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README.md
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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: '20230823184639'
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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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# 20230823184639
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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: 0.1007
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- Accuracy: 0.7184
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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: 0.001
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- train_batch_size: 8
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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: 60.0
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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 | 312 | 0.2166 | 0.5307 |
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| 0.2471 | 2.0 | 624 | 0.1849 | 0.5199 |
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| 0.2471 | 3.0 | 936 | 0.2081 | 0.4729 |
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| 0.2218 | 4.0 | 1248 | 0.1789 | 0.4910 |
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| 0.221 | 5.0 | 1560 | 0.2006 | 0.4946 |
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| 0.221 | 6.0 | 1872 | 0.1834 | 0.5632 |
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| 0.2009 | 7.0 | 2184 | 0.1840 | 0.5523 |
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| 0.2009 | 8.0 | 2496 | 0.1722 | 0.5415 |
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| 0.1974 | 9.0 | 2808 | 0.1734 | 0.5668 |
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| 0.1963 | 10.0 | 3120 | 0.1574 | 0.6245 |
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| 0.1963 | 11.0 | 3432 | 0.2281 | 0.4982 |
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| 0.1897 | 12.0 | 3744 | 0.1829 | 0.4982 |
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| 0.1851 | 13.0 | 4056 | 0.1629 | 0.5379 |
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| 0.1851 | 14.0 | 4368 | 0.1433 | 0.6498 |
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| 0.1835 | 15.0 | 4680 | 0.1490 | 0.6426 |
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| 0.1835 | 16.0 | 4992 | 0.1646 | 0.5812 |
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| 0.1745 | 17.0 | 5304 | 0.1594 | 0.6390 |
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| 0.1679 | 18.0 | 5616 | 0.1566 | 0.6462 |
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| 0.1679 | 19.0 | 5928 | 0.1295 | 0.6895 |
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| 0.1727 | 20.0 | 6240 | 0.1444 | 0.6354 |
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| 0.1636 | 21.0 | 6552 | 0.1444 | 0.6282 |
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| 0.1636 | 22.0 | 6864 | 0.1249 | 0.6823 |
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| 0.1611 | 23.0 | 7176 | 0.1404 | 0.6606 |
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| 0.1611 | 24.0 | 7488 | 0.1167 | 0.6859 |
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| 0.1533 | 25.0 | 7800 | 0.1138 | 0.6895 |
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| 0.1565 | 26.0 | 8112 | 0.1148 | 0.7148 |
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| 0.1565 | 27.0 | 8424 | 0.1320 | 0.6462 |
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| 0.1477 | 28.0 | 8736 | 0.1445 | 0.6643 |
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| 0.152 | 29.0 | 9048 | 0.1106 | 0.6823 |
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| 0.152 | 30.0 | 9360 | 0.1403 | 0.6823 |
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| 0.1478 | 31.0 | 9672 | 0.1240 | 0.7076 |
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| 0.1478 | 32.0 | 9984 | 0.1246 | 0.6823 |
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| 0.1419 | 33.0 | 10296 | 0.1076 | 0.7184 |
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| 0.1434 | 34.0 | 10608 | 0.1068 | 0.6931 |
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| 0.1434 | 35.0 | 10920 | 0.1166 | 0.6968 |
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| 0.1381 | 36.0 | 11232 | 0.1059 | 0.7004 |
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| 0.1371 | 37.0 | 11544 | 0.1225 | 0.7040 |
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| 0.1371 | 38.0 | 11856 | 0.1140 | 0.7076 |
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| 0.1354 | 39.0 | 12168 | 0.1131 | 0.7256 |
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| 0.1354 | 40.0 | 12480 | 0.1074 | 0.7148 |
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| 0.1341 | 41.0 | 12792 | 0.1068 | 0.7329 |
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| 0.1316 | 42.0 | 13104 | 0.1084 | 0.7004 |
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| 0.1316 | 43.0 | 13416 | 0.1018 | 0.7148 |
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| 0.1318 | 44.0 | 13728 | 0.1160 | 0.7292 |
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| 0.1295 | 45.0 | 14040 | 0.1051 | 0.7148 |
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| 0.1295 | 46.0 | 14352 | 0.1078 | 0.7076 |
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| 0.128 | 47.0 | 14664 | 0.1059 | 0.7004 |
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| 0.128 | 48.0 | 14976 | 0.1035 | 0.7256 |
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| 0.1268 | 49.0 | 15288 | 0.1030 | 0.7004 |
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| 0.1264 | 50.0 | 15600 | 0.1016 | 0.7148 |
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| 0.1264 | 51.0 | 15912 | 0.1022 | 0.7004 |
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| 0.1266 | 52.0 | 16224 | 0.1027 | 0.7040 |
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| 0.1235 | 53.0 | 16536 | 0.1037 | 0.7112 |
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| 0.1235 | 54.0 | 16848 | 0.1083 | 0.7184 |
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| 0.121 | 55.0 | 17160 | 0.1008 | 0.7076 |
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| 0.121 | 56.0 | 17472 | 0.1017 | 0.7184 |
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| 0.1215 | 57.0 | 17784 | 0.1001 | 0.7148 |
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| 0.1239 | 58.0 | 18096 | 0.1004 | 0.7148 |
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| 0.1239 | 59.0 | 18408 | 0.1005 | 0.7184 |
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| 0.1193 | 60.0 | 18720 | 0.1007 | 0.7184 |
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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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