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2020-Q4-25p-filtered

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metadata
license: mit
base_model: cardiffnlp/twitter-roberta-base-2019-90m
tags:
  - generated_from_trainer
model-index:
  - name: 2020-Q4-25p-filtered
    results: []

2020-Q4-25p-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: 2.2653

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 2.5926
2.7864 0.04 16000 2.5071
2.7864 0.07 24000 2.4690
2.5937 0.09 32000 2.4355
2.5937 0.11 40000 2.4125
2.55 0.13 48000 2.4009
2.55 0.16 56000 2.3892
2.5159 0.18 64000 2.3736
2.5159 0.2 72000 2.3713
2.495 0.22 80000 2.3641
2.495 0.25 88000 2.3574
2.4845 0.27 96000 2.3491
2.4845 0.29 104000 2.3485
2.4765 0.31 112000 2.3433
2.4765 0.34 120000 2.3376
2.472 0.36 128000 2.3396
2.472 0.38 136000 2.3326
2.467 0.4 144000 2.3384
2.467 0.43 152000 2.3350
2.46 0.45 160000 2.3263
2.46 0.47 168000 2.3231
2.4593 0.49 176000 2.3223
2.4593 0.52 184000 2.3250
2.4552 0.54 192000 2.3195
2.4552 0.56 200000 2.3236
2.4558 0.58 208000 2.3221
2.4558 0.61 216000 2.3194
2.4487 0.63 224000 2.3225
2.4487 0.65 232000 2.3221
2.4485 0.67 240000 2.3135
2.4485 0.7 248000 2.3109
2.4461 0.72 256000 2.3134
2.4461 0.74 264000 2.3177
2.4513 0.76 272000 2.3102
2.4513 0.79 280000 2.3052
2.4488 0.81 288000 2.3044
2.4488 0.83 296000 2.3117
2.4447 0.85 304000 2.3051
2.4447 0.88 312000 2.3112
2.4485 0.9 320000 2.3064
2.4485 0.92 328000 2.3099
2.4475 0.94 336000 2.3110
2.4475 0.97 344000 2.3014
2.4464 0.99 352000 2.3032
2.4464 1.01 360000 2.3036
2.4478 1.03 368000 2.3050
2.4478 1.06 376000 2.3078
2.4416 1.08 384000 2.3028
2.4416 1.1 392000 2.3017
2.4374 1.12 400000 2.3012
2.4374 1.15 408000 2.3017
2.4406 1.17 416000 2.3043
2.4406 1.19 424000 2.3058
2.4434 1.21 432000 2.2938
2.4434 1.24 440000 2.2971
2.4421 1.26 448000 2.3025
2.4421 1.28 456000 2.2950
2.443 1.3 464000 2.2987
2.443 1.32 472000 2.2949
2.4357 1.35 480000 2.3026
2.4357 1.37 488000 2.2961
2.4366 1.39 496000 2.3003
2.4366 1.41 504000 2.2954
2.4528 1.44 512000 2.2883
2.4528 1.46 520000 2.3000
2.4389 1.48 528000 2.2939
2.4389 1.5 536000 2.2990
2.441 1.53 544000 2.2916
2.441 1.55 552000 2.2906
2.4372 1.57 560000 2.2885
2.4372 1.59 568000 2.3003
2.4379 1.62 576000 2.2988
2.4379 1.64 584000 2.2923
2.4347 1.66 592000 2.2937
2.4347 1.68 600000 2.2958
2.4311 1.71 608000 2.2995
2.4311 1.73 616000 2.2941
2.4437 1.75 624000 2.2949
2.4437 1.77 632000 2.2878
2.4306 1.8 640000 2.2895
2.4306 1.82 648000 2.2930
2.4341 1.84 656000 2.2895
2.4341 1.86 664000 2.2908
2.4333 1.89 672000 2.2842
2.4333 1.91 680000 2.2912
2.4403 1.93 688000 2.2900
2.4403 1.95 696000 2.2862
2.4396 1.98 704000 2.2871
2.4396 2.0 712000 2.2948
2.441 2.02 720000 2.2942
2.441 2.04 728000 2.2828
2.434 2.07 736000 2.2808
2.434 2.09 744000 2.2883
2.4387 2.11 752000 2.2923
2.4387 2.13 760000 2.2848
2.4342 2.16 768000 2.2848
2.4342 2.18 776000 2.2865
2.4389 2.2 784000 2.2885
2.4389 2.22 792000 2.2794
2.4318 2.25 800000 2.2861
2.4318 2.27 808000 2.2876
2.4343 2.29 816000 2.2820
2.4343 2.31 824000 2.2835
2.4335 2.34 832000 2.2788
2.4335 2.36 840000 2.2813
2.4428 2.38 848000 2.2789
2.4428 2.4 856000 2.2858
2.4272 2.43 864000 2.2883
2.4272 2.45 872000 2.2809
2.4331 2.47 880000 2.2880
2.4331 2.49 888000 2.2838
2.4326 2.52 896000 2.2804
2.4326 2.54 904000 2.2831
2.436 2.56 912000 2.2867
2.436 2.58 920000 2.2848
2.435 2.6 928000 2.2871
2.435 2.63 936000 2.2828
2.44 2.65 944000 2.2808
2.44 2.67 952000 2.2853
2.4285 2.69 960000 2.2799
2.4285 2.72 968000 2.2829
2.423 2.74 976000 2.2761
2.423 2.76 984000 2.2768
2.4353 2.78 992000 2.2844
2.4353 2.81 1000000 2.2828
2.4301 2.83 1008000 2.2806
2.4301 2.85 1016000 2.2813
2.4284 2.87 1024000 2.2789
2.4284 2.9 1032000 2.2770
2.4252 2.92 1040000 2.2763
2.4252 2.94 1048000 2.2763
2.4289 2.96 1056000 2.2779
2.4289 2.99 1064000 2.2812
2.4349 3.01 1072000 2.2881
2.4349 3.03 1080000 2.2805
2.4365 3.05 1088000 2.2758
2.4365 3.08 1096000 2.2733
2.4274 3.1 1104000 2.2842
2.4274 3.12 1112000 2.2808
2.4326 3.14 1120000 2.2753
2.4326 3.17 1128000 2.2792
2.4244 3.19 1136000 2.2788
2.4244 3.21 1144000 2.2824
2.4285 3.23 1152000 2.2800
2.4285 3.26 1160000 2.2784
2.4371 3.28 1168000 2.2675
2.4371 3.3 1176000 2.2740
2.4273 3.32 1184000 2.2805
2.4273 3.35 1192000 2.2849
2.4359 3.37 1200000 2.2808
2.4359 3.39 1208000 2.2791
2.4303 3.41 1216000 2.2730
2.4303 3.44 1224000 2.2732
2.4306 3.46 1232000 2.2785
2.4306 3.48 1240000 2.2764
2.4267 3.5 1248000 2.2740
2.4267 3.53 1256000 2.2789
2.4271 3.55 1264000 2.2774
2.4271 3.57 1272000 2.2768
2.4263 3.59 1280000 2.2796
2.4263 3.62 1288000 2.2759
2.431 3.64 1296000 2.2741
2.431 3.66 1304000 2.2821
2.4273 3.68 1312000 2.2740
2.4273 3.71 1320000 2.2713
2.4371 3.73 1328000 2.2704
2.4371 3.75 1336000 2.2734
2.4273 3.77 1344000 2.2746
2.4273 3.8 1352000 2.2840
2.4246 3.82 1360000 2.2764
2.4246 3.84 1368000 2.2740
2.4308 3.86 1376000 2.2730
2.4308 3.88 1384000 2.2751
2.4341 3.91 1392000 2.2777
2.4341 3.93 1400000 2.2679
2.4266 3.95 1408000 2.2777
2.4266 3.97 1416000 2.2783
2.4344 4.0 1424000 2.2743
2.4344 4.02 1432000 2.2691
2.431 4.04 1440000 2.2714
2.431 4.06 1448000 2.2694
2.4296 4.09 1456000 2.2749
2.4296 4.11 1464000 2.2810
2.4265 4.13 1472000 2.2744
2.4265 4.15 1480000 2.2714
2.4266 4.18 1488000 2.2733
2.4266 4.2 1496000 2.2790
2.4253 4.22 1504000 2.2766
2.4253 4.24 1512000 2.2764
2.4303 4.27 1520000 2.2692
2.4303 4.29 1528000 2.2684
2.4373 4.31 1536000 2.2752
2.4373 4.33 1544000 2.2701
2.4346 4.36 1552000 2.2758
2.4346 4.38 1560000 2.2727
2.4294 4.4 1568000 2.2753
2.4294 4.42 1576000 2.2687
2.439 4.45 1584000 2.2776
2.439 4.47 1592000 2.2746
2.4337 4.49 1600000 2.2731
2.4337 4.51 1608000 2.2722
2.4273 4.54 1616000 2.2703
2.4273 4.56 1624000 2.2802
2.4275 4.58 1632000 2.2707
2.4275 4.6 1640000 2.2707
2.4201 4.63 1648000 2.2686
2.4201 4.65 1656000 2.2707
2.4319 4.67 1664000 2.2740
2.4319 4.69 1672000 2.2697
2.4314 4.72 1680000 2.2747
2.4314 4.74 1688000 2.2694
2.4242 4.76 1696000 2.2732
2.4242 4.78 1704000 2.2726
2.4302 4.81 1712000 2.2704
2.4302 4.83 1720000 2.2755
2.4375 4.85 1728000 2.2701
2.4375 4.87 1736000 2.2720
2.4305 4.9 1744000 2.2698
2.4305 4.92 1752000 2.2721
2.4353 4.94 1760000 2.2752
2.4353 4.96 1768000 2.2763
2.4274 4.99 1776000 2.2747
2.4274 5.01 1784000 2.2776
2.4234 5.03 1792000 2.2706
2.4234 5.05 1800000 2.2719
2.4304 5.08 1808000 2.2667
2.4304 5.1 1816000 2.2762
2.4308 5.12 1824000 2.2757
2.4308 5.14 1832000 2.2712
2.4342 5.16 1840000 2.2676
2.4342 5.19 1848000 2.2738
2.4342 5.21 1856000 2.2755
2.4342 5.23 1864000 2.2741
2.4329 5.25 1872000 2.2734
2.4329 5.28 1880000 2.2714
2.4306 5.3 1888000 2.2722
2.4306 5.32 1896000 2.2702
2.4302 5.34 1904000 2.2761
2.4302 5.37 1912000 2.2748
2.4303 5.39 1920000 2.2763
2.4303 5.41 1928000 2.2731
2.4234 5.43 1936000 2.2676
2.4234 5.46 1944000 2.2750
2.4349 5.48 1952000 2.2769
2.4349 5.5 1960000 2.2728
2.4295 5.52 1968000 2.2750
2.4295 5.55 1976000 2.2702
2.428 5.57 1984000 2.2729
2.428 5.59 1992000 2.2707
2.4336 5.61 2000000 2.2774
2.4336 5.64 2008000 2.2735
2.4332 5.66 2016000 2.2634
2.4332 5.68 2024000 2.2679
2.4342 5.7 2032000 2.2753
2.4342 5.73 2040000 2.2719
2.4279 5.75 2048000 2.2711
2.4279 5.77 2056000 2.2778
2.4281 5.79 2064000 2.2693
2.4281 5.82 2072000 2.2715
2.4246 5.84 2080000 2.2674
2.4246 5.86 2088000 2.2700
2.4235 5.88 2096000 2.2703
2.4235 5.91 2104000 2.2723
2.4388 5.93 2112000 2.2683
2.4388 5.95 2120000 2.2712
2.431 5.97 2128000 2.2739
2.431 6.0 2136000 2.2757
2.4329 6.02 2144000 2.2785
2.4329 6.04 2152000 2.2721
2.4266 6.06 2160000 2.2745
2.4266 6.09 2168000 2.2738
2.4255 6.11 2176000 2.2735
2.4255 6.13 2184000 2.2667
2.4263 6.15 2192000 2.2766
2.4263 6.18 2200000 2.2754
2.4388 6.2 2208000 2.2694
2.4388 6.22 2216000 2.2675
2.4293 6.24 2224000 2.2699
2.4293 6.27 2232000 2.2712
2.428 6.29 2240000 2.2707
2.428 6.31 2248000 2.2732
2.4247 6.33 2256000 2.2752
2.4247 6.36 2264000 2.2703
2.4272 6.38 2272000 2.2690
2.4272 6.4 2280000 2.2775
2.4297 6.42 2288000 2.2680
2.4297 6.45 2296000 2.2712
2.4268 6.47 2304000 2.2815
2.4268 6.49 2312000 2.2697
2.4248 6.51 2320000 2.2794
2.4248 6.53 2328000 2.2722
2.4285 6.56 2336000 2.2686
2.4285 6.58 2344000 2.2741
2.4318 6.6 2352000 2.2679
2.4318 6.62 2360000 2.2723
2.4269 6.65 2368000 2.2741
2.4269 6.67 2376000 2.2739
2.4275 6.69 2384000 2.2744
2.4275 6.71 2392000 2.2765
2.4259 6.74 2400000 2.2788

Framework versions

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