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sa_BERT_48_stsb
This model is a fine-tuned version of gokuls/bert_base_48 on the GLUE STSB dataset. It achieves the following results on the evaluation set:
- Loss: 1.8552
- Pearson: 0.5082
- Spearmanr: 0.4883
- Combined Score: 0.4983
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: 4e-05
- train_batch_size: 96
- eval_batch_size: 96
- seed: 10
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
Training results
Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr | Combined Score |
---|---|---|---|---|---|---|
2.185 | 1.0 | 60 | 2.8052 | 0.1411 | 0.1236 | 0.1323 |
1.8984 | 2.0 | 120 | 2.3141 | 0.1796 | 0.1681 | 0.1738 |
1.5809 | 3.0 | 180 | 2.2961 | 0.2130 | 0.2067 | 0.2099 |
1.2083 | 4.0 | 240 | 2.6953 | 0.2673 | 0.2669 | 0.2671 |
0.8831 | 5.0 | 300 | 2.7535 | 0.2934 | 0.2785 | 0.2859 |
0.6722 | 6.0 | 360 | 2.5880 | 0.3524 | 0.3452 | 0.3488 |
0.5242 | 7.0 | 420 | 3.2023 | 0.3644 | 0.3526 | 0.3585 |
0.4244 | 8.0 | 480 | 2.2353 | 0.4509 | 0.4368 | 0.4438 |
0.3482 | 9.0 | 540 | 2.1408 | 0.4592 | 0.4435 | 0.4514 |
0.2885 | 10.0 | 600 | 2.1727 | 0.4457 | 0.4343 | 0.4400 |
0.2641 | 11.0 | 660 | 2.2167 | 0.4599 | 0.4462 | 0.4531 |
0.2319 | 12.0 | 720 | 2.2479 | 0.4522 | 0.4296 | 0.4409 |
0.1991 | 13.0 | 780 | 2.0491 | 0.4659 | 0.4495 | 0.4577 |
0.1791 | 14.0 | 840 | 2.0965 | 0.4770 | 0.4556 | 0.4663 |
0.1692 | 15.0 | 900 | 2.2466 | 0.4860 | 0.4721 | 0.4790 |
0.1406 | 16.0 | 960 | 2.0543 | 0.4980 | 0.4790 | 0.4885 |
0.146 | 17.0 | 1020 | 1.9725 | 0.4874 | 0.4697 | 0.4785 |
0.1205 | 18.0 | 1080 | 2.1711 | 0.4560 | 0.4347 | 0.4454 |
0.123 | 19.0 | 1140 | 2.1570 | 0.4622 | 0.4394 | 0.4508 |
0.1075 | 20.0 | 1200 | 2.0031 | 0.4652 | 0.4452 | 0.4552 |
0.107 | 21.0 | 1260 | 2.1680 | 0.4588 | 0.4302 | 0.4445 |
0.0903 | 22.0 | 1320 | 1.8876 | 0.4938 | 0.4705 | 0.4821 |
0.0866 | 23.0 | 1380 | 1.8552 | 0.5082 | 0.4883 | 0.4983 |
0.085 | 24.0 | 1440 | 2.1126 | 0.4735 | 0.4489 | 0.4612 |
0.0786 | 25.0 | 1500 | 1.9673 | 0.4998 | 0.4772 | 0.4885 |
0.0713 | 26.0 | 1560 | 1.9474 | 0.4897 | 0.4680 | 0.4788 |
0.0715 | 27.0 | 1620 | 1.9366 | 0.5000 | 0.4795 | 0.4897 |
0.0612 | 28.0 | 1680 | 2.0001 | 0.4809 | 0.4538 | 0.4673 |
Framework versions
- Transformers 4.30.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.13.0
- Tokenizers 0.13.3