Hugging Face's logo

Onutoa
/
1_1e-2_10_0.1

Text Classification
Transformers
PyTorch
bert
Generated from Trainer
Inference Endpoints
Model card Files Community
1_1e-2_10_0.1 / README.md
Onutoa's picture
Onutoa
update model card README.md
b20344a
preview code
|
raw
history blame contribute delete
7.59 kB
metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - super_glue
metrics:
  - accuracy
model-index:
  - name: 1_1e-2_10_0.1
    results: []

1_1e-2_10_0.1

This model is a fine-tuned version of bert-large-uncased on the super_glue dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9213
  • Accuracy: 0.7489

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: 0.01
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 11
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 100.0

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.8284 1.0 590 2.0796 0.6220
1.4411 2.0 1180 1.1449 0.6220
1.3365 3.0 1770 1.0330 0.6217
1.305 4.0 2360 0.9705 0.6349
1.1782 5.0 2950 0.9411 0.6339
1.1021 6.0 3540 1.4542 0.6223
1.091 7.0 4130 1.3703 0.4969
0.9725 8.0 4720 1.4839 0.6425
0.9313 9.0 5310 0.7887 0.7009
0.8889 10.0 5900 0.8354 0.7052
0.8457 11.0 6490 0.8120 0.6807
0.7264 12.0 7080 0.9915 0.6190
0.7354 13.0 7670 0.7554 0.7205
0.686 14.0 8260 0.8069 0.7183
0.6549 15.0 8850 0.7395 0.7379
0.6278 16.0 9440 0.7282 0.7275
0.5753 17.0 10030 0.9035 0.6795
0.5773 18.0 10620 0.8699 0.6887
0.5437 19.0 11210 0.7501 0.7226
0.5266 20.0 11800 0.9360 0.7336
0.509 21.0 12390 0.8204 0.7199
0.497 22.0 12980 0.7944 0.7343
0.4379 23.0 13570 0.8074 0.7147
0.4276 24.0 14160 0.8147 0.7306
0.4132 25.0 14750 0.8578 0.7373
0.3944 26.0 15340 0.9502 0.7015
0.3845 27.0 15930 0.8962 0.7021
0.3754 28.0 16520 0.8571 0.7275
0.3478 29.0 17110 0.8433 0.7373
0.3561 30.0 17700 0.8819 0.7327
0.3301 31.0 18290 0.8623 0.7382
0.3217 32.0 18880 0.9132 0.7419
0.3182 33.0 19470 0.9184 0.7281
0.2892 34.0 20060 0.8482 0.7358
0.2915 35.0 20650 0.8988 0.7474
0.2816 36.0 21240 0.8834 0.7446
0.2763 37.0 21830 0.9208 0.7251
0.2679 38.0 22420 0.8656 0.7379
0.2785 39.0 23010 0.9177 0.7315
0.2551 40.0 23600 0.9989 0.7508
0.2491 41.0 24190 0.9483 0.7505
0.2482 42.0 24780 0.8921 0.7391
0.2577 43.0 25370 0.9175 0.7459
0.24 44.0 25960 0.9345 0.7453
0.2368 45.0 26550 0.9161 0.7428
0.2261 46.0 27140 0.8859 0.7315
0.2317 47.0 27730 0.8984 0.7437
0.218 48.0 28320 0.8986 0.7465
0.224 49.0 28910 0.8665 0.7431
0.2064 50.0 29500 0.8869 0.7492
0.2163 51.0 30090 0.8786 0.7394
0.2145 52.0 30680 0.9545 0.7446
0.1998 53.0 31270 0.8586 0.7462
0.2008 54.0 31860 0.9008 0.7446
0.1978 55.0 32450 0.9236 0.7471
0.2025 56.0 33040 0.8906 0.7474
0.1903 57.0 33630 0.9517 0.7459
0.1846 58.0 34220 0.9696 0.7529
0.1819 59.0 34810 0.9163 0.7419
0.1883 60.0 35400 0.9419 0.7373
0.1851 61.0 35990 0.9657 0.7419
0.1805 62.0 36580 0.9279 0.7413
0.1866 63.0 37170 0.8996 0.7495
0.1752 64.0 37760 0.9427 0.7554
0.1703 65.0 38350 0.9364 0.7379
0.1702 66.0 38940 0.9546 0.7502
0.1688 67.0 39530 0.9265 0.7498
0.1724 68.0 40120 0.9043 0.7446
0.1635 69.0 40710 0.9426 0.7465
0.1652 70.0 41300 0.9702 0.7471
0.1643 71.0 41890 0.9191 0.7379
0.1684 72.0 42480 0.9362 0.7526
0.1575 73.0 43070 0.9399 0.7511
0.1585 74.0 43660 0.9585 0.7483
0.1551 75.0 44250 0.9481 0.7532
0.1587 76.0 44840 0.9233 0.7483
0.1499 77.0 45430 0.9115 0.7508
0.1541 78.0 46020 0.9531 0.7535
0.1505 79.0 46610 0.9306 0.7456
0.1521 80.0 47200 0.9185 0.7535
0.1448 81.0 47790 0.9228 0.7459
0.1475 82.0 48380 0.9214 0.7446
0.1491 83.0 48970 0.9355 0.7465
0.1433 84.0 49560 0.9403 0.7523
0.1416 85.0 50150 0.9270 0.7492
0.1391 86.0 50740 0.9208 0.7517
0.1391 87.0 51330 0.9134 0.7517
0.1415 88.0 51920 0.9198 0.7486
0.1343 89.0 52510 0.9380 0.7483
0.128 90.0 53100 0.9429 0.7505
0.1328 91.0 53690 0.9211 0.7529
0.1311 92.0 54280 0.9180 0.7431
0.1383 93.0 54870 0.9522 0.7535
0.133 94.0 55460 0.9047 0.7486
0.1331 95.0 56050 0.9339 0.7526
0.1304 96.0 56640 0.9177 0.7480
0.1293 97.0 57230 0.9194 0.7471
0.128 98.0 57820 0.9213 0.7492
0.1268 99.0 58410 0.9260 0.7492
0.1297 100.0 59000 0.9213 0.7489

Framework versions

  • Transformers 4.30.0
  • Pytorch 2.0.1+cu117
  • Datasets 2.14.4
  • Tokenizers 0.13.3