Hugging Face's logo

scales-okn
/
docket-language-model

Fill-Mask
Transformers
PyTorch
TensorBoard
deberta-v2
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
2
docket-language-model / README.md
librarian-bot's picture
librarian-bot
Librarian Bot: Add base_model information to model
c5285a2
preview code
|
raw
history blame
14.9 kB
metadata
tags:
  - generated_from_trainer
base_model: microsoft/deberta-v3-large
model-index:
  - name: deberta-v3-large-ddlm
    results: []

deberta-v3-large-ddlm

This model is a fine-tuned version of microsoft/deberta-v3-large on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5241

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: 5e-05
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 42
  • gradient_accumulation_steps: 64
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3.0

Training results

Training Loss Epoch Step Validation Loss
0.9823 0.01 1000 0.9163
0.8817 0.02 2000 0.9022
0.9647 0.03 3000 0.8879
0.8646 0.04 4000 0.8577
0.9159 0.06 5000 0.8677
0.8449 0.07 6000 0.8221
0.8681 0.08 7000 0.8332
0.8738 0.09 8000 0.8334
0.8638 0.1 9000 0.8236
0.9066 0.11 10000 0.8200
0.8686 0.12 11000 0.8092
0.7736 0.13 12000 0.8199
0.8054 0.14 13000 0.7972
0.8934 0.16 14000 0.7998
0.7884 0.17 15000 0.7895
0.8278 0.18 16000 0.7586
0.8482 0.19 17000 0.7562
0.8716 0.2 18000 0.7819
0.8881 0.21 19000 0.7878
0.8397 0.22 20000 0.7989
0.811 0.23 21000 0.7846
0.7762 0.24 22000 0.7753
0.7778 0.25 23000 0.7878
0.737 0.27 24000 0.7473
0.8451 0.28 25000 0.7460
0.823 0.29 26000 0.7300
0.7472 0.3 27000 0.7292
0.8048 0.31 28000 0.7697
0.7962 0.32 29000 0.7359
0.8048 0.33 30000 0.7409
0.8095 0.34 31000 0.7434
0.7451 0.35 32000 0.7534
0.6997 0.37 33000 0.7602
0.8116 0.38 34000 0.7566
0.7963 0.39 35000 0.7245
0.786 0.4 36000 0.7311
0.7991 0.41 37000 0.7230
0.723 0.42 38000 0.7209
0.789 0.43 39000 0.7418
0.7296 0.44 40000 0.7325
0.7363 0.45 41000 0.7134
0.758 0.47 42000 0.6948
0.711 0.48 43000 0.6992
0.7984 0.49 44000 0.7055
0.8402 0.5 45000 0.7108
0.8553 0.51 46000 0.7005
0.7538 0.52 47000 0.7208
0.7169 0.53 48000 0.7291
0.7345 0.54 49000 0.7195
0.758 0.55 50000 0.6694
0.7868 0.56 51000 0.6938
0.6966 0.58 52000 0.6867
0.7389 0.59 53000 0.6862
0.7529 0.6 54000 0.7175
0.7345 0.61 55000 0.6970
0.766 0.62 56000 0.7017
0.7043 0.63 57000 0.6916
0.6474 0.64 58000 0.7129
0.7456 0.65 59000 0.6802
0.7512 0.66 60000 0.6951
0.6816 0.68 61000 0.7072
0.7206 0.69 62000 0.6967
0.6439 0.7 63000 0.6798
0.7309 0.71 64000 0.7163
0.6925 0.72 65000 0.6794
0.6833 0.73 66000 0.6637
0.6643 0.74 67000 0.6855
0.6433 0.75 68000 0.7035
0.7595 0.76 69000 0.7008
0.7214 0.78 70000 0.6618
0.7111 0.79 71000 0.6850
0.7375 0.8 72000 0.6909
0.6779 0.81 73000 0.7042
0.6646 0.82 74000 0.6634
0.6616 0.83 75000 0.7020
0.6762 0.84 76000 0.6638
0.7509 0.85 77000 0.6541
0.6963 0.86 78000 0.6781
0.6949 0.87 79000 0.6576
0.6781 0.89 80000 0.6900
0.65 0.9 81000 0.6835
0.7205 0.91 82000 0.6712
0.6901 0.92 83000 0.6699
0.6972 0.93 84000 0.6456
0.7041 0.94 85000 0.6497
0.6864 0.95 86000 0.6432
0.7308 0.96 87000 0.6497
0.6886 0.97 88000 0.6674
0.6947 0.99 89000 0.6638
0.6567 1.0 90000 0.6242
0.7185 1.01 91000 0.6704
0.7435 1.02 92000 0.6681
0.7108 1.03 93000 0.6619
0.6942 1.04 94000 0.6306
0.6998 1.05 95000 0.6409
0.6481 1.06 96000 0.6476
0.727 1.07 97000 0.6354
0.647 1.09 98000 0.6222
0.6622 1.1 99000 0.6119
0.6346 1.11 100000 0.6471
0.6203 1.12 101000 0.6655
0.6765 1.13 102000 0.6473
0.6703 1.14 103000 0.6308
0.6793 1.15 104000 0.6531
0.683 1.16 105000 0.6693
0.6654 1.17 106000 0.6241
0.6626 1.18 107000 0.6215
0.6976 1.2 108000 0.6479
0.7494 1.21 109000 0.6345
0.691 1.22 110000 0.6322
0.6568 1.23 111000 0.6265
0.705 1.24 112000 0.6281
0.6307 1.25 113000 0.6202
0.6828 1.26 114000 0.6158
0.6403 1.27 115000 0.6495
0.6615 1.28 116000 0.6298
0.6237 1.3 117000 0.6234
0.6707 1.31 118000 0.6267
0.6823 1.32 119000 0.6299
0.6333 1.33 120000 0.6169
0.685 1.34 121000 0.6371
0.6941 1.35 122000 0.6245
0.6358 1.36 123000 0.6291
0.6754 1.37 124000 0.6400
0.6286 1.38 125000 0.6148
0.7036 1.4 126000 0.6033
0.645 1.41 127000 0.6295
0.6578 1.42 128000 0.6348
0.651 1.43 129000 0.6222
0.5558 1.44 130000 0.6231
0.6601 1.45 131000 0.6302
0.6304 1.46 132000 0.6127
0.6177 1.47 133000 0.6047
0.5933 1.48 134000 0.6169
0.6307 1.49 135000 0.6012
0.6018 1.51 136000 0.5900
0.6724 1.52 137000 0.6086
0.6367 1.53 138000 0.6414
0.6515 1.54 139000 0.6267
0.5902 1.55 140000 0.5913
0.6523 1.56 141000 0.5992
0.6005 1.57 142000 0.6128
0.6179 1.58 143000 0.6089
0.6154 1.59 144000 0.6353
0.6298 1.61 145000 0.5997
0.5623 1.62 146000 0.5974
0.5787 1.63 147000 0.6165
0.6099 1.64 148000 0.6246
0.658 1.65 149000 0.6116
0.6567 1.66 150000 0.5938
0.6227 1.67 151000 0.5948
0.5858 1.68 152000 0.5822
0.6227 1.69 153000 0.5802
0.6699 1.71 154000 0.6067
0.5989 1.72 155000 0.6073
0.6184 1.73 156000 0.6124
0.6404 1.74 157000 0.6169
0.639 1.75 158000 0.5997
0.6433 1.76 159000 0.5989
0.5574 1.77 160000 0.5796
0.5983 1.78 161000 0.6036
0.6532 1.79 162000 0.5888
0.6679 1.8 163000 0.6038
0.62 1.82 164000 0.5984
0.5541 1.83 165000 0.6003
0.6192 1.84 166000 0.5786
0.6613 1.85 167000 0.6064
0.5923 1.86 168000 0.6018
0.5894 1.87 169000 0.5912
0.6462 1.88 170000 0.5902
0.5811 1.89 171000 0.6030
0.6358 1.9 172000 0.5915
0.614 1.92 173000 0.5886
0.5969 1.93 174000 0.6084
0.6146 1.94 175000 0.6003
0.6051 1.95 176000 0.5835
0.6268 1.96 177000 0.5999
0.6436 1.97 178000 0.5965
0.6167 1.98 179000 0.5789
0.5647 1.99 180000 0.5669
0.6038 2.0 181000 0.6009
0.6082 2.02 182000 0.5799
0.6483 2.03 183000 0.5716
0.5503 2.04 184000 0.5806
0.6231 2.05 185000 0.5699
0.5892 2.06 186000 0.5979
0.5933 2.07 187000 0.5709
0.594 2.08 188000 0.5719
0.5838 2.09 189000 0.5879
0.6039 2.1 190000 0.5984
0.5911 2.11 191000 0.5953
0.563 2.13 192000 0.5772
0.5671 2.14 193000 0.5771
0.6051 2.15 194000 0.5972
0.5852 2.16 195000 0.5917
0.5757 2.17 196000 0.5819
0.6557 2.18 197000 0.5655
0.6055 2.19 198000 0.5820
0.6067 2.2 199000 0.5801
0.6422 2.21 200000 0.5590
0.624 2.23 201000 0.5573
0.6222 2.24 202000 0.5661
0.5597 2.25 203000 0.5786
0.5746 2.26 204000 0.5622
0.6269 2.27 205000 0.5804
0.6241 2.28 206000 0.5696
0.6519 2.29 207000 0.5367
0.6161 2.3 208000 0.5666
0.5415 2.31 209000 0.5633
0.633 2.33 210000 0.5499
0.5566 2.34 211000 0.5822
0.6158 2.35 212000 0.5826
0.5574 2.36 213000 0.5429
0.5748 2.37 214000 0.5736
0.5818 2.38 215000 0.5599
0.6226 2.39 216000 0.5407
0.5733 2.4 217000 0.5759
0.6268 2.41 218000 0.5725
0.5885 2.42 219000 0.5771
0.5708 2.44 220000 0.5654
0.5783 2.45 221000 0.5756
0.61 2.46 222000 0.5647
0.5848 2.47 223000 0.5532
0.5869 2.48 224000 0.5519
0.5717 2.49 225000 0.5621
0.5675 2.5 226000 0.5446
0.6321 2.51 227000 0.5812
0.568 2.52 228000 0.5673
0.5577 2.54 229000 0.5590
0.5888 2.55 230000 0.5628
0.6389 2.56 231000 0.5828
0.5782 2.57 232000 0.5543
0.5871 2.58 233000 0.5575
0.5593 2.59 234000 0.5625
0.6167 2.6 235000 0.5450
0.5828 2.61 236000 0.5627
0.5411 2.62 237000 0.5498
0.6168 2.64 238000 0.5891
0.6508 2.65 239000 0.5811
0.6322 2.66 240000 0.5649
0.6131 2.67 241000 0.5473
0.5419 2.68 242000 0.5583
0.5685 2.69 243000 0.5635
0.5267 2.7 244000 0.5481
0.5357 2.71 245000 0.5474
0.585 2.72 246000 0.5281
0.5894 2.73 247000 0.5457
0.5665 2.75 248000 0.5579
0.5409 2.76 249000 0.5412
0.6051 2.77 250000 0.5447
0.5866 2.78 251000 0.5535
0.5348 2.79 252000 0.5377
0.5606 2.8 253000 0.5524
0.5142 2.81 254000 0.5441
0.543 2.82 255000 0.5499
0.5763 2.83 256000 0.5241

Framework versions

  • Transformers 4.20.0.dev0
  • Pytorch 1.10.0+cu102
  • Datasets 1.15.1
  • Tokenizers 0.11.0