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--- |
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license: apache-2.0 |
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base_model: facebook/bart-base |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: bart-base-sci |
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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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# bart-base-sci |
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This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.7325 |
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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: 2e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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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: 100 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:------:|:---------------:| |
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| 3.5083 | 1.0 | 1452 | 3.0211 | |
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| 3.1105 | 2.0 | 2904 | 2.8653 | |
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| 2.9224 | 3.0 | 4356 | 2.7973 | |
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| 2.7795 | 4.0 | 5808 | 2.7556 | |
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| 2.7012 | 5.0 | 7260 | 2.7293 | |
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| 2.603 | 6.0 | 8712 | 2.7064 | |
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| 2.5325 | 7.0 | 10164 | 2.6993 | |
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| 2.4599 | 8.0 | 11616 | 2.6817 | |
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| 2.3871 | 9.0 | 13068 | 2.6872 | |
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| 2.3239 | 10.0 | 14520 | 2.6818 | |
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| 2.2717 | 11.0 | 15972 | 2.6759 | |
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| 2.2161 | 12.0 | 17424 | 2.6810 | |
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| 2.1472 | 13.0 | 18876 | 2.6958 | |
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| 2.1074 | 14.0 | 20328 | 2.6932 | |
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| 2.0596 | 15.0 | 21780 | 2.7109 | |
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| 2.0151 | 16.0 | 23232 | 2.7186 | |
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| 1.9662 | 17.0 | 24684 | 2.7245 | |
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| 1.9305 | 18.0 | 26136 | 2.7425 | |
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| 1.8754 | 19.0 | 27588 | 2.7616 | |
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| 1.8375 | 20.0 | 29040 | 2.7709 | |
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| 1.7806 | 21.0 | 30492 | 2.7838 | |
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| 1.7572 | 22.0 | 31944 | 2.7989 | |
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| 1.706 | 23.0 | 33396 | 2.8198 | |
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| 1.6636 | 24.0 | 34848 | 2.8418 | |
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| 1.6349 | 25.0 | 36300 | 2.8498 | |
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| 1.6061 | 26.0 | 37752 | 2.8751 | |
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| 1.5659 | 27.0 | 39204 | 2.8888 | |
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| 1.5266 | 28.0 | 40656 | 2.9037 | |
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| 1.4952 | 29.0 | 42108 | 2.9209 | |
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| 1.4684 | 30.0 | 43560 | 2.9456 | |
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| 1.4353 | 31.0 | 45012 | 2.9749 | |
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| 1.3855 | 32.0 | 46464 | 2.9816 | |
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| 1.3589 | 33.0 | 47916 | 3.0008 | |
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| 1.3192 | 34.0 | 49368 | 3.0116 | |
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| 1.2974 | 35.0 | 50820 | 3.0332 | |
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| 1.2678 | 36.0 | 52272 | 3.0592 | |
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| 1.2423 | 37.0 | 53724 | 3.0762 | |
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| 1.211 | 38.0 | 55176 | 3.0833 | |
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| 1.1914 | 39.0 | 56628 | 3.1130 | |
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| 1.1569 | 40.0 | 58080 | 3.1248 | |
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| 1.1258 | 41.0 | 59532 | 3.1385 | |
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| 1.0997 | 42.0 | 60984 | 3.1589 | |
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| 1.0776 | 43.0 | 62436 | 3.1805 | |
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| 1.0519 | 44.0 | 63888 | 3.1950 | |
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| 1.0278 | 45.0 | 65340 | 3.2122 | |
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| 1.0112 | 46.0 | 66792 | 3.2242 | |
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| 0.9883 | 47.0 | 68244 | 3.2453 | |
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| 0.9707 | 48.0 | 69696 | 3.2584 | |
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| 0.9486 | 49.0 | 71148 | 3.2716 | |
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| 0.9273 | 50.0 | 72600 | 3.2943 | |
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| 0.9074 | 51.0 | 74052 | 3.3075 | |
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| 0.8863 | 52.0 | 75504 | 3.3217 | |
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| 0.8615 | 53.0 | 76956 | 3.3410 | |
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| 0.8452 | 54.0 | 78408 | 3.3509 | |
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| 0.8268 | 55.0 | 79860 | 3.3673 | |
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| 0.8191 | 56.0 | 81312 | 3.3802 | |
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| 0.7964 | 57.0 | 82764 | 3.3924 | |
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| 0.7811 | 58.0 | 84216 | 3.4044 | |
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| 0.7629 | 59.0 | 85668 | 3.4228 | |
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| 0.7489 | 60.0 | 87120 | 3.4360 | |
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| 0.7358 | 61.0 | 88572 | 3.4527 | |
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| 0.7281 | 62.0 | 90024 | 3.4634 | |
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| 0.7043 | 63.0 | 91476 | 3.4811 | |
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| 0.6938 | 64.0 | 92928 | 3.4885 | |
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| 0.6802 | 65.0 | 94380 | 3.5052 | |
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| 0.6673 | 66.0 | 95832 | 3.5136 | |
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| 0.6553 | 67.0 | 97284 | 3.5237 | |
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| 0.6494 | 68.0 | 98736 | 3.5355 | |
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| 0.6388 | 69.0 | 100188 | 3.5463 | |
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| 0.629 | 70.0 | 101640 | 3.5605 | |
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| 0.6132 | 71.0 | 103092 | 3.5717 | |
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| 0.6018 | 72.0 | 104544 | 3.5811 | |
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| 0.5942 | 73.0 | 105996 | 3.5909 | |
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| 0.5834 | 74.0 | 107448 | 3.6005 | |
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| 0.5785 | 75.0 | 108900 | 3.6125 | |
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| 0.5669 | 76.0 | 110352 | 3.6177 | |
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| 0.5611 | 77.0 | 111804 | 3.6319 | |
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| 0.5532 | 78.0 | 113256 | 3.6357 | |
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| 0.5467 | 79.0 | 114708 | 3.6449 | |
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| 0.544 | 80.0 | 116160 | 3.6468 | |
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| 0.5334 | 81.0 | 117612 | 3.6577 | |
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| 0.5313 | 82.0 | 119064 | 3.6643 | |
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| 0.5241 | 83.0 | 120516 | 3.6741 | |
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| 0.5125 | 84.0 | 121968 | 3.6754 | |
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| 0.5118 | 85.0 | 123420 | 3.6858 | |
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| 0.5063 | 86.0 | 124872 | 3.6933 | |
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| 0.4992 | 87.0 | 126324 | 3.6969 | |
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| 0.4956 | 88.0 | 127776 | 3.7041 | |
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| 0.491 | 89.0 | 129228 | 3.7100 | |
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| 0.4862 | 90.0 | 130680 | 3.7109 | |
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| 0.4836 | 91.0 | 132132 | 3.7166 | |
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| 0.4801 | 92.0 | 133584 | 3.7171 | |
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| 0.4774 | 93.0 | 135036 | 3.7246 | |
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| 0.4738 | 94.0 | 136488 | 3.7251 | |
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| 0.4766 | 95.0 | 137940 | 3.7272 | |
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| 0.4694 | 96.0 | 139392 | 3.7312 | |
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| 0.4708 | 97.0 | 140844 | 3.7305 | |
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| 0.4673 | 98.0 | 142296 | 3.7320 | |
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| 0.4615 | 99.0 | 143748 | 3.7323 | |
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| 0.4622 | 100.0 | 145200 | 3.7325 | |
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### Framework versions |
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- Transformers 4.43.4 |
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- Pytorch 1.13.1 |
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- Datasets 2.12.0 |
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- Tokenizers 0.19.1 |
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