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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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- cnn_dailymail |
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metrics: |
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- rouge |
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model-index: |
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- name: tst-summarization |
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results: |
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- task: |
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name: Summarization |
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type: summarization |
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dataset: |
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name: cnn_dailymail 3.0.0 |
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type: cnn_dailymail |
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config: 3.0.0 |
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split: validation |
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args: 3.0.0 |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 41.607 |
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language: |
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- en |
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library_name: transformers |
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pipeline_tag: summarization |
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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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# tst-summarization |
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the cnn_dailymail 3.0.0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6418 |
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- Rouge1: 41.607 |
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- Rouge2: 19.2272 |
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- Rougel: 29.4514 |
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- Rougelsum: 38.8228 |
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- Gen Len: 73.8731 |
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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: 5e-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: 3.0 |
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### Training results |
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### Framework versions |
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- Transformers 4.29.2 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
