20230822011214
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: 13.1424
- Accuracy: 0.4729
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: 0.0005
- train_batch_size: 8
- 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 |
---|---|---|---|---|
No log | 1.0 | 312 | 34.1366 | 0.4729 |
34.4899 | 2.0 | 624 | 31.6158 | 0.4982 |
34.4899 | 3.0 | 936 | 29.7502 | 0.4765 |
31.3598 | 4.0 | 1248 | 29.3626 | 0.5018 |
29.6767 | 5.0 | 1560 | 29.1220 | 0.4729 |
29.6767 | 6.0 | 1872 | 28.7672 | 0.5307 |
29.2217 | 7.0 | 2184 | 27.2268 | 0.5126 |
29.2217 | 8.0 | 2496 | 23.7819 | 0.4982 |
27.2285 | 9.0 | 2808 | 20.2651 | 0.5271 |
23.6907 | 10.0 | 3120 | 17.8350 | 0.5271 |
23.6907 | 11.0 | 3432 | 16.7909 | 0.4729 |
21.0475 | 12.0 | 3744 | 16.1897 | 0.4729 |
20.1309 | 13.0 | 4056 | 15.7234 | 0.4729 |
20.1309 | 14.0 | 4368 | 15.4084 | 0.4729 |
19.6553 | 15.0 | 4680 | 15.1657 | 0.4729 |
19.6553 | 16.0 | 4992 | 14.9716 | 0.5271 |
19.3496 | 17.0 | 5304 | 14.7880 | 0.5271 |
19.122 | 18.0 | 5616 | 14.6322 | 0.4729 |
19.122 | 19.0 | 5928 | 14.5424 | 0.4729 |
18.9517 | 20.0 | 6240 | 14.4178 | 0.5271 |
18.7994 | 21.0 | 6552 | 14.2725 | 0.4729 |
18.7994 | 22.0 | 6864 | 14.2138 | 0.5271 |
18.6835 | 23.0 | 7176 | 14.1064 | 0.5271 |
18.6835 | 24.0 | 7488 | 14.0401 | 0.4729 |
18.59 | 25.0 | 7800 | 13.9478 | 0.4729 |
18.504 | 26.0 | 8112 | 13.9156 | 0.4729 |
18.504 | 27.0 | 8424 | 13.8335 | 0.4729 |
18.4387 | 28.0 | 8736 | 13.7761 | 0.4729 |
18.3758 | 29.0 | 9048 | 13.7312 | 0.4729 |
18.3758 | 30.0 | 9360 | 13.6791 | 0.4729 |
18.3264 | 31.0 | 9672 | 13.6458 | 0.5271 |
18.3264 | 32.0 | 9984 | 13.5991 | 0.4729 |
18.2808 | 33.0 | 10296 | 13.5762 | 0.5271 |
18.2355 | 34.0 | 10608 | 13.5283 | 0.4729 |
18.2355 | 35.0 | 10920 | 13.4919 | 0.4729 |
18.2071 | 36.0 | 11232 | 13.4721 | 0.4729 |
18.1831 | 37.0 | 11544 | 13.4375 | 0.4729 |
18.1831 | 38.0 | 11856 | 13.4097 | 0.5271 |
18.1448 | 39.0 | 12168 | 13.4004 | 0.5271 |
18.1448 | 40.0 | 12480 | 13.3691 | 0.5271 |
18.1182 | 41.0 | 12792 | 13.3430 | 0.4729 |
18.1006 | 42.0 | 13104 | 13.3514 | 0.4729 |
18.1006 | 43.0 | 13416 | 13.3017 | 0.4729 |
18.0785 | 44.0 | 13728 | 13.2838 | 0.4729 |
18.0562 | 45.0 | 14040 | 13.2687 | 0.4729 |
18.0562 | 46.0 | 14352 | 13.2555 | 0.4729 |
18.0454 | 47.0 | 14664 | 13.2510 | 0.4729 |
18.0454 | 48.0 | 14976 | 13.2384 | 0.5271 |
18.0293 | 49.0 | 15288 | 13.2096 | 0.4729 |
18.0221 | 50.0 | 15600 | 13.2013 | 0.4729 |
18.0221 | 51.0 | 15912 | 13.1936 | 0.4729 |
17.9969 | 52.0 | 16224 | 13.1813 | 0.4729 |
17.9919 | 53.0 | 16536 | 13.1736 | 0.4729 |
17.9919 | 54.0 | 16848 | 13.1681 | 0.5271 |
17.9823 | 55.0 | 17160 | 13.1559 | 0.4729 |
17.9823 | 56.0 | 17472 | 13.1537 | 0.4729 |
17.9804 | 57.0 | 17784 | 13.1490 | 0.4729 |
17.9743 | 58.0 | 18096 | 13.1461 | 0.4729 |
17.9743 | 59.0 | 18408 | 13.1429 | 0.4729 |
17.9703 | 60.0 | 18720 | 13.1424 | 0.4729 |
Framework versions
- Transformers 4.30.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3
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