update model card README.md
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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: '20230822124929'
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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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# 20230822124929
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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: 0.3407
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- Accuracy: 0.6570
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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 | 0.3734 | 0.5307 |
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| 0.4216 | 2.0 | 624 | 0.3802 | 0.4729 |
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| 0.4216 | 3.0 | 936 | 0.4299 | 0.4765 |
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| 0.3883 | 4.0 | 1248 | 0.3490 | 0.5451 |
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| 0.3918 | 5.0 | 1560 | 0.3461 | 0.5884 |
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| 0.3918 | 6.0 | 1872 | 0.3599 | 0.5523 |
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| 0.3764 | 7.0 | 2184 | 0.3565 | 0.5451 |
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| 0.3764 | 8.0 | 2496 | 0.3611 | 0.5018 |
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| 0.3794 | 9.0 | 2808 | 0.4040 | 0.5415 |
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| 0.3778 | 10.0 | 3120 | 0.3622 | 0.4729 |
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| 0.3778 | 11.0 | 3432 | 0.4954 | 0.4693 |
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| 0.3813 | 12.0 | 3744 | 0.3602 | 0.4765 |
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| 0.3718 | 13.0 | 4056 | 0.3453 | 0.5415 |
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| 0.3718 | 14.0 | 4368 | 0.3640 | 0.5343 |
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| 0.3701 | 15.0 | 4680 | 0.3589 | 0.4838 |
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| 0.3701 | 16.0 | 4992 | 0.3700 | 0.5632 |
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| 0.371 | 17.0 | 5304 | 0.4147 | 0.5343 |
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| 0.3644 | 18.0 | 5616 | 0.3505 | 0.5740 |
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| 0.3644 | 19.0 | 5928 | 0.3736 | 0.4874 |
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| 0.3667 | 20.0 | 6240 | 0.3637 | 0.5704 |
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| 0.3629 | 21.0 | 6552 | 0.3412 | 0.6209 |
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| 0.3629 | 22.0 | 6864 | 0.3451 | 0.6282 |
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| 0.3574 | 23.0 | 7176 | 0.3626 | 0.6065 |
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| 0.3574 | 24.0 | 7488 | 0.3732 | 0.4874 |
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| 0.3565 | 25.0 | 7800 | 0.3427 | 0.6173 |
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| 0.3525 | 26.0 | 8112 | 0.3855 | 0.5812 |
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| 0.3525 | 27.0 | 8424 | 0.3384 | 0.6498 |
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| 0.3523 | 28.0 | 8736 | 0.3408 | 0.6282 |
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| 0.3505 | 29.0 | 9048 | 0.3548 | 0.6101 |
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| 0.3505 | 30.0 | 9360 | 0.3861 | 0.5921 |
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| 0.3509 | 31.0 | 9672 | 0.3710 | 0.5993 |
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| 0.3509 | 32.0 | 9984 | 0.3897 | 0.5993 |
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| 0.3494 | 33.0 | 10296 | 0.3535 | 0.6354 |
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| 0.3459 | 34.0 | 10608 | 0.3389 | 0.6282 |
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| 0.3459 | 35.0 | 10920 | 0.3397 | 0.6209 |
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| 0.3429 | 36.0 | 11232 | 0.3450 | 0.6101 |
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| 0.3432 | 37.0 | 11544 | 0.3925 | 0.6065 |
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| 0.3432 | 38.0 | 11856 | 0.3294 | 0.6715 |
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| 0.341 | 39.0 | 12168 | 0.3442 | 0.6390 |
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| 0.341 | 40.0 | 12480 | 0.3421 | 0.6462 |
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| 0.3392 | 41.0 | 12792 | 0.3371 | 0.6390 |
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| 0.3392 | 42.0 | 13104 | 0.3326 | 0.6534 |
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| 0.3392 | 43.0 | 13416 | 0.3714 | 0.6282 |
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| 0.337 | 44.0 | 13728 | 0.3535 | 0.6245 |
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| 0.3352 | 45.0 | 14040 | 0.3548 | 0.6245 |
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| 0.3352 | 46.0 | 14352 | 0.3361 | 0.6570 |
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| 0.3335 | 47.0 | 14664 | 0.3329 | 0.6859 |
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| 0.3335 | 48.0 | 14976 | 0.3423 | 0.6462 |
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| 0.3329 | 49.0 | 15288 | 0.3356 | 0.6534 |
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| 0.3308 | 50.0 | 15600 | 0.3398 | 0.6643 |
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| 0.3308 | 51.0 | 15912 | 0.3374 | 0.6679 |
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| 0.3291 | 52.0 | 16224 | 0.3315 | 0.6787 |
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| 0.3284 | 53.0 | 16536 | 0.3650 | 0.6318 |
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| 0.3284 | 54.0 | 16848 | 0.3537 | 0.6282 |
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| 0.3257 | 55.0 | 17160 | 0.3480 | 0.6426 |
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| 0.3257 | 56.0 | 17472 | 0.3424 | 0.6570 |
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| 0.3274 | 57.0 | 17784 | 0.3413 | 0.6679 |
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| 0.3265 | 58.0 | 18096 | 0.3442 | 0.6390 |
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| 0.3265 | 59.0 | 18408 | 0.3417 | 0.6534 |
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| 0.326 | 60.0 | 18720 | 0.3407 | 0.6570 |
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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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