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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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metrics: |
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- rouge |
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model-index: |
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- name: fine-tuned-bart-20-epochs-wang-lab |
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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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# fine-tuned-bart-20-epochs-wang-lab |
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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: 1.1462 |
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- Rouge1: 0.2876 |
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- Rouge2: 0.1104 |
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- Rougel: 0.2587 |
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- Rougelsum: 0.2583 |
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- Gen Len: 15.32 |
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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: 0.0001 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
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| No log | 1.0 | 301 | 0.8236 | 0.2393 | 0.0872 | 0.2103 | 0.2098 | 15.1 | |
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| 2.6644 | 2.0 | 602 | 0.7800 | 0.2486 | 0.0882 | 0.219 | 0.2187 | 14.24 | |
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| 2.6644 | 3.0 | 903 | 0.7623 | 0.3152 | 0.131 | 0.2914 | 0.2901 | 15.83 | |
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| 0.6713 | 4.0 | 1204 | 0.7802 | 0.2909 | 0.104 | 0.2577 | 0.2577 | 14.4 | |
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| 0.4641 | 5.0 | 1505 | 0.8159 | 0.2986 | 0.1058 | 0.2629 | 0.2606 | 14.71 | |
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| 0.4641 | 6.0 | 1806 | 0.8451 | 0.3212 | 0.1374 | 0.2892 | 0.2892 | 15.3 | |
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| 0.2986 | 7.0 | 2107 | 0.8913 | 0.2965 | 0.115 | 0.2724 | 0.2728 | 15.25 | |
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| 0.2986 | 8.0 | 2408 | 0.9194 | 0.2686 | 0.1036 | 0.2395 | 0.2389 | 15.07 | |
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| 0.2025 | 9.0 | 2709 | 0.9674 | 0.283 | 0.1077 | 0.2549 | 0.2535 | 15.38 | |
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| 0.1397 | 10.0 | 3010 | 0.9848 | 0.2805 | 0.1127 | 0.2484 | 0.2475 | 15.99 | |
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| 0.1397 | 11.0 | 3311 | 1.0356 | 0.2943 | 0.1158 | 0.2568 | 0.2586 | 15.32 | |
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| 0.0922 | 12.0 | 3612 | 1.0481 | 0.3291 | 0.1211 | 0.297 | 0.2999 | 15.39 | |
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| 0.0922 | 13.0 | 3913 | 1.0846 | 0.2861 | 0.1074 | 0.2473 | 0.2482 | 15.04 | |
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| 0.0618 | 14.0 | 4214 | 1.0941 | 0.2929 | 0.103 | 0.2511 | 0.2505 | 15.34 | |
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| 0.042 | 15.0 | 4515 | 1.1076 | 0.2639 | 0.1111 | 0.2349 | 0.2328 | 15.11 | |
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| 0.042 | 16.0 | 4816 | 1.1180 | 0.2825 | 0.1125 | 0.2465 | 0.2452 | 15.08 | |
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| 0.03 | 17.0 | 5117 | 1.1310 | 0.2924 | 0.1073 | 0.2527 | 0.2528 | 15.47 | |
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| 0.03 | 18.0 | 5418 | 1.1407 | 0.2823 | 0.1017 | 0.2491 | 0.2471 | 15.1 | |
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| 0.0204 | 19.0 | 5719 | 1.1445 | 0.2952 | 0.1142 | 0.2635 | 0.264 | 15.13 | |
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| 0.0153 | 20.0 | 6020 | 1.1462 | 0.2876 | 0.1104 | 0.2587 | 0.2583 | 15.32 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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