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custom_billsum_model

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text2text-generation
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text-generation-inference
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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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+ - billsum
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+ metrics:
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+ - rouge
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+ model-index:
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+ - name: custom_billsum_model
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+ results:
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+ - task:
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+ name: Sequence-to-sequence Language Modeling
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+ type: text2text-generation
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+ dataset:
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+ name: billsum
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+ type: billsum
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+ config: default
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+ split: ca_test
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+ args: default
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+ metrics:
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+ - name: Rouge1
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+ type: rouge
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+ value: 0.1968
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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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+ # custom_billsum_model
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+
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+ This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the billsum dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2.2150
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+ - Rouge1: 0.1968
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+ - Rouge2: 0.0981
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+ - Rougel: 0.1672
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+ - Rougelsum: 0.167
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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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+
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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: 16
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+ - eval_batch_size: 16
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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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+
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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 | 62 | 2.4551 | 0.1626 | 0.0663 | 0.135 | 0.135 | 19.0 |
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+ | No log | 2.0 | 124 | 2.3987 | 0.1882 | 0.0866 | 0.1577 | 0.1577 | 19.0 |
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+ | No log | 3.0 | 186 | 2.3639 | 0.1964 | 0.0937 | 0.1652 | 0.165 | 19.0 |
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+ | No log | 4.0 | 248 | 2.3370 | 0.1943 | 0.0931 | 0.164 | 0.1638 | 19.0 |
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+ | No log | 5.0 | 310 | 2.3135 | 0.1942 | 0.0938 | 0.1646 | 0.1643 | 19.0 |
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+ | No log | 6.0 | 372 | 2.2949 | 0.195 | 0.0938 | 0.1648 | 0.1648 | 19.0 |
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+ | No log | 7.0 | 434 | 2.2809 | 0.1937 | 0.0944 | 0.1643 | 0.1642 | 19.0 |
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+ | No log | 8.0 | 496 | 2.2676 | 0.1949 | 0.0957 | 0.1664 | 0.166 | 19.0 |
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+ | 2.5047 | 9.0 | 558 | 2.2582 | 0.1954 | 0.097 | 0.1665 | 0.1662 | 19.0 |
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+ | 2.5047 | 10.0 | 620 | 2.2510 | 0.1951 | 0.0966 | 0.1661 | 0.166 | 19.0 |
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+ | 2.5047 | 11.0 | 682 | 2.2416 | 0.1962 | 0.0979 | 0.1673 | 0.1671 | 19.0 |
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+ | 2.5047 | 12.0 | 744 | 2.2360 | 0.196 | 0.0975 | 0.1664 | 0.1663 | 19.0 |
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+ | 2.5047 | 13.0 | 806 | 2.2302 | 0.1965 | 0.098 | 0.1667 | 0.1666 | 19.0 |
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+ | 2.5047 | 14.0 | 868 | 2.2262 | 0.1973 | 0.0985 | 0.1673 | 0.1671 | 19.0 |
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+ | 2.5047 | 15.0 | 930 | 2.2224 | 0.197 | 0.0976 | 0.1668 | 0.1667 | 19.0 |
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+ | 2.5047 | 16.0 | 992 | 2.2200 | 0.1973 | 0.0984 | 0.1673 | 0.1671 | 19.0 |
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+ | 2.3391 | 17.0 | 1054 | 2.2183 | 0.1967 | 0.0974 | 0.1669 | 0.1666 | 19.0 |
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+ | 2.3391 | 18.0 | 1116 | 2.2164 | 0.1968 | 0.0974 | 0.1669 | 0.1666 | 19.0 |
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+ | 2.3391 | 19.0 | 1178 | 2.2152 | 0.1969 | 0.0982 | 0.1673 | 0.1671 | 19.0 |
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+ | 2.3391 | 20.0 | 1240 | 2.2150 | 0.1968 | 0.0981 | 0.1672 | 0.167 | 19.0 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.30.2
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+ - Pytorch 2.0.0
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+ - Datasets 2.1.0
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+ - Tokenizers 0.13.3