 | 856000 | 1.9810 |
2.0523 | 1.77 | 864000 | 1.9770 |
2.0523 | 1.79 | 872000 | 1.9788 |
2.0436 | 1.8 | 880000 | 1.9785 |
2.0436 | 1.82 | 888000 | 1.9740 |
2.0527 | 1.84 | 896000 | 1.9770 |
2.0527 | 1.85 | 904000 | 1.9757 |
2.0504 | 1.87 | 912000 | 1.9818 |
2.0504 | 1.88 | 920000 | 1.9851 |
2.0552 | 1.9 | 928000 | 1.9748 |
2.0552 | 1.92 | 936000 | 1.9807 |
2.0512 | 1.93 | 944000 | 1.9803 |
2.0512 | 1.95 | 952000 | 1.9812 |
2.0472 | 1.97 | 960000 | 1.9808 |
2.0472 | 1.98 | 968000 | 1.9725 |
2.0485 | 2.0 | 976000 | 1.9746 |
2.0485 | 2.02 | 984000 | 1.9762 |
2.048 | 2.03 | 992000 | 1.9753 |
2.048 | 2.05 | 1000000 | 1.9741 |
2.0485 | 2.07 | 1008000 | 1.9785 |
2.0485 | 2.08 | 1016000 | 1.9792 |
2.0421 | 2.1 | 1024000 | 1.9731 |
2.0421 | 2.11 | 1032000 | 1.9797 |
2.0497 | 2.13 | 1040000 | 1.9812 |
2.0497 | 2.15 | 1048000 | 1.9764 |
2.0457 | 2.16 | 1056000 | 1.9763 |
2.0457 | 2.18 | 1064000 | 1.9769 |
2.0539 | 2.2 | 1072000 | 1.9792 |
2.0539 | 2.21 | 1080000 | 1.9767 |
2.0462 | 2.23 | 1088000 | 1.9796 |
2.0462 | 2.25 | 1096000 | 1.9789 |
2.0568 | 2.26 | 1104000 | 1.9752 |
2.0568 | 2.28 | 1112000 | 1.9795 |
2.0443 | 2.29 | 1120000 | 1.9762 |
2.0443 | 2.31 | 1128000 | 1.9770 |
2.0478 | 2.33 | 1136000 | 1.9769 |
2.0478 | 2.34 | 1144000 | 1.9785 |
2.0439 | 2.36 | 1152000 | 1.9757 |
2.0439 | 2.38 | 1160000 | 1.9733 |
2.0488 | 2.39 | 1168000 | 1.9755 |
2.0488 | 2.41 | 1176000 | 1.9775 |
2.0474 | 2.43 | 1184000 | 1.9751 |
2.0474 | 2.44 | 1192000 | 1.9793 |
2.0465 | 2.46 | 1200000 | 1.9799 |
2.0465 | 2.47 | 1208000 | 1.9811 |
2.0525 | 2.49 | 1216000 | 1.9787 |
2.0525 | 2.51 | 1224000 | 1.9740 |
2.0419 | 2.52 | 1232000 | 1.9754 |
2.0419 | 2.54 | 1240000 | 1.9754 |
2.042 | 2.56 | 1248000 | 1.9757 |
2.042 | 2.57 | 1256000 | 1.9800 |
2.0499 | 2.59 | 1264000 | 1.9793 |
2.0499 | 2.61 | 1272000 | 1.9768 |
2.0448 | 2.62 | 1280000 | 1.9735 |
2.0448 | 2.64 | 1288000 | 1.9736 |
2.041 | 2.66 | 1296000 | 1.9741 |
2.041 | 2.67 | 1304000 | 1.9729 |
2.0402 | 2.69 | 1312000 | 1.9761 |
2.0402 | 2.7 | 1320000 | 1.9737 |
2.0491 | 2.72 | 1328000 | 1.9771 |
2.0491 | 2.74 | 1336000 | 1.9766 |
2.0422 | 2.75 | 1344000 | 1.9685 |
2.0422 | 2.77 | 1352000 | 1.9726 |
2.0436 | 2.79 | 1360000 | 1.9756 |
2.0436 | 2.8 | 1368000 | 1.9712 |
2.0482 | 2.82 | 1376000 | 1.9736 |
2.0482 | 2.84 | 1384000 | 1.9778 |
2.0443 | 2.85 | 1392000 | 1.9731 |
2.0443 | 2.87 | 1400000 | 1.9734 |
2.0409 | 2.88 | 1408000 | 1.9756 |
2.0409 | 2.9 | 1416000 | 1.9742 |
2.0418 | 2.92 | 1424000 | 1.9765 |
2.0418 | 2.93 | 1432000 | 1.9715 |
2.0512 | 2.95 | 1440000 | 1.9771 |
2.0512 | 2.97 | 1448000 | 1.9796 |
2.0437 | 2.98 | 1456000 | 1.9751 |
2.0437 | 3.0 | 1464000 | 1.9719 |
2.0412 | 3.02 | 1472000 | 1.9798 |
2.0412 | 3.03 | 1480000 | 1.9811 |
2.0368 | 3.05 | 1488000 | 1.9770 |
2.0368 | 3.07 | 1496000 | 1.9765 |
2.0401 | 3.08 | 1504000 | 1.9666 |
2.0401 | 3.1 | 1512000 | 1.9774 |
2.048 | 3.11 | 1520000 | 1.9710 |
2.048 | 3.13 | 1528000 | 1.9769 |
2.0478 | 3.15 | 1536000 | 1.9749 |
2.0478 | 3.16 | 1544000 | 1.9754 |
2.0441 | 3.18 | 1552000 | 1.9767 |
2.0441 | 3.2 | 1560000 | 1.9732 |
2.0458 | 3.21 | 1568000 | 1.9834 |
2.0458 | 3.23 | 1576000 | 1.9801 |
2.043 | 3.25 | 1584000 | 1.9764 |
2.043 | 3.26 | 1592000 | 1.9745 |
2.0451 | 3.28 | 1600000 | 1.9755 |
2.0451 | 3.29 | 1608000 | 1.9747 |
2.0446 | 3.31 | 1616000 | 1.9775 |
2.0446 | 3.33 | 1624000 | 1.9732 |
2.041 | 3.34 | 1632000 | 1.9716 |
2.041 | 3.36 | 1640000 | 1.9712 |
2.046 | 3.38 | 1648000 | 1.9726 |
2.046 | 3.39 | 1656000 | 1.9765 |
2.0367 | 3.41 | 1664000 | 1.9826 |
2.0367 | 3.43 | 1672000 | 1.9764 |
2.0454 | 3.44 | 1680000 | 1.9751 |
2.0454 | 3.46 | 1688000 | 1.9797 |
2.0415 | 3.47 | 1696000 | 1.9762 |
2.0415 | 3.49 | 1704000 | 1.9738 |
2.0447 | 3.51 | 1712000 | 1.9806 |
2.0447 | 3.52 | 1720000 | 1.9783 |
2.0457 | 3.54 | 1728000 | 1.9783 |
2.0457 | 3.56 | 1736000 | 1.9816 |
2.0471 | 3.57 | 1744000 | 1.9734 |
2.0471 | 3.59 | 1752000 | 1.9732 |
2.0463 | 3.61 | 1760000 | 1.9754 |
2.0463 | 3.62 | 1768000 | 1.9782 |
2.0435 | 3.64 | 1776000 | 1.9815 |
2.0435 | 3.66 | 1784000 | 1.9803 |
2.0415 | 3.67 | 1792000 | 1.9751 |
2.0415 | 3.69 | 1800000 | 1.9780 |
2.0541 | 3.7 | 1808000 | 1.9681 |
2.0541 | 3.72 | 1816000 | 1.9716 |
2.0533 | 3.74 | 1824000 | 1.9790 |
2.0533 | 3.75 | 1832000 | 1.9783 |
2.0451 | 3.77 | 1840000 | 1.9786 |
2.0451 | 3.79 | 1848000 | 1.9780 |
2.044 | 3.8 | 1856000 | 1.9781 |
2.044 | 3.82 | 1864000 | 1.9692 |
2.0525 | 3.84 | 1872000 | 1.9778 |
2.0525 | 3.85 | 1880000 | 1.9724 |
2.0521 | 3.87 | 1888000 | 1.9753 |
2.0521 | 3.88 | 1896000 | 1.9798 |
2.0421 | 3.9 | 1904000 | 1.9810 |
2.0421 | 3.92 | 1912000 | 1.9785 |
2.0402 | 3.93 | 1920000 | 1.9822 |
2.0402 | 3.95 | 1928000 | 1.9793 |
2.0393 | 3.97 | 1936000 | 1.9740 |
2.0393 | 3.98 | 1944000 | 1.9773 |
2.043 | 4.0 | 1952000 | 1.9709 |
2.043 | 4.02 | 1960000 | 1.9765 |
2.0437 | 4.03 | 1968000 | 1.9737 |
2.0437 | 4.05 | 1976000 | 1.9728 |
2.038 | 4.06 | 1984000 | 1.9737 |
2.038 | 4.08 | 1992000 | 1.9798 |
2.0486 | 4.1 | 2000000 | 1.9739 |
2.0486 | 4.11 | 2008000 | 1.9744 |
2.0344 | 4.13 | 2016000 | 1.9778 |
2.0344 | 4.15 | 2024000 | 1.9747 |
2.0487 | 4.16 | 2032000 | 1.9737 |
2.0487 | 4.18 | 2040000 | 1.9762 |
2.0443 | 4.2 | 2048000 | 1.9779 |
2.0443 | 4.21 | 2056000 | 1.9791 |
2.0401 | 4.23 | 2064000 | 1.9796 |
2.0401 | 4.25 | 2072000 | 1.9716 |
2.045 | 4.26 | 2080000 | 1.9752 |
2.045 | 4.28 | 2088000 | 1.9775 |
2.0416 | 4.29 | 2096000 | 1.9792 |
2.0416 | 4.31 | 2104000 | 1.9763 |
2.0474 | 4.33 | 2112000 | 1.9738 |
2.0474 | 4.34 | 2120000 | 1.9784 |
2.0413 | 4.36 | 2128000 | 1.9759 |
2.0413 | 4.38 | 2136000 | 1.9748 |
2.0424 | 4.39 | 2144000 | 1.9747 |
2.0424 | 4.41 | 2152000 | 1.9807 |
2.0415 | 4.43 | 2160000 | 1.9758 |
2.0415 | 4.44 | 2168000 | 1.9744 |
2.0385 | 4.46 | 2176000 | 1.9745 |
2.0385 | 4.47 | 2184000 | 1.9718 |
2.0488 | 4.49 | 2192000 | 1.9787 |
2.0488 | 4.51 | 2200000 | 1.9765 |
2.0464 | 4.52 | 2208000 | 1.9776 |
2.0464 | 4.54 | 2216000 | 1.9745 |
2.0433 | 4.56 | 2224000 | 1.9753 |
2.0433 | 4.57 | 2232000 | 1.9749 |
2.0483 | 4.59 | 2240000 | 1.9775 |
2.0483 | 4.61 | 2248000 | 1.9770 |
2.0448 | 4.62 | 2256000 | 1.9763 |
2.0448 | 4.64 | 2264000 | 1.9797 |
2.0459 | 4.65 | 2272000 | 1.9792 |
2.0459 | 4.67 | 2280000 | 1.9749 |
2.0453 | 4.69 | 2288000 | 1.9779 |
2.0453 | 4.7 | 2296000 | 1.9759 |
2.0413 | 4.72 | 2304000 | 1.9797 |
2.0413 | 4.74 | 2312000 | 1.9702 |
2.0439 | 4.75 | 2320000 | 1.9795 |
2.0439 | 4.77 | 2328000 | 1.9745 |
2.0447 | 4.79 | 2336000 | 1.9748 |
2.0447 | 4.8 | 2344000 | 1.9709 |
2.0416 | 4.82 | 2352000 | 1.9775 |
2.0416 | 4.84 | 2360000 | 1.9811 |
2.0445 | 4.85 | 2368000 | 1.9830 |
2.0445 | 4.87 | 2376000 | 1.9771 |
2.05 | 4.88 | 2384000 | 1.9766 |
2.05 | 4.9 | 2392000 | 1.9731 |
2.0439 | 4.92 | 2400000 | 1.9746 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3