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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: '20230903121524' |
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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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# 20230903121524 |
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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: 0.9097 |
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- Accuracy: 0.6442 |
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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: 0.0002 |
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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 | 0.7286 | 0.5 | |
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| 0.7482 | 2.0 | 680 | 0.7273 | 0.5 | |
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| 0.7442 | 3.0 | 1020 | 0.7313 | 0.5 | |
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| 0.7442 | 4.0 | 1360 | 0.7599 | 0.5 | |
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| 0.7355 | 5.0 | 1700 | 0.7222 | 0.6113 | |
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| 0.6979 | 6.0 | 2040 | 0.7373 | 0.6160 | |
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| 0.6979 | 7.0 | 2380 | 0.6950 | 0.6583 | |
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| 0.6629 | 8.0 | 2720 | 0.6711 | 0.6740 | |
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| 0.6282 | 9.0 | 3060 | 0.7543 | 0.6599 | |
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| 0.6282 | 10.0 | 3400 | 0.7217 | 0.6520 | |
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| 0.6023 | 11.0 | 3740 | 0.7513 | 0.6426 | |
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| 0.5705 | 12.0 | 4080 | 0.6886 | 0.6693 | |
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| 0.5705 | 13.0 | 4420 | 0.6779 | 0.6755 | |
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| 0.5607 | 14.0 | 4760 | 0.7978 | 0.6489 | |
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| 0.527 | 15.0 | 5100 | 0.6722 | 0.6771 | |
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| 0.527 | 16.0 | 5440 | 0.8047 | 0.6317 | |
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| 0.5226 | 17.0 | 5780 | 0.7721 | 0.6740 | |
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| 0.5133 | 18.0 | 6120 | 0.7900 | 0.6552 | |
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| 0.5133 | 19.0 | 6460 | 0.7563 | 0.6599 | |
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| 0.5054 | 20.0 | 6800 | 0.8456 | 0.6411 | |
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| 0.4836 | 21.0 | 7140 | 0.8232 | 0.6426 | |
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| 0.4836 | 22.0 | 7480 | 0.7993 | 0.6270 | |
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| 0.4796 | 23.0 | 7820 | 0.8026 | 0.6426 | |
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| 0.4659 | 24.0 | 8160 | 0.8306 | 0.6254 | |
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| 0.4669 | 25.0 | 8500 | 0.8153 | 0.6505 | |
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| 0.4669 | 26.0 | 8840 | 0.8499 | 0.6489 | |
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| 0.4487 | 27.0 | 9180 | 0.8366 | 0.6332 | |
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| 0.4499 | 28.0 | 9520 | 0.7661 | 0.6567 | |
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| 0.4499 | 29.0 | 9860 | 0.7668 | 0.6630 | |
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| 0.4483 | 30.0 | 10200 | 0.8147 | 0.6520 | |
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| 0.4303 | 31.0 | 10540 | 0.8030 | 0.6442 | |
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| 0.4303 | 32.0 | 10880 | 0.8346 | 0.6285 | |
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| 0.4272 | 33.0 | 11220 | 0.7779 | 0.6489 | |
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| 0.43 | 34.0 | 11560 | 0.8193 | 0.6599 | |
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| 0.43 | 35.0 | 11900 | 0.8792 | 0.6411 | |
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| 0.4139 | 36.0 | 12240 | 0.8091 | 0.6332 | |
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| 0.4139 | 37.0 | 12580 | 0.7939 | 0.6458 | |
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| 0.4139 | 38.0 | 12920 | 0.8626 | 0.6505 | |
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| 0.4102 | 39.0 | 13260 | 0.8111 | 0.6442 | |
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| 0.4065 | 40.0 | 13600 | 0.8054 | 0.6583 | |
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| 0.4065 | 41.0 | 13940 | 0.8704 | 0.6520 | |
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| 0.4049 | 42.0 | 14280 | 0.8441 | 0.6348 | |
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| 0.3978 | 43.0 | 14620 | 0.8723 | 0.6411 | |
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| 0.3978 | 44.0 | 14960 | 0.8747 | 0.6552 | |
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| 0.4074 | 45.0 | 15300 | 0.8662 | 0.6505 | |
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| 0.3952 | 46.0 | 15640 | 0.8432 | 0.6442 | |
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| 0.3952 | 47.0 | 15980 | 0.8837 | 0.6552 | |
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| 0.3868 | 48.0 | 16320 | 0.8219 | 0.6583 | |
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| 0.3805 | 49.0 | 16660 | 0.7792 | 0.6536 | |
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| 0.386 | 50.0 | 17000 | 0.8385 | 0.6520 | |
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| 0.386 | 51.0 | 17340 | 0.8554 | 0.6505 | |
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| 0.3869 | 52.0 | 17680 | 0.8655 | 0.6583 | |
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| 0.3772 | 53.0 | 18020 | 0.8613 | 0.6552 | |
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| 0.3772 | 54.0 | 18360 | 0.9268 | 0.6364 | |
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| 0.3744 | 55.0 | 18700 | 0.8710 | 0.6473 | |
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| 0.378 | 56.0 | 19040 | 0.9222 | 0.6395 | |
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| 0.378 | 57.0 | 19380 | 0.8803 | 0.6536 | |
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| 0.3702 | 58.0 | 19720 | 0.9055 | 0.6364 | |
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| 0.3687 | 59.0 | 20060 | 0.8305 | 0.6630 | |
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| 0.3687 | 60.0 | 20400 | 0.9229 | 0.6395 | |
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| 0.3677 | 61.0 | 20740 | 0.9214 | 0.6301 | |
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| 0.3635 | 62.0 | 21080 | 0.9074 | 0.6458 | |
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| 0.3635 | 63.0 | 21420 | 0.8890 | 0.6520 | |
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| 0.3613 | 64.0 | 21760 | 0.8725 | 0.6426 | |
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| 0.3634 | 65.0 | 22100 | 0.8860 | 0.6489 | |
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| 0.3634 | 66.0 | 22440 | 0.8428 | 0.6614 | |
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| 0.3528 | 67.0 | 22780 | 0.8792 | 0.6458 | |
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| 0.3613 | 68.0 | 23120 | 0.8840 | 0.6254 | |
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| 0.3613 | 69.0 | 23460 | 0.8960 | 0.6489 | |
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| 0.3516 | 70.0 | 23800 | 0.8763 | 0.6567 | |
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| 0.348 | 71.0 | 24140 | 0.8935 | 0.6332 | |
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| 0.348 | 72.0 | 24480 | 0.9031 | 0.6442 | |
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| 0.3567 | 73.0 | 24820 | 0.9070 | 0.6458 | |
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| 0.3514 | 74.0 | 25160 | 0.8997 | 0.6426 | |
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| 0.3543 | 75.0 | 25500 | 0.9025 | 0.6458 | |
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| 0.3543 | 76.0 | 25840 | 0.9028 | 0.6379 | |
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| 0.3457 | 77.0 | 26180 | 0.9155 | 0.6364 | |
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| 0.3452 | 78.0 | 26520 | 0.8973 | 0.6426 | |
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| 0.3452 | 79.0 | 26860 | 0.9085 | 0.6458 | |
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| 0.3379 | 80.0 | 27200 | 0.9097 | 0.6442 | |
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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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