Hugging Face's logo

DouglasPontes
/
2020-Q4-50p-filtered-prog_from_Q3

Fill-Mask
Transformers
PyTorch
roberta
Generated from Trainer
Inference Endpoints
Model card Files Community
2020-Q4-50p-filtered-prog_from_Q3 / README.md
DouglasPontes's picture
DouglasPontes
Training in progress, step 32000
0a190fd verified
preview code
|
raw
history blame
17.5 kB
metadata
license: mit
base_model: cardiffnlp/twitter-roberta-base-2019-90m
tags:
  - generated_from_trainer
model-index:
  - name: 2020-Q4-50p-filtered-random
    results: []

2020-Q4-50p-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: 2.2570

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 0.03 8000 2.5888
2.8176 0.07 16000 2.4814
2.8176 0.1 24000 2.4264
2.5609 0.13 32000 2.3993
2.5609 0.17 40000 2.3761
2.4969 0.2 48000 2.3624
2.4969 0.24 56000 2.3481
2.48 0.27 64000 2.3399
2.48 0.3 72000 2.3289
2.451 0.34 80000 2.3221
2.451 0.37 88000 2.3183
2.4367 0.4 96000 2.3221
2.4367 0.44 104000 2.3142
2.4388 0.47 112000 2.3028
2.4388 0.51 120000 2.3066
2.4215 0.54 128000 2.3013
2.4215 0.57 136000 2.3039
2.4178 0.61 144000 2.2907
2.4178 0.64 152000 2.2996
2.4103 0.67 160000 2.2943
2.4103 0.71 168000 2.2900
2.4122 0.74 176000 2.2902
2.4122 0.77 184000 2.2961
2.4173 0.81 192000 2.2906
2.4173 0.84 200000 2.2925
2.4067 0.88 208000 2.2911
2.4067 0.91 216000 2.2844
2.4059 0.94 224000 2.2855
2.4059 0.98 232000 2.2811
2.4089 1.01 240000 2.2788
2.4089 1.04 248000 2.2796
2.4034 1.08 256000 2.2827
2.4034 1.11 264000 2.2803
2.408 1.15 272000 2.2746
2.408 1.18 280000 2.2851
2.3985 1.21 288000 2.2781
2.3985 1.25 296000 2.2795
2.4009 1.28 304000 2.2777
2.4009 1.31 312000 2.2770
2.4017 1.35 320000 2.2763
2.4017 1.38 328000 2.2734
2.4056 1.41 336000 2.2758
2.4056 1.45 344000 2.2763
2.4017 1.48 352000 2.2700
2.4017 1.52 360000 2.2736
2.3993 1.55 368000 2.2763
2.3993 1.58 376000 2.2792
2.3994 1.62 384000 2.2666
2.3994 1.65 392000 2.2699
2.3969 1.68 400000 2.2753
2.3969 1.72 408000 2.2707
2.4094 1.75 416000 2.2731
2.4094 1.79 424000 2.2709
2.4102 1.82 432000 2.2623
2.4102 1.85 440000 2.2751
2.4042 1.89 448000 2.2728
2.4042 1.92 456000 2.2714
2.3991 1.95 464000 2.2634
2.3991 1.99 472000 2.2695
2.3976 2.02 480000 2.2731
2.3976 2.05 488000 2.2736
2.4019 2.09 496000 2.2803
2.4019 2.12 504000 2.2699
2.4044 2.16 512000 2.2731
2.4044 2.19 520000 2.2709
2.3989 2.22 528000 2.2716
2.3989 2.26 536000 2.2668
2.4068 2.29 544000 2.2728
2.4068 2.32 552000 2.2709
2.4047 2.36 560000 2.2683
2.4047 2.39 568000 2.2731
2.3976 2.43 576000 2.2676
2.3976 2.46 584000 2.2736
2.3994 2.49 592000 2.2624
2.3994 2.53 600000 2.2773
2.3997 2.56 608000 2.2719
2.3997 2.59 616000 2.2701
2.4042 2.63 624000 2.2695
2.4042 2.66 632000 2.2666
2.3994 2.69 640000 2.2719
2.3994 2.73 648000 2.2686
2.3953 2.76 656000 2.2623
2.3953 2.8 664000 2.2662
2.402 2.83 672000 2.2707
2.402 2.86 680000 2.2662
2.3929 2.9 688000 2.2726
2.3929 2.93 696000 2.2682
2.3977 2.96 704000 2.2634
2.3977 3.0 712000 2.2685
2.4022 3.03 720000 2.2693
2.4022 3.07 728000 2.2666
2.4046 3.1 736000 2.2690
2.4046 3.13 744000 2.2641
2.3977 3.17 752000 2.2658
2.3977 3.2 760000 2.2645
2.4015 3.23 768000 2.2619
2.4015 3.27 776000 2.2671
2.393 3.3 784000 2.2694
2.393 3.33 792000 2.2662
2.3907 3.37 800000 2.2691
2.3907 3.4 808000 2.2679
2.3987 3.44 816000 2.2688
2.3987 3.47 824000 2.2655
2.4116 3.5 832000 2.2668
2.4116 3.54 840000 2.2675
2.3913 3.57 848000 2.2689
2.3913 3.6 856000 2.2642
2.3974 3.64 864000 2.2667
2.3974 3.67 872000 2.2717
2.4046 3.71 880000 2.2661
2.4046 3.74 888000 2.2705
2.4006 3.77 896000 2.2637
2.4006 3.81 904000 2.2635
2.3987 3.84 912000 2.2642
2.3987 3.87 920000 2.2691
2.4068 3.91 928000 2.2689
2.4068 3.94 936000 2.2730
2.4092 3.97 944000 2.2644
2.4092 4.01 952000 2.2706
2.4035 4.04 960000 2.2671
2.4035 4.08 968000 2.2562
2.4005 4.11 976000 2.2622
2.4005 4.14 984000 2.2642
2.406 4.18 992000 2.2625
2.406 4.21 1000000 2.2662
2.3972 4.24 1008000 2.2658
2.3972 4.28 1016000 2.2668
2.3937 4.31 1024000 2.2593
2.3937 4.35 1032000 2.2712
2.3982 4.38 1040000 2.2695
2.3982 4.41 1048000 2.2684
2.4034 4.45 1056000 2.2643
2.4034 4.48 1064000 2.2665
2.3996 4.51 1072000 2.2692
2.3996 4.55 1080000 2.2628
2.4054 4.58 1088000 2.2673
2.4054 4.61 1096000 2.2577
2.4039 4.65 1104000 2.2671
2.4039 4.68 1112000 2.2586
2.4033 4.72 1120000 2.2730
2.4033 4.75 1128000 2.2655
2.4036 4.78 1136000 2.2694
2.4036 4.82 1144000 2.2630
2.4036 4.85 1152000 2.2618
2.4036 4.88 1160000 2.2665
2.4005 4.92 1168000 2.2609
2.4005 4.95 1176000 2.2617
2.4065 4.99 1184000 2.2646
2.4065 5.02 1192000 2.2606
2.4044 5.05 1200000 2.2656
2.4044 5.09 1208000 2.2630
2.3997 5.12 1216000 2.2737
2.3997 5.15 1224000 2.2762
2.407 5.19 1232000 2.2669
2.407 5.22 1240000 2.2695
2.4013 5.25 1248000 2.2704
2.4013 5.29 1256000 2.2612
2.4118 5.32 1264000 2.2654
2.4118 5.36 1272000 2.2683
2.3953 5.39 1280000 2.2628
2.3953 5.42 1288000 2.2605
2.3973 5.46 1296000 2.2667
2.3973 5.49 1304000 2.2640
2.4027 5.52 1312000 2.2619
2.4027 5.56 1320000 2.2687
2.3967 5.59 1328000 2.2598
2.3967 5.63 1336000 2.2621
2.4028 5.66 1344000 2.2602
2.4028 5.69 1352000 2.2713
2.4053 5.73 1360000 2.2623
2.4053 5.76 1368000 2.2697
2.3987 5.79 1376000 2.2638
2.3987 5.83 1384000 2.2601
2.3987 5.86 1392000 2.2642
2.3987 5.89 1400000 2.2656
2.401 5.93 1408000 2.2712
2.401 5.96 1416000 2.2639
2.4011 6.0 1424000 2.2646
2.4011 6.03 1432000 2.2669
2.4022 6.06 1440000 2.2619
2.4022 6.1 1448000 2.2580
2.3998 6.13 1456000 2.2612
2.3998 6.16 1464000 2.2652
2.3999 6.2 1472000 2.2610
2.3999 6.23 1480000 2.2567
2.3984 6.27 1488000 2.2590
2.3984 6.3 1496000 2.2565
2.4017 6.33 1504000 2.2658
2.4017 6.37 1512000 2.2626
2.4055 6.4 1520000 2.2656
2.4055 6.43 1528000 2.2622
2.3959 6.47 1536000 2.2691
2.3959 6.5 1544000 2.2604
2.4016 6.53 1552000 2.2599
2.4016 6.57 1560000 2.2655
2.3986 6.6 1568000 2.2684
2.3986 6.64 1576000 2.2716
2.4051 6.67 1584000 2.2605
2.4051 6.7 1592000 2.2569
2.4057 6.74 1600000 2.2687
2.4057 6.77 1608000 2.2571
2.3956 6.8 1616000 2.2664
2.3956 6.84 1624000 2.2612
2.4048 6.87 1632000 2.2643
2.4048 6.91 1640000 2.2633
2.4042 6.94 1648000 2.2634
2.4042 6.97 1656000 2.2637
2.4008 7.01 1664000 2.2619
2.4008 7.04 1672000 2.2579
2.397 7.07 1680000 2.2628
2.397 7.11 1688000 2.2593
2.4044 7.14 1696000 2.2593
2.4044 7.17 1704000 2.2613
2.3979 7.21 1712000 2.2685
2.3979 7.24 1720000 2.2683
2.4017 7.28 1728000 2.2611
2.4017 7.31 1736000 2.2672
2.4017 7.34 1744000 2.2577
2.4017 7.38 1752000 2.2609
2.4018 7.41 1760000 2.2567
2.4018 7.44 1768000 2.2661
2.3905 7.48 1776000 2.2671
2.3905 7.51 1784000 2.2663
2.4063 7.55 1792000 2.2619
2.4063 7.58 1800000 2.2587
2.4015 7.61 1808000 2.2584
2.4015 7.65 1816000 2.2580
2.3984 7.68 1824000 2.2586
2.3984 7.71 1832000 2.2620
2.3962 7.75 1840000 2.2584
2.3962 7.78 1848000 2.2607
2.3998 7.81 1856000 2.2638
2.3998 7.85 1864000 2.2629
2.4005 7.88 1872000 2.2716
2.4005 7.92 1880000 2.2623
2.4006 7.95 1888000 2.2555
2.4006 7.98 1896000 2.2653
2.3946 8.02 1904000 2.2629
2.3946 8.05 1912000 2.2654
2.3983 8.08 1920000 2.2623
2.3983 8.12 1928000 2.2544
2.4038 8.15 1936000 2.2605
2.4038 8.19 1944000 2.2622
2.399 8.22 1952000 2.2600
2.399 8.25 1960000 2.2629
2.3983 8.29 1968000 2.2621
2.3983 8.32 1976000 2.2609
2.4059 8.35 1984000 2.2705
2.4059 8.39 1992000 2.2572
2.4058 8.42 2000000 2.2602
2.4058 8.45 2008000 2.2626
2.3954 8.49 2016000 2.2668
2.3954 8.52 2024000 2.2599
2.3932 8.56 2032000 2.2643
2.3932 8.59 2040000 2.2559
2.4001 8.62 2048000 2.2614
2.4001 8.66 2056000 2.2577
2.3912 8.69 2064000 2.2665
2.3912 8.72 2072000 2.2576
2.4015 8.76 2080000 2.2672
2.4015 8.79 2088000 2.2598
2.4015 8.83 2096000 2.2599
2.4015 8.86 2104000 2.2641
2.399 8.89 2112000 2.2612
2.399 8.93 2120000 2.2607
2.3963 8.96 2128000 2.2633
2.3963 8.99 2136000 2.2567
2.3957 9.03 2144000 2.2630
2.3957 9.06 2152000 2.2597
2.3943 9.09 2160000 2.2624
2.3943 9.13 2168000 2.2599
2.4025 9.16 2176000 2.2578
2.4025 9.2 2184000 2.2640
2.3944 9.23 2192000 2.2562
2.3944 9.26 2200000 2.2660
2.3964 9.3 2208000 2.2556
2.3964 9.33 2216000 2.2697
2.4026 9.36 2224000 2.2652
2.4026 9.4 2232000 2.2571
2.398 9.43 2240000 2.2555
2.398 9.47 2248000 2.2607
2.4038 9.5 2256000 2.2558
2.4038 9.53 2264000 2.2660
2.4027 9.57 2272000 2.2587
2.4027 9.6 2280000 2.2605
2.4025 9.63 2288000 2.2578
2.4025 9.67 2296000 2.2609
2.3969 9.7 2304000 2.2597
2.3969 9.73 2312000 2.2619
2.3886 9.77 2320000 2.2645
2.3886 9.8 2328000 2.2717
2.3942 9.84 2336000 2.2627
2.3942 9.87 2344000 2.2582
2.396 9.9 2352000 2.2634
2.396 9.94 2360000 2.2582
2.3998 9.97 2368000 2.2643
2.3998 10.0 2376000 2.2690
2.4014 10.04 2384000 2.2655
2.4014 10.07 2392000 2.2660
2.4004 10.11 2400000 2.2650

Framework versions

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