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2020-Q1-90p-filtered-random

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2020-Q1-90p-filtered-random / README.md
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metadata
license: mit
base_model: cardiffnlp/twitter-roberta-base-2019-90m
tags:
  - generated_from_trainer
model-index:
  - name: 2020-Q1-90p-filtered
    results: []

2020-Q1-90p-filtered

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: 3.2574

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: 1e-05
  • 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
  • lr_scheduler_warmup_steps: 1400
  • training_steps: 2400000

Training results

Training Loss Epoch Step Validation Loss
No log 0.16 8000 3.4495
3.5684 0.33 16000 3.4166
3.5684 0.49 24000 3.3847
3.3755 0.66 32000 3.3665
3.3755 0.82 40000 3.3654
3.3533 0.98 48000 3.3654
3.3533 1.15 56000 3.3328
3.3014 1.31 64000 3.3210
3.3014 1.48 72000 3.3492
3.2888 1.64 80000 3.3213
3.2888 1.8 88000 3.2708
3.2609 1.97 96000 3.2908
3.2609 2.13 104000 3.2767
3.2159 2.29 112000 3.2592
3.2159 2.46 120000 3.2411
3.2167 2.62 128000 3.2377
3.2167 2.79 136000 3.2485
3.199 2.95 144000 3.2609
3.199 3.11 152000 3.2553
3.1905 3.28 160000 3.2425
3.1905 3.44 168000 3.2422
3.1822 3.61 176000 3.2624
3.1822 3.77 184000 3.2507
3.1852 3.93 192000 3.2483
3.1852 4.1 200000 3.2514
3.1767 4.26 208000 3.2426
3.1767 4.43 216000 3.2348
3.1767 4.59 224000 3.2735
3.1767 4.75 232000 3.2472
3.1973 4.92 240000 3.2596
3.1973 5.08 248000 3.2606
3.1781 5.24 256000 3.2815
3.1781 5.41 264000 3.2734
3.1803 5.57 272000 3.2739
3.1803 5.74 280000 3.2712
3.1989 5.9 288000 3.2734
3.1989 6.06 296000 3.2939
3.1929 6.23 304000 3.2880
3.1929 6.39 312000 3.2894
3.2083 6.56 320000 3.3086
3.2083 6.72 328000 3.3067
3.2013 6.88 336000 3.2787
3.2013 7.05 344000 3.3153
3.2111 7.21 352000 3.3246
3.2111 7.38 360000 3.3323
3.2186 7.54 368000 3.2938
3.2186 7.7 376000 3.3500
3.2268 7.87 384000 3.3180
3.2268 8.03 392000 3.3171
3.233 8.2 400000 3.3462
3.233 8.36 408000 3.3413
3.2432 8.52 416000 3.3281
3.2432 8.69 424000 3.3420
3.2586 8.85 432000 3.3609
3.2586 9.01 440000 3.3527
3.2567 9.18 448000 3.3594
3.2567 9.34 456000 3.3497
3.2592 9.51 464000 3.3607
3.2592 9.67 472000 3.3840
3.2793 9.83 480000 3.3668
3.2793 10.0 488000 3.3609
3.257 10.16 496000 3.3682
3.257 10.33 504000 3.4006
3.2656 10.49 512000 3.3588
3.2656 10.65 520000 3.3799
3.2727 10.82 528000 3.3833
3.2727 10.98 536000 3.3566
3.2705 11.15 544000 3.3794
3.2705 11.31 552000 3.3838
3.2676 11.47 560000 3.3660
3.2676 11.64 568000 3.3938
3.258 11.8 576000 3.3661
3.258 11.97 584000 3.3490
3.2646 12.13 592000 3.3716
3.2646 12.29 600000 3.3877
3.2578 12.46 608000 3.3930
3.2578 12.62 616000 3.3921
3.2719 12.78 624000 3.3957
3.2719 12.95 632000 3.4196
3.2828 13.11 640000 3.4078
3.2828 13.28 648000 3.4203
3.2805 13.44 656000 3.3900
3.2805 13.6 664000 3.4038
3.2975 13.77 672000 3.4056
3.2975 13.93 680000 3.4284
3.2965 14.1 688000 3.4180
3.2965 14.26 696000 3.4196
3.3069 14.42 704000 3.4257
3.3069 14.59 712000 3.4299
3.3152 14.75 720000 3.4788
3.3152 14.92 728000 3.4425
3.3125 15.08 736000 3.4301
3.3125 15.24 744000 3.4441
3.3174 15.41 752000 3.4396
3.3174 15.57 760000 3.4639
3.3242 15.73 768000 3.4524
3.3242 15.9 776000 3.4560
3.3385 16.06 784000 3.4780
3.3385 16.23 792000 3.4774
3.3371 16.39 800000 3.4772
3.3371 16.55 808000 3.4955
3.3633 16.72 816000 3.4861
3.3633 16.88 824000 3.5063
3.3678 17.05 832000 3.5044
3.3678 17.21 840000 3.5202
3.3634 17.37 848000 3.4941
3.3634 17.54 856000 3.5223
3.3797 17.7 864000 3.5028
3.3797 17.87 872000 3.5264
3.3802 18.03 880000 3.5313
3.3802 18.19 888000 3.4963
3.357 18.36 896000 3.5171
3.357 18.52 904000 3.5307
3.3866 18.69 912000 3.5222
3.3866 18.85 920000 3.5319
3.3818 19.01 928000 3.5326
3.3818 19.18 936000 3.5116
3.3754 19.34 944000 3.5229
3.3754 19.5 952000 3.5383
3.3893 19.67 960000 3.5445
3.3893 19.83 968000 3.5231
3.3899 20.0 976000 3.5310
3.3899 20.16 984000 3.5329
3.3918 20.32 992000 3.5159
3.3918 20.49 1000000 3.5628
3.3786 20.65 1008000 3.5291
3.3786 20.82 1016000 3.5163
3.3862 20.98 1024000 3.5312
3.3862 21.14 1032000 3.5140
3.3855 21.31 1040000 3.5617
3.3855 21.47 1048000 3.5375
3.3872 21.64 1056000 3.5328
3.3872 21.8 1064000 3.5616
3.3931 21.96 1072000 3.5648
3.3931 22.13 1080000 3.5443
3.3708 22.29 1088000 3.5401
3.3708 22.45 1096000 3.5529
3.4099 22.62 1104000 3.5334
3.4099 22.78 1112000 3.5325
3.4027 22.95 1120000 3.5819
3.4027 23.11 1128000 3.5471
3.4035 23.27 1136000 3.5486
3.4035 23.44 1144000 3.5470
3.3964 23.6 1152000 3.5722
3.3964 23.77 1160000 3.5510
3.4115 23.93 1168000 3.5610
3.4115 24.09 1176000 3.5757
3.4173 24.26 1184000 3.5541
3.4173 24.42 1192000 3.5777
3.4169 24.59 1200000 3.5638
3.4169 24.75 1208000 3.5463
3.4031 24.91 1216000 3.5300
3.4031 25.08 1224000 3.5584
3.4094 25.24 1232000 3.5682
3.4094 25.41 1240000 3.5558
3.4116 25.57 1248000 3.5629
3.4116 25.73 1256000 3.5490
3.4199 25.9 1264000 3.5679
3.4199 26.06 1272000 3.5885
3.412 26.22 1280000 3.5579
3.412 26.39 1288000 3.5465
3.4123 26.55 1296000 3.5726
3.4123 26.72 1304000 3.5775
3.4132 26.88 1312000 3.5478
3.4132 27.04 1320000 3.5589
3.4161 27.21 1328000 3.5662
3.4161 27.37 1336000 3.5895
3.4097 27.54 1344000 3.5941
3.4097 27.7 1352000 3.5912
3.415 27.86 1360000 3.5658
3.415 28.03 1368000 3.5554
3.4193 28.19 1376000 3.5899
3.4193 28.36 1384000 3.5652
3.4136 28.52 1392000 3.5832
3.4136 28.68 1400000 3.5885
3.4294 28.85 1408000 3.5832
3.4294 29.01 1416000 3.6025
3.4243 29.17 1424000 3.6040
3.4243 29.34 1432000 3.5890
3.4427 29.5 1440000 3.5835
3.4427 29.67 1448000 3.6185
3.4293 29.83 1456000 3.6029
3.4293 29.99 1464000 3.6162
3.4363 30.16 1472000 3.6258
3.4363 30.32 1480000 3.6038
3.4532 30.49 1488000 3.6039
3.4532 30.65 1496000 3.6054
3.4401 30.81 1504000 3.6269
3.4401 30.98 1512000 3.6004
3.4491 31.14 1520000 3.6096
3.4491 31.31 1528000 3.6217
3.4438 31.47 1536000 3.6081
3.4438 31.63 1544000 3.6190
3.4337 31.8 1552000 3.6120
3.4337 31.96 1560000 3.5861
3.4475 32.13 1568000 3.6209
3.4475 32.29 1576000 3.6302
3.4406 32.45 1584000 3.6053
3.4406 32.62 1592000 3.5934
3.4392 32.78 1600000 3.5942
3.4392 32.94 1608000 3.6013
3.4514 33.11 1616000 3.6506
3.4514 33.27 1624000 3.6049
3.4406 33.44 1632000 3.6285
3.4406 33.6 1640000 3.6107
3.4522 33.76 1648000 3.6081
3.4522 33.93 1656000 3.6121
3.4592 34.09 1664000 3.6396
3.4592 34.26 1672000 3.6284
3.4587 34.42 1680000 3.6195
3.4587 34.58 1688000 3.6168
3.4589 34.75 1696000 3.6315
3.4589 34.91 1704000 3.6045
3.4703 35.08 1712000 3.6251
3.4703 35.24 1720000 3.6252
3.4565 35.4 1728000 3.6254
3.4565 35.57 1736000 3.6544
3.4634 35.73 1744000 3.6290
3.4634 35.9 1752000 3.6124
3.4625 36.06 1760000 3.6262
3.4625 36.22 1768000 3.6318
3.457 36.39 1776000 3.6408
3.457 36.55 1784000 3.6433
3.4618 36.71 1792000 3.6276
3.4618 36.88 1800000 3.6314
3.4611 37.04 1808000 3.6416
3.4611 37.21 1816000 3.6658
3.4651 37.37 1824000 3.6382
3.4651 37.53 1832000 3.6562
3.4625 37.7 1840000 3.6376
3.4625 37.86 1848000 3.6520
3.4561 38.03 1856000 3.6301
3.4561 38.19 1864000 3.6195
3.4655 38.35 1872000 3.6279
3.4655 38.52 1880000 3.6365
3.4637 38.68 1888000 3.6386
3.4637 38.85 1896000 3.6434
3.458 39.01 1904000 3.6519
3.458 39.17 1912000 3.6438
3.4523 39.34 1920000 3.6408
3.4523 39.5 1928000 3.6513
3.4743 39.66 1936000 3.6178
3.4743 39.83 1944000 3.6399
3.4626 39.99 1952000 3.6243
3.4626 40.16 1960000 3.6326
3.4692 40.32 1968000 3.6723
3.4692 40.48 1976000 3.6456
3.4765 40.65 1984000 3.6437
3.4765 40.81 1992000 3.6477
3.4747 40.98 2000000 3.6384
3.4747 41.14 2008000 3.6370
3.4683 41.3 2016000 3.6625
3.4683 41.47 2024000 3.6453
3.4599 41.63 2032000 3.6489
3.4599 41.8 2040000 3.6311
3.4713 41.96 2048000 3.6192
3.4713 42.12 2056000 3.6511
3.4677 42.29 2064000 3.6426
3.4677 42.45 2072000 3.6363
3.4689 42.62 2080000 3.6378
3.4689 42.78 2088000 3.6450
3.4598 42.94 2096000 3.6481
3.4598 43.11 2104000 3.6675
3.4487 43.27 2112000 3.6558
3.4487 43.43 2120000 3.6451
3.4555 43.6 2128000 3.6431
3.4555 43.76 2136000 3.6470
3.4727 43.93 2144000 3.6265
3.4727 44.09 2152000 3.6335
3.4626 44.25 2160000 3.6396
3.4626 44.42 2168000 3.6537
3.4724 44.58 2176000 3.6168
3.4724 44.75 2184000 3.6444
3.4545 44.91 2192000 3.6440
3.4545 45.07 2200000 3.6327
3.461 45.24 2208000 3.6363
3.461 45.4 2216000 3.6537
3.4702 45.57 2224000 3.6123
3.4702 45.73 2232000 3.6554
3.4565 45.89 2240000 3.6523
3.4565 46.06 2248000 3.6340
3.4517 46.22 2256000 3.6459
3.4517 46.38 2264000 3.6561
3.4631 46.55 2272000 3.6548
3.4631 46.71 2280000 3.6229
3.4518 46.88 2288000 3.6350
3.4518 47.04 2296000 3.6483
3.4592 47.2 2304000 3.6263
3.4592 47.37 2312000 3.6339
3.4569 47.53 2320000 3.6594
3.4569 47.7 2328000 3.6385
3.4524 47.86 2336000 3.6434
3.4524 48.02 2344000 3.6502
3.4644 48.19 2352000 3.6176
3.4644 48.35 2360000 3.6293
3.4586 48.52 2368000 3.6304
3.4586 48.68 2376000 3.6343
3.4439 48.84 2384000 3.6090
3.4439 49.01 2392000 3.6414
3.4474 49.17 2400000 3.6208

Framework versions

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