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--- |
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library_name: transformers |
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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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- summarization |
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- generated_from_trainer |
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datasets: |
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- multi_news |
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metrics: |
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- rouge |
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model-index: |
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- name: t5-small-Abstractive-Summarizer |
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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: multi_news |
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type: multi_news |
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config: default |
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split: validation |
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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: 15.7032 |
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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-Abstractive-Summarizer |
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the multi_news dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.7737 |
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- Rouge1: 15.7032 |
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- Rouge2: 5.2433 |
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- Rougel: 12.282 |
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- Rougelsum: 14.0946 |
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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: 0.00056 |
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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: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:| |
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| 3.118 | 1.0 | 113 | 2.7677 | 15.1343 | 4.7712 | 11.8812 | 13.386 | |
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| 2.7857 | 2.0 | 226 | 2.7609 | 15.7641 | 4.8705 | 12.0955 | 13.9779 | |
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| 2.6158 | 3.0 | 339 | 2.7494 | 15.1515 | 4.4523 | 11.7147 | 13.4181 | |
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| 2.4962 | 4.0 | 452 | 2.7743 | 15.344 | 5.1073 | 12.1574 | 13.7917 | |
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| 2.4304 | 5.0 | 565 | 2.7737 | 15.7032 | 5.2433 | 12.282 | 14.0946 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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