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--- |
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license: apache-2.0 |
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base_model: google/flan-t5-small |
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tags: |
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- generated_from_trainer |
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datasets: |
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- billsum |
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metrics: |
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- rouge |
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model-index: |
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- name: 3_loa |
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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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# 3_loa |
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This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on the billsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.1919 |
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- Rouge1: 0.1973 |
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- Rouge2: 0.1007 |
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- Rougel: 0.1708 |
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- Rougelsum: 0.1711 |
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- Gen Len: 19.0 |
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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: 8 |
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- eval_batch_size: 8 |
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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: 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 | 124 | 2.2622 | 0.1909 | 0.0921 | 0.1656 | 0.1659 | 19.0 | |
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| No log | 2.0 | 248 | 2.2534 | 0.1931 | 0.0956 | 0.1679 | 0.1681 | 19.0 | |
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| No log | 3.0 | 372 | 2.2433 | 0.1952 | 0.0967 | 0.1697 | 0.1699 | 19.0 | |
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| No log | 4.0 | 496 | 2.2358 | 0.1953 | 0.0978 | 0.1701 | 0.1702 | 19.0 | |
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| 2.4755 | 5.0 | 620 | 2.2323 | 0.1951 | 0.0981 | 0.1705 | 0.1706 | 19.0 | |
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| 2.4755 | 6.0 | 744 | 2.2253 | 0.1962 | 0.0996 | 0.1712 | 0.1714 | 19.0 | |
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| 2.4755 | 7.0 | 868 | 2.2199 | 0.1968 | 0.1003 | 0.1719 | 0.172 | 19.0 | |
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| 2.4755 | 8.0 | 992 | 2.2170 | 0.1963 | 0.0999 | 0.1717 | 0.1717 | 19.0 | |
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| 2.4416 | 9.0 | 1116 | 2.2134 | 0.1971 | 0.1002 | 0.1723 | 0.1724 | 19.0 | |
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| 2.4416 | 10.0 | 1240 | 2.2069 | 0.1967 | 0.0995 | 0.1715 | 0.1716 | 19.0 | |
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| 2.4416 | 11.0 | 1364 | 2.2053 | 0.1983 | 0.102 | 0.1729 | 0.1732 | 19.0 | |
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| 2.4416 | 12.0 | 1488 | 2.2034 | 0.1976 | 0.1018 | 0.1722 | 0.1725 | 19.0 | |
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| 2.4153 | 13.0 | 1612 | 2.1995 | 0.1985 | 0.1019 | 0.1725 | 0.1727 | 19.0 | |
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| 2.4153 | 14.0 | 1736 | 2.1980 | 0.198 | 0.1016 | 0.1721 | 0.1722 | 19.0 | |
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| 2.4153 | 15.0 | 1860 | 2.1961 | 0.1983 | 0.1017 | 0.172 | 0.1721 | 19.0 | |
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| 2.4153 | 16.0 | 1984 | 2.1947 | 0.1977 | 0.1013 | 0.1715 | 0.1717 | 19.0 | |
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| 2.4069 | 17.0 | 2108 | 2.1936 | 0.1976 | 0.101 | 0.1714 | 0.1716 | 19.0 | |
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| 2.4069 | 18.0 | 2232 | 2.1925 | 0.1977 | 0.1013 | 0.1713 | 0.1715 | 19.0 | |
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| 2.4069 | 19.0 | 2356 | 2.1918 | 0.1973 | 0.1007 | 0.1709 | 0.1711 | 19.0 | |
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| 2.4069 | 20.0 | 2480 | 2.1919 | 0.1973 | 0.1007 | 0.1708 | 0.1711 | 19.0 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 1.13.1.post200 |
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- Datasets 2.10.0 |
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- Tokenizers 0.13.2 |
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