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2020-Q4-25p-filtered-random

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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-random
    results: []

2020-Q4-25p-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: 2.2681

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 2.5802
2.8151 0.04 16000 2.4882
2.8151 0.07 24000 2.4292
2.5636 0.09 32000 2.3980
2.5636 0.11 40000 2.3799
2.4947 0.13 48000 2.3665
2.4947 0.16 56000 2.3455
2.473 0.18 64000 2.3419
2.473 0.2 72000 2.3307
2.4512 0.22 80000 2.3289
2.4512 0.25 88000 2.3250
2.4421 0.27 96000 2.3189
2.4421 0.29 104000 2.3200
2.4354 0.31 112000 2.3155
2.4354 0.34 120000 2.3138
2.4324 0.36 128000 2.3054
2.4324 0.38 136000 2.3028
2.4253 0.4 144000 2.3029
2.4253 0.43 152000 2.3006
2.4156 0.45 160000 2.3001
2.4156 0.47 168000 2.2980
2.4165 0.49 176000 2.2913
2.4165 0.52 184000 2.2974
2.4131 0.54 192000 2.2906
2.4131 0.56 200000 2.2908
2.407 0.58 208000 2.2895
2.407 0.61 216000 2.2865
2.4153 0.63 224000 2.2914
2.4153 0.65 232000 2.2806
2.4011 0.67 240000 2.2819
2.4011 0.7 248000 2.2854
2.4087 0.72 256000 2.2837
2.4087 0.74 264000 2.2866
2.4059 0.76 272000 2.2855
2.4059 0.79 280000 2.2868
2.4086 0.81 288000 2.2770
2.4086 0.83 296000 2.2789
2.4093 0.85 304000 2.2792
2.4093 0.88 312000 2.2797
2.4036 0.9 320000 2.2794
2.4036 0.92 328000 2.2768
2.4063 0.94 336000 2.2836
2.4063 0.97 344000 2.2809
2.4047 0.99 352000 2.2808
2.4047 1.01 360000 2.2840
2.4084 1.03 368000 2.2799
2.4084 1.06 376000 2.2726
2.4041 1.08 384000 2.2824
2.4041 1.1 392000 2.2781
2.4034 1.12 400000 2.2751
2.4034 1.15 408000 2.2761
2.3951 1.17 416000 2.2732
2.3951 1.19 424000 2.2710
2.409 1.21 432000 2.2780
2.409 1.24 440000 2.2715
2.3985 1.26 448000 2.2790
2.3985 1.28 456000 2.2766
2.4016 1.3 464000 2.2745
2.4016 1.32 472000 2.2719
2.3978 1.35 480000 2.2755
2.3978 1.37 488000 2.2699
2.406 1.39 496000 2.2823
2.406 1.41 504000 2.2736
2.3958 1.44 512000 2.2728
2.3958 1.46 520000 2.2763
2.406 1.48 528000 2.2781
2.406 1.5 536000 2.2723
2.4 1.53 544000 2.2733
2.4 1.55 552000 2.2715
2.3998 1.57 560000 2.2716
2.3998 1.59 568000 2.2751
2.4017 1.62 576000 2.2743
2.4017 1.64 584000 2.2739
2.4019 1.66 592000 2.2755
2.4019 1.68 600000 2.2691
2.398 1.71 608000 2.2706
2.398 1.73 616000 2.2703
2.4027 1.75 624000 2.2657
2.4027 1.77 632000 2.2674
2.4 1.8 640000 2.2749
2.4 1.82 648000 2.2714
2.4046 1.84 656000 2.2695
2.4046 1.86 664000 2.2724
2.4033 1.89 672000 2.2697
2.4033 1.91 680000 2.2697
2.3981 1.93 688000 2.2674
2.3981 1.95 696000 2.2669
2.4029 1.98 704000 2.2755
2.4029 2.0 712000 2.2664
2.4046 2.02 720000 2.2759
2.4046 2.04 728000 2.2689
2.4056 2.07 736000 2.2710
2.4056 2.09 744000 2.2744
2.4036 2.11 752000 2.2653
2.4036 2.13 760000 2.2642
2.3961 2.16 768000 2.2703
2.3961 2.18 776000 2.2683
2.3939 2.2 784000 2.2746
2.3939 2.22 792000 2.2667
2.3998 2.25 800000 2.2690
2.3998 2.27 808000 2.2697
2.3921 2.29 816000 2.2681
2.3921 2.31 824000 2.2740
2.4011 2.34 832000 2.2704
2.4011 2.36 840000 2.2666
2.3948 2.38 848000 2.2689
2.3948 2.4 856000 2.2742
2.3957 2.43 864000 2.2755
2.3957 2.45 872000 2.2689
2.3971 2.47 880000 2.2717
2.3971 2.49 888000 2.2690
2.3982 2.52 896000 2.2645
2.3982 2.54 904000 2.2726
2.4005 2.56 912000 2.2628
2.4005 2.58 920000 2.2726
2.4037 2.6 928000 2.2760
2.4037 2.63 936000 2.2662
2.4031 2.65 944000 2.2729
2.4031 2.67 952000 2.2706
2.4025 2.69 960000 2.2684
2.4025 2.72 968000 2.2635
2.409 2.74 976000 2.2606
2.409 2.76 984000 2.2664
2.4085 2.78 992000 2.2647
2.4085 2.81 1000000 2.2656
2.3971 2.83 1008000 2.2655
2.3971 2.85 1016000 2.2681
2.3946 2.87 1024000 2.2671
2.3946 2.9 1032000 2.2660
2.4063 2.92 1040000 2.2697
2.4063 2.94 1048000 2.2706
2.399 2.96 1056000 2.2625
2.399 2.99 1064000 2.2699
2.4024 3.01 1072000 2.2622
2.4024 3.03 1080000 2.2695
2.4035 3.05 1088000 2.2700
2.4035 3.08 1096000 2.2624
2.4061 3.1 1104000 2.2690
2.4061 3.12 1112000 2.2653
2.4044 3.14 1120000 2.2679
2.4044 3.17 1128000 2.2658
2.3996 3.19 1136000 2.2680
2.3996 3.21 1144000 2.2668
2.3943 3.23 1152000 2.2689
2.3943 3.26 1160000 2.2702
2.3948 3.28 1168000 2.2653
2.3948 3.3 1176000 2.2621
2.4047 3.32 1184000 2.2723
2.4047 3.35 1192000 2.2718
2.4057 3.37 1200000 2.2668
2.4057 3.39 1208000 2.2649
2.3901 3.41 1216000 2.2699
2.3901 3.44 1224000 2.2683
2.3942 3.46 1232000 2.2679
2.3942 3.48 1240000 2.2647
2.4052 3.5 1248000 2.2656
2.4052 3.53 1256000 2.2679
2.401 3.55 1264000 2.2685
2.401 3.57 1272000 2.2654
2.4012 3.59 1280000 2.2607
2.4012 3.62 1288000 2.2668
2.4015 3.64 1296000 2.2672
2.4015 3.66 1304000 2.2685
2.4039 3.68 1312000 2.2675
2.4039 3.71 1320000 2.2702
2.3927 3.73 1328000 2.2689
2.3927 3.75 1336000 2.2674
2.3998 3.77 1344000 2.2694
2.3998 3.8 1352000 2.2649
2.404 3.82 1360000 2.2635
2.404 3.84 1368000 2.2681
2.4023 3.86 1376000 2.2601
2.4023 3.88 1384000 2.2661
2.393 3.91 1392000 2.2613
2.393 3.93 1400000 2.2717
2.402 3.95 1408000 2.2672
2.402 3.97 1416000 2.2637
2.4047 4.0 1424000 2.2705
2.4047 4.02 1432000 2.2682
2.4045 4.04 1440000 2.2630
2.4045 4.06 1448000 2.2699
2.3973 4.09 1456000 2.2579
2.3973 4.11 1464000 2.2601
2.399 4.13 1472000 2.2609
2.399 4.15 1480000 2.2697
2.399 4.18 1488000 2.2630
2.399 4.2 1496000 2.2658
2.3995 4.22 1504000 2.2656
2.3995 4.24 1512000 2.2689
2.3929 4.27 1520000 2.2678
2.3929 4.29 1528000 2.2694
2.404 4.31 1536000 2.2632
2.404 4.33 1544000 2.2657
2.3932 4.36 1552000 2.2642
2.3932 4.38 1560000 2.2607
2.3985 4.4 1568000 2.2635
2.3985 4.42 1576000 2.2645
2.3997 4.45 1584000 2.2654
2.3997 4.47 1592000 2.2672
2.396 4.49 1600000 2.2666
2.396 4.51 1608000 2.2708
2.4012 4.54 1616000 2.2707
2.4012 4.56 1624000 2.2684
2.4074 4.58 1632000 2.2676
2.4074 4.6 1640000 2.2658
2.3965 4.63 1648000 2.2716
2.3965 4.65 1656000 2.2656
2.4021 4.67 1664000 2.2690
2.4021 4.69 1672000 2.2656
2.3981 4.72 1680000 2.2659
2.3981 4.74 1688000 2.2667
2.3974 4.76 1696000 2.2655
2.3974 4.78 1704000 2.2676
2.3964 4.81 1712000 2.2655
2.3964 4.83 1720000 2.2636
2.3933 4.85 1728000 2.2679
2.3933 4.87 1736000 2.2667
2.4066 4.9 1744000 2.2647
2.4066 4.92 1752000 2.2657
2.4027 4.94 1760000 2.2628
2.4027 4.96 1768000 2.2642
2.4029 4.99 1776000 2.2677
2.4029 5.01 1784000 2.2704
2.3958 5.03 1792000 2.2650
2.3958 5.05 1800000 2.2650
2.4054 5.08 1808000 2.2680
2.4054 5.1 1816000 2.2601
2.3984 5.12 1824000 2.2671
2.3984 5.14 1832000 2.2639
2.4005 5.16 1840000 2.2629
2.4005 5.19 1848000 2.2656
2.3962 5.21 1856000 2.2646
2.3962 5.23 1864000 2.2571
2.4033 5.25 1872000 2.2689
2.4033 5.28 1880000 2.2632
2.4064 5.3 1888000 2.2633
2.4064 5.32 1896000 2.2694
2.3967 5.34 1904000 2.2685
2.3967 5.37 1912000 2.2636
2.4002 5.39 1920000 2.2687
2.4002 5.41 1928000 2.2632
2.4045 5.43 1936000 2.2625
2.4045 5.46 1944000 2.2677
2.4096 5.48 1952000 2.2563
2.4096 5.5 1960000 2.2642
2.4004 5.52 1968000 2.2692
2.4004 5.55 1976000 2.2696
2.4065 5.57 1984000 2.2579
2.4065 5.59 1992000 2.2660
2.4025 5.61 2000000 2.2654
2.4025 5.64 2008000 2.2706
2.3993 5.66 2016000 2.2704
2.3993 5.68 2024000 2.2664
2.4034 5.7 2032000 2.2659
2.4034 5.73 2040000 2.2680
2.4004 5.75 2048000 2.2611
2.4004 5.77 2056000 2.2646
2.4025 5.79 2064000 2.2682
2.4025 5.82 2072000 2.2646
2.4063 5.84 2080000 2.2598
2.4063 5.86 2088000 2.2673
2.4071 5.88 2096000 2.2646
2.4071 5.91 2104000 2.2672
2.401 5.93 2112000 2.2648
2.401 5.95 2120000 2.2654
2.402 5.97 2128000 2.2664
2.402 6.0 2136000 2.2683
2.4004 6.02 2144000 2.2618
2.4004 6.04 2152000 2.2669
2.4001 6.06 2160000 2.2630
2.4001 6.09 2168000 2.2632
2.4046 6.11 2176000 2.2696
2.4046 6.13 2184000 2.2641
2.405 6.15 2192000 2.2627
2.405 6.18 2200000 2.2681
2.4063 6.2 2208000 2.2604
2.4063 6.22 2216000 2.2715
2.3991 6.24 2224000 2.2683
2.3991 6.27 2232000 2.2657
2.405 6.29 2240000 2.2645
2.405 6.31 2248000 2.2676
2.3941 6.33 2256000 2.2706
2.3941 6.36 2264000 2.2593
2.4041 6.38 2272000 2.2679
2.4041 6.4 2280000 2.2643
2.4001 6.42 2288000 2.2728
2.4001 6.44 2296000 2.2631
2.3983 6.47 2304000 2.2636
2.3983 6.49 2312000 2.2630
2.4003 6.51 2320000 2.2663
2.4003 6.53 2328000 2.2647
2.3981 6.56 2336000 2.2669
2.3981 6.58 2344000 2.2660
2.3951 6.6 2352000 2.2692
2.3951 6.62 2360000 2.2644
2.4013 6.65 2368000 2.2610
2.4013 6.67 2376000 2.2655
2.4 6.69 2384000 2.2592
2.4 6.71 2392000 2.2666
2.3975 6.74 2400000 2.2685

Framework versions

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