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update model card README.md
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README.md
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---
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license: apache-2.0
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base_model: t5-small
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tags:
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- generated_from_trainer
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datasets:
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- eur-lex-sum
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metrics:
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- rouge
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model-index:
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- name: T5_small_eurlexsum
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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: eur-lex-sum
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type: eur-lex-sum
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config: french
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split: test
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args: french
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metrics:
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- name: Rouge1
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type: rouge
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value: 0.2288
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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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# T5_small_eurlexsum
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the eur-lex-sum dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.9360
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- Rouge1: 0.2288
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- Rouge2: 0.1816
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- Rougel: 0.2157
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- Rougelsum: 0.2158
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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: 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: 8
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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 | 71 | 1.4482 | 0.1743 | 0.0982 | 0.1509 | 0.1511 | 19.0 |
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| No log | 2.0 | 142 | 1.1661 | 0.193 | 0.1257 | 0.1731 | 0.1734 | 19.0 |
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| No log | 3.0 | 213 | 1.0651 | 0.2072 | 0.1483 | 0.1892 | 0.1896 | 19.0 |
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| No log | 4.0 | 284 | 1.0053 | 0.2167 | 0.1638 | 0.2017 | 0.2019 | 19.0 |
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| No log | 5.0 | 355 | 0.9706 | 0.222 | 0.1731 | 0.2082 | 0.2079 | 19.0 |
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| No log | 6.0 | 426 | 0.9510 | 0.2253 | 0.1771 | 0.2114 | 0.2114 | 19.0 |
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| No log | 7.0 | 497 | 0.9393 | 0.2263 | 0.1785 | 0.2134 | 0.2133 | 19.0 |
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| 1.4549 | 8.0 | 568 | 0.9360 | 0.2288 | 0.1816 | 0.2157 | 0.2158 | 19.0 |
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### Framework versions
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- Transformers 4.31.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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