20230824042730
This model is a fine-tuned version of bert-large-cased on the super_glue dataset. It achieves the following results on the evaluation set:
- Loss: 1.5547
- Accuracy: 0.7581
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: 0.003
- train_batch_size: 4
- eval_batch_size: 8
- seed: 11
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 60.0
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
1.1252 | 1.0 | 623 | 0.6915 | 0.5415 |
0.9382 | 2.0 | 1246 | 0.7221 | 0.5307 |
1.0555 | 3.0 | 1869 | 0.7387 | 0.5199 |
0.9336 | 4.0 | 2492 | 0.9751 | 0.6390 |
0.8894 | 5.0 | 3115 | 0.9277 | 0.6643 |
0.9066 | 6.0 | 3738 | 1.1836 | 0.6931 |
0.8496 | 7.0 | 4361 | 0.8242 | 0.7184 |
0.7761 | 8.0 | 4984 | 0.9061 | 0.6859 |
0.8175 | 9.0 | 5607 | 0.7474 | 0.7220 |
0.7575 | 10.0 | 6230 | 0.8582 | 0.7292 |
0.747 | 11.0 | 6853 | 0.8351 | 0.7256 |
0.728 | 12.0 | 7476 | 0.8912 | 0.7148 |
0.8296 | 13.0 | 8099 | 0.9471 | 0.7220 |
0.7327 | 14.0 | 8722 | 1.1407 | 0.7148 |
0.7284 | 15.0 | 9345 | 0.7681 | 0.7256 |
0.6642 | 16.0 | 9968 | 1.4084 | 0.6679 |
0.5888 | 17.0 | 10591 | 0.8413 | 0.7329 |
0.6074 | 18.0 | 11214 | 0.7461 | 0.7401 |
0.625 | 19.0 | 11837 | 0.9516 | 0.7545 |
0.5911 | 20.0 | 12460 | 1.3395 | 0.7292 |
0.5322 | 21.0 | 13083 | 1.3924 | 0.7509 |
0.5247 | 22.0 | 13706 | 1.1553 | 0.7256 |
0.5146 | 23.0 | 14329 | 1.6692 | 0.7040 |
0.4493 | 24.0 | 14952 | 1.2315 | 0.7437 |
0.399 | 25.0 | 15575 | 1.2710 | 0.7545 |
0.3644 | 26.0 | 16198 | 1.5049 | 0.7473 |
0.4031 | 27.0 | 16821 | 1.5735 | 0.7401 |
0.386 | 28.0 | 17444 | 1.4749 | 0.7220 |
0.3735 | 29.0 | 18067 | 0.9541 | 0.7365 |
0.356 | 30.0 | 18690 | 1.3936 | 0.7473 |
0.3496 | 31.0 | 19313 | 0.9982 | 0.7437 |
0.3149 | 32.0 | 19936 | 0.9572 | 0.7581 |
0.3094 | 33.0 | 20559 | 1.5663 | 0.7256 |
0.2886 | 34.0 | 21182 | 1.5993 | 0.7365 |
0.2545 | 35.0 | 21805 | 1.1515 | 0.7545 |
0.276 | 36.0 | 22428 | 1.2768 | 0.7473 |
0.2645 | 37.0 | 23051 | 1.4290 | 0.7509 |
0.262 | 38.0 | 23674 | 1.2363 | 0.7617 |
0.2261 | 39.0 | 24297 | 1.3446 | 0.7617 |
0.2291 | 40.0 | 24920 | 1.0532 | 0.7509 |
0.2178 | 41.0 | 25543 | 1.4745 | 0.7509 |
0.2104 | 42.0 | 26166 | 1.3830 | 0.7545 |
0.217 | 43.0 | 26789 | 1.7099 | 0.7473 |
0.214 | 44.0 | 27412 | 1.7054 | 0.7401 |
0.1856 | 45.0 | 28035 | 1.4350 | 0.7545 |
0.2014 | 46.0 | 28658 | 1.7266 | 0.7473 |
0.1759 | 47.0 | 29281 | 1.2659 | 0.7581 |
0.2027 | 48.0 | 29904 | 1.8336 | 0.7401 |
0.1871 | 49.0 | 30527 | 1.3398 | 0.7509 |
0.1586 | 50.0 | 31150 | 1.4948 | 0.7509 |
0.1619 | 51.0 | 31773 | 1.3787 | 0.7545 |
0.1665 | 52.0 | 32396 | 1.6532 | 0.7545 |
0.1786 | 53.0 | 33019 | 1.4697 | 0.7581 |
0.1609 | 54.0 | 33642 | 1.5462 | 0.7653 |
0.1304 | 55.0 | 34265 | 1.3577 | 0.7581 |
0.1576 | 56.0 | 34888 | 1.7004 | 0.7617 |
0.1522 | 57.0 | 35511 | 1.4629 | 0.7581 |
0.1496 | 58.0 | 36134 | 1.6336 | 0.7581 |
0.1406 | 59.0 | 36757 | 1.5699 | 0.7545 |
0.1268 | 60.0 | 37380 | 1.5547 | 0.7581 |
Framework versions
- Transformers 4.26.1
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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