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3_loa

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- library_name: peft
 
 
 
 
 
 
 
 
 
 
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ## Training procedure
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- ### Framework versions
 
 
 
 
 
 
 
 
 
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- - PEFT 0.4.0
 
 
 
 
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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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+
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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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+
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+ # 3_loa
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+
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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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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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  ## Training procedure
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+ ### Training hyperparameters
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+
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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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+
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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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+
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+
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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