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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: '20230824083011'
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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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# 20230824083011
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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: 0.3090
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- Accuracy: 0.7401
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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: 0.003
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- train_batch_size: 4
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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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| 0.7501 | 1.0 | 623 | 0.9859 | 0.4729 |
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| 0.6252 | 2.0 | 1246 | 0.4891 | 0.4801 |
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| 0.5769 | 3.0 | 1869 | 1.1271 | 0.4729 |
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| 0.5672 | 4.0 | 2492 | 0.4257 | 0.5632 |
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| 0.5439 | 5.0 | 3115 | 0.5883 | 0.5415 |
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| 0.5426 | 6.0 | 3738 | 0.3734 | 0.6245 |
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| 0.61 | 7.0 | 4361 | 0.4410 | 0.5848 |
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| 0.4937 | 8.0 | 4984 | 0.4091 | 0.5632 |
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| 0.4293 | 9.0 | 5607 | 0.3712 | 0.6282 |
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| 0.3897 | 10.0 | 6230 | 0.3441 | 0.6931 |
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| 0.3759 | 11.0 | 6853 | 0.3400 | 0.7004 |
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| 0.379 | 12.0 | 7476 | 0.3802 | 0.6787 |
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| 0.3661 | 13.0 | 8099 | 0.3456 | 0.7184 |
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| 0.374 | 14.0 | 8722 | 0.3545 | 0.6859 |
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| 0.3441 | 15.0 | 9345 | 0.3219 | 0.7112 |
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| 0.3339 | 16.0 | 9968 | 0.3192 | 0.7184 |
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| 0.3324 | 17.0 | 10591 | 0.3290 | 0.7184 |
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| 0.324 | 18.0 | 11214 | 0.3284 | 0.7112 |
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| 0.3641 | 19.0 | 11837 | 0.3100 | 0.7292 |
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| 0.3138 | 20.0 | 12460 | 0.3102 | 0.7365 |
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| 0.3099 | 21.0 | 13083 | 0.3887 | 0.7076 |
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| 0.3095 | 22.0 | 13706 | 0.3443 | 0.7004 |
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| 0.3039 | 23.0 | 14329 | 0.3937 | 0.6895 |
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| 0.287 | 24.0 | 14952 | 0.3071 | 0.7473 |
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| 0.2718 | 25.0 | 15575 | 0.3097 | 0.7184 |
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| 0.2711 | 26.0 | 16198 | 0.2888 | 0.7329 |
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| 0.2738 | 27.0 | 16821 | 0.2920 | 0.7220 |
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| 0.2697 | 28.0 | 17444 | 0.2986 | 0.7329 |
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| 0.2589 | 29.0 | 18067 | 0.3092 | 0.7437 |
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| 0.2536 | 30.0 | 18690 | 0.3141 | 0.7292 |
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| 0.2564 | 31.0 | 19313 | 0.3134 | 0.7401 |
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| 0.2493 | 32.0 | 19936 | 0.2962 | 0.7365 |
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| 0.2428 | 33.0 | 20559 | 0.3358 | 0.7256 |
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| 0.2425 | 34.0 | 21182 | 0.3155 | 0.7148 |
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| 0.2342 | 35.0 | 21805 | 0.3000 | 0.7220 |
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| 0.2394 | 36.0 | 22428 | 0.2955 | 0.7329 |
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| 0.2257 | 37.0 | 23051 | 0.3070 | 0.7509 |
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| 0.2272 | 38.0 | 23674 | 0.2959 | 0.7365 |
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| 0.2197 | 39.0 | 24297 | 0.3100 | 0.7401 |
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| 0.2144 | 40.0 | 24920 | 0.3009 | 0.7365 |
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| 0.2164 | 41.0 | 25543 | 0.2957 | 0.7256 |
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| 0.2129 | 42.0 | 26166 | 0.3133 | 0.7292 |
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| 0.2106 | 43.0 | 26789 | 0.3110 | 0.7329 |
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| 0.2069 | 44.0 | 27412 | 0.3072 | 0.7329 |
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| 0.2051 | 45.0 | 28035 | 0.3300 | 0.7292 |
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| 0.2064 | 46.0 | 28658 | 0.3106 | 0.7256 |
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| 0.2039 | 47.0 | 29281 | 0.3114 | 0.7292 |
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| 0.2106 | 48.0 | 29904 | 0.3180 | 0.7365 |
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| 0.2008 | 49.0 | 30527 | 0.3099 | 0.7329 |
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| 0.1945 | 50.0 | 31150 | 0.3066 | 0.7329 |
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| 0.1958 | 51.0 | 31773 | 0.3124 | 0.7401 |
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| 0.1939 | 52.0 | 32396 | 0.3230 | 0.7401 |
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| 0.1942 | 53.0 | 33019 | 0.3105 | 0.7365 |
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| 0.1887 | 54.0 | 33642 | 0.3014 | 0.7256 |
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| 0.185 | 55.0 | 34265 | 0.3052 | 0.7365 |
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| 0.1868 | 56.0 | 34888 | 0.3155 | 0.7365 |
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| 0.1888 | 57.0 | 35511 | 0.3056 | 0.7256 |
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| 0.1885 | 58.0 | 36134 | 0.3069 | 0.7329 |
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| 0.192 | 59.0 | 36757 | 0.3076 | 0.7329 |
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| 0.1807 | 60.0 | 37380 | 0.3090 | 0.7401 |
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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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