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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: '20230825183857' |
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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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# 20230825183857 |
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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: 0.5542 |
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- Accuracy: 0.7545 |
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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: 0.005 |
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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 | 156 | 1.3372 | 0.5307 | |
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| No log | 2.0 | 312 | 0.6864 | 0.5162 | |
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| No log | 3.0 | 468 | 0.6919 | 0.4874 | |
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| 0.9682 | 4.0 | 624 | 0.6674 | 0.5451 | |
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| 0.9682 | 5.0 | 780 | 0.6774 | 0.5415 | |
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| 0.9682 | 6.0 | 936 | 0.5435 | 0.6498 | |
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| 0.8254 | 7.0 | 1092 | 0.7442 | 0.5235 | |
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| 0.8254 | 8.0 | 1248 | 0.4993 | 0.6679 | |
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| 0.8254 | 9.0 | 1404 | 0.5592 | 0.6570 | |
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| 0.741 | 10.0 | 1560 | 0.6748 | 0.6498 | |
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| 0.741 | 11.0 | 1716 | 0.9543 | 0.4729 | |
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| 0.741 | 12.0 | 1872 | 0.5518 | 0.7004 | |
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| 0.6941 | 13.0 | 2028 | 0.4643 | 0.7040 | |
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| 0.6941 | 14.0 | 2184 | 0.5154 | 0.7220 | |
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| 0.6941 | 15.0 | 2340 | 0.5493 | 0.6570 | |
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| 0.6941 | 16.0 | 2496 | 0.5450 | 0.6570 | |
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| 0.6291 | 17.0 | 2652 | 0.5940 | 0.7040 | |
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| 0.6291 | 18.0 | 2808 | 0.4530 | 0.6931 | |
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| 0.6291 | 19.0 | 2964 | 0.5100 | 0.7581 | |
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| 0.5831 | 20.0 | 3120 | 0.4821 | 0.6751 | |
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| 0.5831 | 21.0 | 3276 | 0.7629 | 0.6354 | |
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| 0.5831 | 22.0 | 3432 | 0.4882 | 0.7437 | |
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| 0.5334 | 23.0 | 3588 | 0.4779 | 0.7040 | |
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| 0.5334 | 24.0 | 3744 | 0.5483 | 0.7365 | |
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| 0.5334 | 25.0 | 3900 | 0.4978 | 0.7112 | |
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| 0.465 | 26.0 | 4056 | 0.4617 | 0.7220 | |
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| 0.465 | 27.0 | 4212 | 0.4768 | 0.7545 | |
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| 0.465 | 28.0 | 4368 | 0.5384 | 0.7545 | |
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| 0.4116 | 29.0 | 4524 | 0.4739 | 0.7401 | |
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| 0.4116 | 30.0 | 4680 | 0.7430 | 0.6895 | |
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| 0.4116 | 31.0 | 4836 | 0.7631 | 0.6426 | |
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| 0.4116 | 32.0 | 4992 | 0.4750 | 0.7365 | |
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| 0.3972 | 33.0 | 5148 | 0.5293 | 0.7509 | |
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| 0.3972 | 34.0 | 5304 | 0.5111 | 0.7545 | |
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| 0.3972 | 35.0 | 5460 | 0.4787 | 0.7617 | |
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| 0.3632 | 36.0 | 5616 | 0.5954 | 0.7617 | |
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| 0.3632 | 37.0 | 5772 | 0.6243 | 0.7509 | |
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| 0.3632 | 38.0 | 5928 | 0.6147 | 0.7256 | |
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| 0.334 | 39.0 | 6084 | 0.4867 | 0.7581 | |
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| 0.334 | 40.0 | 6240 | 0.5077 | 0.7545 | |
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| 0.334 | 41.0 | 6396 | 0.6957 | 0.7112 | |
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| 0.2964 | 42.0 | 6552 | 0.5827 | 0.7690 | |
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| 0.2964 | 43.0 | 6708 | 0.4632 | 0.7617 | |
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| 0.2964 | 44.0 | 6864 | 0.5142 | 0.7545 | |
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| 0.291 | 45.0 | 7020 | 0.5525 | 0.7617 | |
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| 0.291 | 46.0 | 7176 | 0.4876 | 0.7581 | |
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| 0.291 | 47.0 | 7332 | 0.5730 | 0.7617 | |
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| 0.291 | 48.0 | 7488 | 0.5040 | 0.7653 | |
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| 0.2478 | 49.0 | 7644 | 0.5468 | 0.7545 | |
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| 0.2478 | 50.0 | 7800 | 0.5621 | 0.7653 | |
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| 0.2478 | 51.0 | 7956 | 0.5678 | 0.7545 | |
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| 0.2549 | 52.0 | 8112 | 0.5960 | 0.7509 | |
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| 0.2549 | 53.0 | 8268 | 0.5923 | 0.7437 | |
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| 0.2549 | 54.0 | 8424 | 0.5902 | 0.7653 | |
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| 0.2303 | 55.0 | 8580 | 0.4664 | 0.7617 | |
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| 0.2303 | 56.0 | 8736 | 0.5903 | 0.7617 | |
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| 0.2303 | 57.0 | 8892 | 0.6671 | 0.7329 | |
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| 0.2122 | 58.0 | 9048 | 0.5309 | 0.7473 | |
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| 0.2122 | 59.0 | 9204 | 0.6262 | 0.7581 | |
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| 0.2122 | 60.0 | 9360 | 0.5361 | 0.7545 | |
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| 0.2039 | 61.0 | 9516 | 0.6225 | 0.7545 | |
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| 0.2039 | 62.0 | 9672 | 0.6425 | 0.7509 | |
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| 0.2039 | 63.0 | 9828 | 0.6376 | 0.7365 | |
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| 0.2039 | 64.0 | 9984 | 0.6124 | 0.7473 | |
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| 0.1952 | 65.0 | 10140 | 0.5522 | 0.7401 | |
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| 0.1952 | 66.0 | 10296 | 0.6943 | 0.7509 | |
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| 0.1952 | 67.0 | 10452 | 0.5358 | 0.7653 | |
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| 0.1855 | 68.0 | 10608 | 0.5289 | 0.7581 | |
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| 0.1855 | 69.0 | 10764 | 0.5713 | 0.7545 | |
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| 0.1855 | 70.0 | 10920 | 0.5293 | 0.7617 | |
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| 0.1792 | 71.0 | 11076 | 0.6354 | 0.7617 | |
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| 0.1792 | 72.0 | 11232 | 0.5219 | 0.7653 | |
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| 0.1792 | 73.0 | 11388 | 0.5897 | 0.7581 | |
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| 0.1683 | 74.0 | 11544 | 0.5471 | 0.7653 | |
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| 0.1683 | 75.0 | 11700 | 0.5273 | 0.7653 | |
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| 0.1683 | 76.0 | 11856 | 0.5517 | 0.7581 | |
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| 0.1711 | 77.0 | 12012 | 0.5440 | 0.7653 | |
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| 0.1711 | 78.0 | 12168 | 0.5506 | 0.7545 | |
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| 0.1711 | 79.0 | 12324 | 0.5671 | 0.7581 | |
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| 0.1711 | 80.0 | 12480 | 0.5542 | 0.7545 | |
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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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