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2020-Q2-full_tweets_combined90

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metadata
license: mit
base_model: cardiffnlp/twitter-roberta-base-2019-90m
tags:
  - generated_from_trainer
model-index:
  - name: 2020-Q2-full_tweets_combined90
    results: []

2020-Q2-full_tweets_combined90

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: 1.9349

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 0.02 8000 2.2220
2.4154 0.03 16000 2.1427
2.4154 0.05 24000 2.1028
2.2273 0.07 32000 2.0824
2.2273 0.08 40000 2.0645
2.1774 0.1 48000 2.0478
2.1774 0.12 56000 2.0327
2.1569 0.13 64000 2.0248
2.1569 0.15 72000 2.0209
2.1439 0.17 80000 2.0049
2.1439 0.19 88000 2.0113
2.1271 0.2 96000 2.0038
2.1271 0.22 104000 2.0065
2.1211 0.24 112000 1.9987
2.1211 0.25 120000 1.9929
2.1194 0.27 128000 1.9922
2.1194 0.29 136000 1.9917
2.1118 0.3 144000 1.9885
2.1118 0.32 152000 1.9870
2.1047 0.34 160000 1.9843
2.1047 0.35 168000 1.9827
2.1015 0.37 176000 1.9826
2.1015 0.39 184000 1.9774
2.1042 0.4 192000 1.9771
2.1042 0.42 200000 1.9770
2.0919 0.44 208000 1.9752
2.0919 0.45 216000 1.9775
2.0953 0.47 224000 1.9684
2.0953 0.49 232000 1.9748
2.0848 0.51 240000 1.9714
2.0848 0.52 248000 1.9781
2.0882 0.54 256000 1.9709
2.0882 0.56 264000 1.9660
2.0922 0.57 272000 1.9651
2.0922 0.59 280000 1.9678
2.0938 0.61 288000 1.9667
2.0938 0.62 296000 1.9630
2.095 0.64 304000 1.9642
2.095 0.66 312000 1.9624
2.0908 0.67 320000 1.9603
2.0908 0.69 328000 1.9649
2.0927 0.71 336000 1.9641
2.0927 0.72 344000 1.9603
2.0931 0.74 352000 1.9590
2.0931 0.76 360000 1.9644
2.087 0.77 368000 1.9635
2.087 0.79 376000 1.9614
2.0792 0.81 384000 1.9591
2.0792 0.83 392000 1.9575
2.0899 0.84 400000 1.9592
2.0899 0.86 408000 1.9619
2.0812 0.88 416000 1.9582
2.0812 0.89 424000 1.9580
2.0948 0.91 432000 1.9587
2.0948 0.93 440000 1.9593
2.0895 0.94 448000 1.9608
2.0895 0.96 456000 1.9566
2.0756 0.98 464000 1.9525
2.0756 0.99 472000 1.9541
2.0842 1.01 480000 1.9601
2.0842 1.03 488000 1.9564
2.0935 1.04 496000 1.9522
2.0935 1.06 504000 1.9532
2.0836 1.08 512000 1.9537
2.0836 1.09 520000 1.9553
2.0876 1.11 528000 1.9469
2.0876 1.13 536000 1.9497
2.0778 1.15 544000 1.9542
2.0778 1.16 552000 1.9516
2.0829 1.18 560000 1.9506
2.0829 1.2 568000 1.9505
2.0864 1.21 576000 1.9531
2.0864 1.23 584000 1.9455
2.0893 1.25 592000 1.9471
2.0893 1.26 600000 1.9539
2.0808 1.28 608000 1.9455
2.0808 1.3 616000 1.9497
2.0838 1.31 624000 1.9466
2.0838 1.33 632000 1.9498
2.0812 1.35 640000 1.9510
2.0812 1.36 648000 1.9526
2.0793 1.38 656000 1.9471
2.0793 1.4 664000 1.9469
2.0789 1.41 672000 1.9455
2.0789 1.43 680000 1.9469
2.0883 1.45 688000 1.9439
2.0883 1.47 696000 1.9439
2.09 1.48 704000 1.9416
2.09 1.5 712000 1.9492
2.0845 1.52 720000 1.9430
2.0845 1.53 728000 1.9484
2.0742 1.55 736000 1.9456
2.0742 1.57 744000 1.9380
2.0839 1.58 752000 1.9418
2.0839 1.6 760000 1.9434
2.0806 1.62 768000 1.9450
2.0806 1.63 776000 1.9426
2.0805 1.65 784000 1.9441
2.0805 1.67 792000 1.9459
2.0833 1.68 800000 1.9435
2.0833 1.7 808000 1.9455
2.0763 1.72 816000 1.9421
2.0763 1.73 824000 1.9438
2.0758 1.75 832000 1.9371
2.0758 1.77 840000 1.9432
2.0888 1.79 848000 1.9414
2.0888 1.8 856000 1.9444
2.0786 1.82 864000 1.9408
2.0786 1.84 872000 1.9397
2.079 1.85 880000 1.9406
2.079 1.87 888000 1.9442
2.0817 1.89 896000 1.9404
2.0817 1.9 904000 1.9450
2.0792 1.92 912000 1.9380
2.0792 1.94 920000 1.9385
2.0741 1.95 928000 1.9449
2.0741 1.97 936000 1.9414
2.0832 1.99 944000 1.9402
2.0832 2.0 952000 1.9410
2.0695 2.02 960000 1.9371
2.0695 2.04 968000 1.9342
2.0813 2.05 976000 1.9376
2.0813 2.07 984000 1.9397
2.0804 2.09 992000 1.9394
2.0804 2.11 1000000 1.9370
2.0789 2.12 1008000 1.9350
2.0789 2.14 1016000 1.9327
2.0754 2.16 1024000 1.9421
2.0754 2.17 1032000 1.9371
2.0774 2.19 1040000 1.9411
2.0774 2.21 1048000 1.9337
2.0766 2.22 1056000 1.9387
2.0766 2.24 1064000 1.9334
2.079 2.26 1072000 1.9386
2.079 2.27 1080000 1.9335
2.068 2.29 1088000 1.9363
2.068 2.31 1096000 1.9420
2.0786 2.32 1104000 1.9331
2.0786 2.34 1112000 1.9327
2.0734 2.36 1120000 1.9391
2.0734 2.37 1128000 1.9363
2.0787 2.39 1136000 1.9321
2.0787 2.41 1144000 1.9333
2.0731 2.43 1152000 1.9369
2.0731 2.44 1160000 1.9357
2.0816 2.46 1168000 1.9353
2.0816 2.48 1176000 1.9319
2.0758 2.49 1184000 1.9366
2.0758 2.51 1192000 1.9301
2.0725 2.53 1200000 1.9329
2.0725 2.54 1208000 1.9370
2.085 2.56 1216000 1.9251
2.085 2.58 1224000 1.9369
2.0809 2.59 1232000 1.9377
2.0809 2.61 1240000 1.9398
2.0742 2.63 1248000 1.9368
2.0742 2.64 1256000 1.9389
2.0743 2.66 1264000 1.9287
2.0743 2.68 1272000 1.9337
2.0822 2.69 1280000 1.9323
2.0822 2.71 1288000 1.9348
2.0845 2.73 1296000 1.9328
2.0845 2.75 1304000 1.9324
2.0706 2.76 1312000 1.9304
2.0706 2.78 1320000 1.9322
2.0813 2.8 1328000 1.9320
2.0813 2.81 1336000 1.9379
2.0768 2.83 1344000 1.9283
2.0768 2.85 1352000 1.9352
2.0776 2.86 1360000 1.9266
2.0776 2.88 1368000 1.9339
2.0776 2.9 1376000 1.9371
2.0776 2.91 1384000 1.9353
2.072 2.93 1392000 1.9290
2.072 2.95 1400000 1.9337
2.077 2.96 1408000 1.9318
2.077 2.98 1416000 1.9326
2.0777 3.0 1424000 1.9338
2.0777 3.01 1432000 1.9307
2.0846 3.03 1440000 1.9305
2.0846 3.05 1448000 1.9312
2.0744 3.07 1456000 1.9332
2.0744 3.08 1464000 1.9313
2.0767 3.1 1472000 1.9311
2.0767 3.12 1480000 1.9322
2.082 3.13 1488000 1.9362
2.082 3.15 1496000 1.9329
2.0774 3.17 1504000 1.9335
2.0774 3.18 1512000 1.9342
2.0793 3.2 1520000 1.9326
2.0793 3.22 1528000 1.9313
2.0834 3.23 1536000 1.9302
2.0834 3.25 1544000 1.9299
2.0698 3.27 1552000 1.9288
2.0698 3.28 1560000 1.9311
2.0721 3.3 1568000 1.9262
2.0721 3.32 1576000 1.9320
2.0742 3.33 1584000 1.9278
2.0742 3.35 1592000 1.9333
2.0774 3.37 1600000 1.9252
2.0774 3.39 1608000 1.9301
2.0766 3.4 1616000 1.9344
2.0766 3.42 1624000 1.9320
2.0702 3.44 1632000 1.9307
2.0702 3.45 1640000 1.9304
2.0772 3.47 1648000 1.9280
2.0772 3.49 1656000 1.9324
2.0757 3.5 1664000 1.9343
2.0757 3.52 1672000 1.9312
2.0747 3.54 1680000 1.9304
2.0747 3.55 1688000 1.9360
2.068 3.57 1696000 1.9297
2.068 3.59 1704000 1.9337
2.0825 3.6 1712000 1.9293
2.0825 3.62 1720000 1.9295
2.0811 3.64 1728000 1.9315
2.0811 3.65 1736000 1.9279
2.0844 3.67 1744000 1.9289
2.0844 3.69 1752000 1.9279
2.0827 3.71 1760000 1.9283
2.0827 3.72 1768000 1.9295
2.0684 3.74 1776000 1.9281
2.0684 3.76 1784000 1.9330
2.0724 3.77 1792000 1.9294
2.0724 3.79 1800000 1.9276
2.074 3.81 1808000 1.9227
2.074 3.82 1816000 1.9320
2.0801 3.84 1824000 1.9275
2.0801 3.86 1832000 1.9302
2.0783 3.87 1840000 1.9333
2.0783 3.89 1848000 1.9296
2.0787 3.91 1856000 1.9302
2.0787 3.92 1864000 1.9347
2.0733 3.94 1872000 1.9298
2.0733 3.96 1880000 1.9302
2.0742 3.97 1888000 1.9279
2.0742 3.99 1896000 1.9258
2.0769 4.01 1904000 1.9255
2.0769 4.03 1912000 1.9282
2.0736 4.04 1920000 1.9298
2.0736 4.06 1928000 1.9325
2.0713 4.08 1936000 1.9296
2.0713 4.09 1944000 1.9293
2.0825 4.11 1952000 1.9345
2.0825 4.13 1960000 1.9346
2.0828 4.14 1968000 1.9311
2.0828 4.16 1976000 1.9307
2.0821 4.18 1984000 1.9336
2.0821 4.19 1992000 1.9265
2.0768 4.21 2000000 1.9284
2.0768 4.23 2008000 1.9290
2.0695 4.24 2016000 1.9306
2.0695 4.26 2024000 1.9299
2.0698 4.28 2032000 1.9230
2.0698 4.29 2040000 1.9272
2.0776 4.31 2048000 1.9306
2.0776 4.33 2056000 1.9243
2.0797 4.35 2064000 1.9266
2.0797 4.36 2072000 1.9249
2.0808 4.38 2080000 1.9279
2.0808 4.4 2088000 1.9262
2.0776 4.41 2096000 1.9350
2.0776 4.43 2104000 1.9297
2.0805 4.45 2112000 1.9337
2.0805 4.46 2120000 1.9302
2.0791 4.48 2128000 1.9337
2.0791 4.5 2136000 1.9298
2.0771 4.51 2144000 1.9268
2.0771 4.53 2152000 1.9370
2.0807 4.55 2160000 1.9307
2.0807 4.56 2168000 1.9292
2.0856 4.58 2176000 1.9300
2.0856 4.6 2184000 1.9329
2.0744 4.61 2192000 1.9319
2.0744 4.63 2200000 1.9352
2.0839 4.65 2208000 1.9368
2.0839 4.67 2216000 1.9343
2.0706 4.68 2224000 1.9290
2.0706 4.7 2232000 1.9347
2.0745 4.72 2240000 1.9294
2.0745 4.73 2248000 1.9255
2.0767 4.75 2256000 1.9271
2.0767 4.77 2264000 1.9296
2.0753 4.78 2272000 1.9268
2.0753 4.8 2280000 1.9292
2.0716 4.82 2288000 1.9310
2.0716 4.83 2296000 1.9267
2.0778 4.85 2304000 1.9301
2.0778 4.87 2312000 1.9280
2.0724 4.88 2320000 1.9283
2.0724 4.9 2328000 1.9289
2.0811 4.92 2336000 1.9315
2.0811 4.93 2344000 1.9268
2.0816 4.95 2352000 1.9304
2.0816 4.97 2360000 1.9302
2.0775 4.99 2368000 1.9292
2.0775 5.0 2376000 1.9274
2.0807 5.02 2384000 1.9317
2.0807 5.04 2392000 1.9298
2.0668 5.05 2400000 1.9349

Framework versions

  • Transformers 4.35.0.dev0
  • Pytorch 2.0.1+cu117
  • Datasets 2.14.5
  • Tokenizers 0.14.0