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metadata
tags:
  - generated_from_trainer
model-index:
  - name: patentbert-cased-2b-seq-2560
    results: []
from transformers import AutoModel, AutoTokenizer

# Load pre-trained model and tokenizer
model_name = "dheerajpai/patentbert-cased-2b-seq-2560"
model = AutoModel.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)

# Tokenize input text
input_text = "A method for predicting the future"
input_ids = tokenizer(input_text, return_tensors="pt")

# Get embeddings
import torch
with torch.no_grad():
    outputs = model(**input_ids)
    embeddings = outputs.last_hidden_state

# Print embeddings
print(embeddings)



This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment.

patentbert-cased-2b-seq-2560

This model is a foundational model that is trained on HUPD Dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7631

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: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss
10.3108 0.0 500 10.2972
10.1051 0.0 1000 10.0832
9.8252 0.0 1500 nan
9.585 0.0 2000 9.5358
9.3422 0.0 2500 9.3382
9.171 0.0 3000 9.1602
8.8067 0.0 3500 8.8285
8.6069 0.0 4000 8.6089
8.3746 0.0 4500 8.4192
8.0536 0.0 5000 8.0997
7.8671 0.01 5500 7.8348
7.6091 0.01 6000 7.6633
7.3797 0.01 6500 7.3655
7.2716 0.01 7000 7.1536
7.0645 0.01 7500 6.9757
7.1671 0.01 8000 7.1558
6.9607 0.01 8500 7.1138
7.0289 0.01 9000 6.8836
6.8139 0.01 9500 6.7857
6.8424 0.01 10000 6.9236
6.7113 0.01 10500 6.9056
6.8353 0.01 11000 6.8248
6.7775 0.01 11500 6.7361
6.7572 0.01 12000 6.5039
6.5891 0.01 12500 6.7092
6.6666 0.01 13000 6.7711
6.5264 0.01 13500 6.5961
6.6102 0.01 14000 6.6122
6.6613 0.01 14500 6.5437
6.5007 0.01 15000 6.6745
6.5923 0.02 15500 6.4211
6.4733 0.02 16000 nan
6.5177 0.02 16500 6.4441
6.4695 0.02 17000 6.4167
6.468 0.02 17500 nan
6.4366 0.02 18000 6.4643
6.3223 0.02 18500 6.3400
6.4059 0.02 19000 6.4455
6.3487 0.02 19500 6.4198
6.2694 0.02 20000 6.2709
6.3494 0.02 20500 6.3544
6.4325 0.02 21000 6.3966
6.1486 0.02 21500 6.1809
6.2384 0.02 22000 6.1942
6.3231 0.02 22500 6.1774
6.22 0.02 23000 6.1428
6.2379 0.02 23500 6.1543
6.1446 0.02 24000 6.4025
6.2554 0.02 24500 6.2696
6.1878 0.02 25000 6.1100
6.1791 0.03 25500 6.2361
5.9089 0.03 26000 6.0577
6.1151 0.03 26500 5.9858
6.08 0.03 27000 6.0933
6.1131 0.03 27500 6.1432
6.1 0.03 28000 6.0211
6.0719 0.03 28500 6.0765
6.0946 0.03 29000 5.9564
5.97 0.03 29500 6.1308
5.9956 0.03 30000 5.9477
6.0646 0.03 30500 5.8772
6.0831 0.03 31000 5.8322
6.104 0.03 31500 6.0062
5.8465 0.03 32000 5.7755
5.9233 0.03 32500 6.0247
5.9325 0.03 33000 5.8521
5.9619 0.03 33500 5.9103
5.948 0.03 34000 5.7352
5.8996 0.03 34500 5.8461
5.8479 0.03 35000 5.8702
5.8515 0.04 35500 5.8775
5.8718 0.04 36000 5.8950
5.9758 0.04 36500 5.9297
5.8583 0.04 37000 5.6992
5.8591 0.04 37500 5.7497
5.7199 0.04 38000 5.6971
5.858 0.04 38500 5.7512
5.8578 0.04 39000 5.7475
5.7426 0.04 39500 5.7610
5.7427 0.04 40000 5.7675
5.7374 0.04 40500 5.7163
5.6564 0.04 41000 5.7539
5.7734 0.04 41500 5.7654
5.7775 0.04 42000 5.6227
5.6601 0.04 42500 5.8363
5.7822 0.04 43000 5.7640
5.659 0.04 43500 5.5969
5.7551 0.04 44000 5.5721
5.5936 0.04 44500 5.6323
5.6782 0.04 45000 5.6320
5.6217 0.05 45500 5.7216
5.6243 0.05 46000 5.7571
5.5589 0.05 46500 5.6128
5.6897 0.05 47000 5.4603
5.5028 0.05 47500 5.6687
5.628 0.05 48000 5.5962
5.6578 0.05 48500 5.5450
5.5513 0.05 49000 5.6963
5.6322 0.05 49500 5.5455
5.5783 0.05 50000 5.4846
5.5091 0.05 50500 5.5800
5.5177 0.05 51000 5.5642
5.5917 0.05 51500 5.4345
5.5996 0.05 52000 5.5709
5.4707 0.05 52500 5.4512
5.5662 0.05 53000 5.5459
5.6362 0.05 53500 5.3636
5.4621 0.05 54000 5.4129
5.5071 0.05 54500 5.4666
5.4123 0.05 55000 5.5095
5.5336 0.06 55500 5.4275
5.4836 0.06 56000 5.4120
5.5995 0.06 56500 5.4324
5.5469 0.06 57000 5.2927
5.4154 0.06 57500 5.4637
5.471 0.06 58000 5.3241
5.5797 0.06 58500 5.4726
5.5169 0.06 59000 5.5312
5.3527 0.06 59500 5.5792
5.4948 0.06 60000 5.6725
5.3375 0.06 60500 5.3917
5.3983 0.06 61000 5.4772
5.3293 0.06 61500 5.4511
5.4525 0.06 62000 5.3458
5.519 0.06 62500 5.3215
5.4592 0.06 63000 5.2476
5.5163 0.06 63500 5.4829
5.3263 0.06 64000 5.2511
5.4157 0.06 64500 5.5367
5.5014 0.06 65000 5.4259
5.2952 0.07 65500 5.1938
5.3977 0.07 66000 5.5348
5.3704 0.07 66500 5.3582
5.3516 0.07 67000 5.4562
5.3519 0.07 67500 5.2855
5.4913 0.07 68000 5.3189
5.4046 0.07 68500 5.3860
5.2793 0.07 69000 5.3688
5.3197 0.07 69500 nan
5.2306 0.07 70000 5.3194
5.4705 0.07 70500 nan
5.2994 0.07 71000 5.1970
5.2489 0.07 71500 nan
5.35 0.07 72000 5.1307
5.367 0.07 72500 5.1823
5.3014 0.07 73000 5.3477
5.3133 0.07 73500 5.2823
5.308 0.07 74000 5.3723
5.228 0.07 74500 5.3760
5.3351 0.07 75000 5.2688
5.3312 0.08 75500 5.3148
5.2935 0.08 76000 5.4694
5.2833 0.08 76500 5.2810
5.2742 0.08 77000 5.1937
5.1953 0.08 77500 5.2168
5.2382 0.08 78000 nan
5.1734 0.08 78500 5.1098
5.3006 0.08 79000 5.3727
5.1816 0.08 79500 5.3007
5.3119 0.08 80000 nan
5.2583 0.08 80500 5.0899
5.0782 0.08 81000 5.3198
5.3114 0.08 81500 5.2453
5.272 0.08 82000 5.1199
5.2827 0.08 82500 5.1879
5.3218 0.08 83000 5.0042
5.1726 0.08 83500 nan
5.3344 0.08 84000 nan
5.2826 0.08 84500 5.2514
5.3085 0.08 85000 5.1459
5.2664 0.09 85500 5.2593
5.3743 0.09 86000 5.3096
5.341 0.09 86500 5.3054
5.2509 0.09 87000 5.2503
5.2329 0.09 87500 5.1273
5.3716 0.09 88000 5.1140
5.0893 0.09 88500 5.2895
5.2501 0.09 89000 5.3515
5.2556 0.09 89500 5.3965
5.2715 0.09 90000 4.9594
5.1421 0.09 90500 5.4293
5.2206 0.09 91000 5.1499
5.0447 0.09 91500 5.1303
5.1432 0.09 92000 nan
5.1847 0.09 92500 5.3791
5.1638 0.09 93000 4.9793
5.1862 0.09 93500 5.1570
5.1576 0.09 94000 5.0856
5.2095 0.09 94500 5.1610
5.1446 0.09 95000 5.0668
5.1084 0.1 95500 5.1512
5.2135 0.1 96000 5.3496
5.2005 0.1 96500 nan
5.0792 0.1 97000 4.9646
5.0845 0.1 97500 5.1137
5.3104 0.1 98000 5.1792
5.2235 0.1 98500 4.9565
5.0976 0.1 99000 5.2577
5.3409 0.1 99500 5.1923
5.0521 0.1 100000 5.0434
5.25 0.1 100500 nan
5.1161 0.1 101000 5.1386
5.0612 0.1 101500 nan
5.0001 0.1 102000 5.1310
5.2386 0.1 102500 5.0340
5.2105 0.1 103000 5.1773
5.2084 0.1 103500 5.1247
5.0763 0.1 104000 5.1326
5.1643 0.1 104500 5.1616
5.084 0.1 105000 5.0687
5.1146 0.11 105500 5.2083
5.1201 0.11 106000 5.1106
5.0894 0.11 106500 5.0553
5.1971 0.11 107000 5.2672
5.1201 0.11 107500 5.1432
5.0814 0.11 108000 nan
5.073 0.11 108500 5.2188
5.0756 0.11 109000 5.2541
5.0874 0.11 109500 5.1205
5.1272 0.11 110000 5.1913
4.8945 0.11 110500 nan
5.0255 0.11 111000 5.1739
5.104 0.11 111500 5.0617
5.1365 0.11 112000 4.8285
5.1029 0.11 112500 5.1033
5.0535 0.11 113000 4.9960
4.9839 0.11 113500 4.9242
5.0797 0.11 114000 nan
4.9397 0.11 114500 5.0119
5.0802 0.11 115000 5.0234
5.0841 0.12 115500 5.0896
5.0425 0.12 116000 5.1255
5.0101 0.12 116500 5.1633
5.0221 0.12 117000 4.9497
5.1098 0.12 117500 nan
5.0613 0.12 118000 5.0107
5.1104 0.12 118500 4.8609
4.993 0.12 119000 nan
5.059 0.12 119500 5.1214
4.9553 0.12 120000 5.0494
5.1097 0.12 120500 4.8121
5.0657 0.12 121000 4.9866
5.0954 0.12 121500 5.0809
4.974 0.12 122000 5.1170
5.0931 0.12 122500 5.1628
5.0726 0.12 123000 4.9747
5.077 0.12 123500 4.9684
4.9644 0.12 124000 4.9622
5.0906 0.12 124500 5.0708
4.956 0.12 125000 5.0252
4.8863 0.13 125500 4.8449
5.1082 0.13 126000 4.8806
5.0773 0.13 126500 4.9116
4.8896 0.13 127000 5.1229
4.8766 0.13 127500 5.0384
4.9869 0.13 128000 5.1335
4.9558 0.13 128500 5.1123
4.9828 0.13 129000 4.8389
5.1223 0.13 129500 4.9417
5.0064 0.13 130000 4.9984
5.0859 0.13 130500 5.0096
4.943 0.13 131000 nan
4.9274 0.13 131500 4.8440
5.0719 0.13 132000 4.9418
4.9647 0.13 132500 5.0342
4.9271 0.13 133000 4.8805
5.0476 0.13 133500 5.0476
5.0446 0.13 134000 5.0132
4.9754 0.13 134500 4.9995
5.0001 0.13 135000 4.9921
5.0542 0.14 135500 4.8779
5.0162 0.14 136000 4.8671
5.1442 0.14 136500 nan
5.0029 0.14 137000 4.9190
4.9366 0.14 137500 4.8176
4.96 0.14 138000 4.9705
5.0691 0.14 138500 4.9670
4.9975 0.14 139000 4.9877
4.7967 0.14 139500 4.9331
4.9496 0.14 140000 4.9342
5.0449 0.14 140500 4.9601
4.9804 0.14 141000 4.9119
4.9473 0.14 141500 4.8596
4.9562 0.14 142000 4.9853
4.9063 0.14 142500 4.7850
4.9701 0.14 143000 5.0711
4.9089 0.14 143500 5.0360
4.8403 0.14 144000 4.9165
4.989 0.14 144500 5.0046
4.9967 0.14 145000 4.8406
4.8871 0.14 145500 nan
5.0179 0.15 146000 4.8793
4.9366 0.15 146500 4.7137
4.9206 0.15 147000 4.9649
4.9735 0.15 147500 4.8197
4.9212 0.15 148000 4.9675
4.8773 0.15 148500 4.7220
4.9446 0.15 149000 4.8134
4.9369 0.15 149500 5.0508
4.9514 0.15 150000 4.8808
4.8955 0.15 150500 nan
4.958 0.15 151000 4.8736
4.7584 0.15 151500 4.7126
4.8966 0.15 152000 4.8752
4.752 0.15 152500 4.8972
4.8869 0.15 153000 4.8670
4.8554 0.15 153500 4.6702
4.8551 0.15 154000 nan
4.9096 0.15 154500 4.8019
4.7414 0.15 155000 4.7015
4.9376 0.15 155500 4.7915
4.8313 0.16 156000 4.7908
4.8848 0.16 156500 4.5982
4.8155 0.16 157000 4.7690
4.7999 0.16 157500 4.7613
4.8956 0.16 158000 4.9168
4.786 0.16 158500 4.9093
4.7222 0.16 159000 4.8725
4.8093 0.16 159500 4.6335
4.891 0.16 160000 4.9281
4.7131 0.16 160500 4.8461
4.8382 0.16 161000 nan
4.681 0.16 161500 4.7026
4.8793 0.16 162000 4.5926
4.7656 0.16 162500 4.6321
4.7977 0.16 163000 4.6786
4.7427 0.16 163500 4.7494
4.8589 0.16 164000 4.7973
4.9484 0.16 164500 4.7792
4.7759 0.16 165000 4.8411
4.775 0.16 165500 4.5031
4.6852 0.17 166000 4.6319
4.678 0.17 166500 4.4804
4.6859 0.17 167000 4.3519
4.5622 0.17 167500 4.6006
4.4071 0.17 168000 nan
4.5024 0.17 168500 4.4991
4.6905 0.17 169000 4.4173
4.4859 0.17 169500 4.3873
4.5052 0.17 170000 4.1469
4.3587 0.17 170500 3.8055
4.456 0.17 171000 4.1394
4.3458 0.17 171500 4.0963
4.2893 0.17 172000 4.2467
4.2879 0.17 172500 4.1487
4.3218 0.17 173000 4.1782
4.2976 0.17 173500 4.1867
4.2087 0.17 174000 4.0386
4.2653 0.17 174500 4.0119
4.1096 0.17 175000 4.2030
4.0391 0.17 175500 3.9293
4.0848 0.18 176000 3.7016
4.1159 0.18 176500 4.1230
3.9837 0.18 177000 nan
4.1074 0.18 177500 3.8607
4.0702 0.18 178000 3.9369
3.8135 0.18 178500 3.8203
3.936 0.18 179000 3.6830
3.95 0.18 179500 3.6186
3.9935 0.18 180000 3.5923
4.0053 0.18 180500 3.4808
3.8986 0.18 181000 3.6185
4.1166 0.18 181500 3.8901
4.0373 0.18 182000 3.9097
3.8312 0.18 182500 3.7495
3.7596 0.18 183000 3.6929
3.771 0.18 183500 3.4781
3.9007 0.18 184000 3.6396
3.6432 0.18 184500 3.8321
3.6861 0.18 185000 3.7202
3.764 0.18 185500 3.5643
3.8885 0.19 186000 3.5166
3.644 0.19 186500 3.5768
3.8086 0.19 187000 3.4721
3.7104 0.19 187500 3.5530
3.7079 0.19 188000 3.5369
3.6162 0.19 188500 3.3808
3.6456 0.19 189000 3.5744
3.5931 0.19 189500 3.3176
3.7159 0.19 190000 3.2284
3.5938 0.19 190500 3.1965
3.526 0.19 191000 3.3849
3.5559 0.19 191500 3.5148
3.6142 0.19 192000 3.3375
3.583 0.19 192500 3.0472
3.4242 0.19 193000 3.4076
3.3964 0.19 193500 3.2054
3.4507 0.19 194000 3.2950
3.3661 0.19 194500 3.0554
3.407 0.19 195000 3.0494
3.346 0.19 195500 3.1238
3.3785 0.2 196000 3.1012
3.182 0.2 196500 2.8919
3.3367 0.2 197000 3.0999
3.2987 0.2 197500 2.8941
3.0248 0.2 198000 2.9771
3.405 0.2 198500 2.8544
3.2292 0.2 199000 2.8955
2.9835 0.2 199500 2.8065
3.349 0.2 200000 2.7614
3.0754 0.2 200500 2.7383
3.2153 0.2 201000 2.7829
2.9064 0.2 201500 2.5079
2.7192 0.2 202000 2.7502
2.9335 0.2 202500 2.6825
2.8794 0.2 203000 2.5354
2.9583 0.2 203500 2.7660
2.9196 0.2 204000 2.4501
2.736 0.2 204500 2.6040
2.864 0.2 205000 2.2898
2.6318 0.2 205500 2.2793
2.828 0.21 206000 2.1573
2.7871 0.21 206500 2.3254
2.6693 0.21 207000 2.3778
2.7007 0.21 207500 2.3653
2.7447 0.21 208000 2.3186
2.8414 0.21 208500 2.0390
2.5687 0.21 209000 2.3767
2.5098 0.21 209500 2.1557
2.6272 0.21 210000 2.1714
2.9166 0.21 210500 2.1061
2.5423 0.21 211000 2.1971
2.4275 0.21 211500 2.2001
2.5763 0.21 212000 2.3593
2.3555 0.21 212500 nan
2.5078 0.21 213000 1.9354
2.3763 0.21 213500 2.2007
2.2813 0.21 214000 2.1125
2.6017 0.21 214500 2.0470
2.5325 0.21 215000 2.0185
2.5335 0.21 215500 2.0580
2.495 0.22 216000 2.0935
2.4319 0.22 216500 2.0109
2.2747 0.22 217000 1.8986
2.3316 0.22 217500 2.0196
2.3834 0.22 218000 1.8775
2.3406 0.22 218500 2.0477
2.352 0.22 219000 nan
2.271 0.22 219500 1.9934
2.3377 0.22 220000 2.0494
2.3768 0.22 220500 nan
2.3557 0.22 221000 nan
2.3068 0.22 221500 2.2126
2.3616 0.22 222000 nan
2.3619 0.22 222500 1.9602
2.2602 0.22 223000 1.8290
2.2516 0.22 223500 1.8721
2.1106 0.22 224000 1.8527
2.1877 0.22 224500 nan
2.2805 0.22 225000 2.0094
2.3053 0.22 225500 1.9346
2.1862 0.23 226000 1.9152
2.2604 0.23 226500 1.7553
2.1791 0.23 227000 2.0891
2.2407 0.23 227500 1.8452
2.0978 0.23 228000 nan
2.1384 0.23 228500 2.0158
2.149 0.23 229000 1.7843
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2.1842 0.23 230000 1.6995
1.9767 0.23 230500 1.8023
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2.1801 0.23 231500 1.7378
2.1145 0.23 232000 2.1310
2.0712 0.23 232500 1.8601
1.988 0.23 233000 1.6978
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2.1182 0.23 234000 1.7814
1.8749 0.23 234500 1.4981
1.8677 0.23 235000 1.8330
1.9593 0.23 235500 1.6507
2.2362 0.24 236000 1.8061
2.0682 0.24 236500 1.6051
1.9664 0.24 237000 1.7702
1.9273 0.24 237500 1.8628
2.0707 0.24 238000 nan
1.9 0.24 238500 1.8365
1.9824 0.24 239000 1.6568
2.2663 0.24 239500 1.8440
1.8693 0.24 240000 1.8191
1.9319 0.24 240500 1.8056
1.9543 0.24 241000 2.0462
2.1437 0.24 241500 1.7123
1.7062 0.24 242000 1.5814
1.8035 0.24 242500 1.8891
1.955 0.24 243000 nan
1.8476 0.24 243500 1.7330
1.8361 0.24 244000 1.8884
2.0996 0.24 244500 1.5817
1.898 0.24 245000 1.6666
1.8617 0.24 245500 1.6905
1.9938 0.25 246000 1.7288
1.8993 0.25 246500 1.5452
2.0614 0.25 247000 1.6925
1.9841 0.25 247500 1.6353
1.988 0.25 248000 1.7163
1.9573 0.25 248500 1.8355
1.7605 0.25 249000 1.7693
1.8335 0.25 249500 nan
1.8563 0.25 250000 1.9049
1.9492 0.25 250500 1.8820
2.0465 0.25 251000 nan
2.0284 0.25 251500 1.5709
1.7657 0.25 252000 1.5673
1.9065 0.25 252500 1.7573
1.8689 0.25 253000 1.6787
1.8239 0.25 253500 1.5488
1.7079 0.25 254000 1.6740
1.8035 0.25 254500 1.6096
1.8439 0.25 255000 1.6126
1.7429 0.25 255500 1.6894
1.8663 0.26 256000 1.5178
1.7599 0.26 256500 1.7082
1.8221 0.26 257000 1.4887
1.9287 0.26 257500 1.5528
1.8538 0.26 258000 1.6779
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1.02 0.99 998500 1.0209
1.1344 1.0 999000 0.9050
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1.1997 1.0 1000000 0.9012
1.0085 1.0 1000500 1.1230
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0.9979 1.0 1001500 0.7978
1.0444 1.0 1002000 1.0917
0.9184 1.0 1002500 0.9623
1.05 1.0 1003000 0.8484
1.1686 1.0 1003500 0.7631

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.1.2+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.1