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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- super_glue |
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metrics: |
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- accuracy |
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model-index: |
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- name: '20230901101200' |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# 20230901101200 |
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This model is a fine-tuned version of [bert-large-cased](https://huggingface.co/bert-large-cased) on the super_glue dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1593 |
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- Accuracy: 0.5 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0007 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 11 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 80.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
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| No log | 1.0 | 340 | 0.1696 | 0.5 | |
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| 0.1874 | 2.0 | 680 | 0.1654 | 0.5 | |
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| 0.1712 | 3.0 | 1020 | 0.1626 | 0.5 | |
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| 0.1712 | 4.0 | 1360 | 0.1604 | 0.5 | |
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| 0.1706 | 5.0 | 1700 | 0.1658 | 0.5 | |
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| 0.1677 | 6.0 | 2040 | 0.1600 | 0.5 | |
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| 0.1677 | 7.0 | 2380 | 0.1608 | 0.5 | |
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| 0.1695 | 8.0 | 2720 | 0.1604 | 0.5 | |
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| 0.1669 | 9.0 | 3060 | 0.1605 | 0.5 | |
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| 0.1669 | 10.0 | 3400 | 0.1694 | 0.5 | |
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| 0.168 | 11.0 | 3740 | 0.1618 | 0.5 | |
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| 0.168 | 12.0 | 4080 | 0.1641 | 0.5 | |
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| 0.168 | 13.0 | 4420 | 0.1601 | 0.5 | |
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| 0.1667 | 14.0 | 4760 | 0.1601 | 0.5 | |
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| 0.1679 | 15.0 | 5100 | 0.1640 | 0.5 | |
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| 0.1679 | 16.0 | 5440 | 0.1638 | 0.5 | |
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| 0.1681 | 17.0 | 5780 | 0.1636 | 0.5 | |
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| 0.1655 | 18.0 | 6120 | 0.1645 | 0.5 | |
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| 0.1655 | 19.0 | 6460 | 0.1627 | 0.5 | |
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| 0.1672 | 20.0 | 6800 | 0.1601 | 0.5 | |
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| 0.1672 | 21.0 | 7140 | 0.1618 | 0.5 | |
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| 0.1672 | 22.0 | 7480 | 0.1668 | 0.5 | |
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| 0.1675 | 23.0 | 7820 | 0.1599 | 0.5 | |
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| 0.1663 | 24.0 | 8160 | 0.1608 | 0.5 | |
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| 0.168 | 25.0 | 8500 | 0.1617 | 0.5 | |
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| 0.168 | 26.0 | 8840 | 0.1601 | 0.5 | |
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| 0.1667 | 27.0 | 9180 | 0.1604 | 0.5 | |
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| 0.1655 | 28.0 | 9520 | 0.1643 | 0.5 | |
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| 0.1655 | 29.0 | 9860 | 0.1605 | 0.5 | |
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| 0.1675 | 30.0 | 10200 | 0.1603 | 0.5 | |
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| 0.1664 | 31.0 | 10540 | 0.1602 | 0.5 | |
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| 0.1664 | 32.0 | 10880 | 0.1631 | 0.5 | |
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| 0.1666 | 33.0 | 11220 | 0.1611 | 0.5 | |
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| 0.167 | 34.0 | 11560 | 0.1616 | 0.5 | |
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| 0.167 | 35.0 | 11900 | 0.1613 | 0.5 | |
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| 0.1667 | 36.0 | 12240 | 0.1600 | 0.5 | |
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| 0.1662 | 37.0 | 12580 | 0.1600 | 0.5 | |
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| 0.1662 | 38.0 | 12920 | 0.1702 | 0.5 | |
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| 0.1652 | 39.0 | 13260 | 0.1599 | 0.5 | |
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| 0.1659 | 40.0 | 13600 | 0.1600 | 0.5 | |
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| 0.1659 | 41.0 | 13940 | 0.1605 | 0.5 | |
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| 0.1661 | 42.0 | 14280 | 0.1601 | 0.5 | |
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| 0.165 | 43.0 | 14620 | 0.1622 | 0.5 | |
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| 0.165 | 44.0 | 14960 | 0.1607 | 0.5 | |
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| 0.1664 | 45.0 | 15300 | 0.1621 | 0.5 | |
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| 0.1654 | 46.0 | 15640 | 0.1600 | 0.5 | |
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| 0.1654 | 47.0 | 15980 | 0.1606 | 0.5 | |
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| 0.1666 | 48.0 | 16320 | 0.1612 | 0.5 | |
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| 0.1652 | 49.0 | 16660 | 0.1600 | 0.5 | |
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| 0.1658 | 50.0 | 17000 | 0.1605 | 0.5 | |
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| 0.1658 | 51.0 | 17340 | 0.1604 | 0.5 | |
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| 0.1647 | 52.0 | 17680 | 0.1606 | 0.5 | |
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| 0.1657 | 53.0 | 18020 | 0.1641 | 0.5 | |
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| 0.1657 | 54.0 | 18360 | 0.1613 | 0.5 | |
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| 0.1644 | 55.0 | 18700 | 0.1605 | 0.5 | |
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| 0.1643 | 56.0 | 19040 | 0.1592 | 0.5 | |
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| 0.1643 | 57.0 | 19380 | 0.1600 | 0.5 | |
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| 0.1632 | 58.0 | 19720 | 0.1633 | 0.5 | |
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| 0.1643 | 59.0 | 20060 | 0.1612 | 0.5 | |
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| 0.1643 | 60.0 | 20400 | 0.1604 | 0.5 | |
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| 0.163 | 61.0 | 20740 | 0.1616 | 0.5 | |
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| 0.1623 | 62.0 | 21080 | 0.1598 | 0.5 | |
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| 0.1623 | 63.0 | 21420 | 0.1597 | 0.5 | |
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| 0.1616 | 64.0 | 21760 | 0.1655 | 0.5 | |
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| 0.1636 | 65.0 | 22100 | 0.1595 | 0.5 | |
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| 0.1636 | 66.0 | 22440 | 0.1599 | 0.5 | |
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| 0.1599 | 67.0 | 22780 | 0.1598 | 0.5 | |
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| 0.163 | 68.0 | 23120 | 0.1602 | 0.5 | |
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| 0.163 | 69.0 | 23460 | 0.1587 | 0.5 | |
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| 0.1613 | 70.0 | 23800 | 0.1604 | 0.5 | |
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| 0.1608 | 71.0 | 24140 | 0.1599 | 0.5 | |
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| 0.1608 | 72.0 | 24480 | 0.1587 | 0.5 | |
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| 0.1604 | 73.0 | 24820 | 0.1610 | 0.5 | |
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| 0.1606 | 74.0 | 25160 | 0.1592 | 0.5 | |
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| 0.1599 | 75.0 | 25500 | 0.1587 | 0.5 | |
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| 0.1599 | 76.0 | 25840 | 0.1593 | 0.5 | |
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| 0.1604 | 77.0 | 26180 | 0.1589 | 0.5 | |
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| 0.16 | 78.0 | 26520 | 0.1602 | 0.5 | |
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| 0.16 | 79.0 | 26860 | 0.1596 | 0.5 | |
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| 0.1599 | 80.0 | 27200 | 0.1593 | 0.5 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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