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--- |
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license: bsd-3-clause |
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base_model: pszemraj/led-base-book-summary |
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tags: |
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- generated_from_trainer |
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datasets: |
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- pubmed-summarization |
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metrics: |
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- rouge |
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model-index: |
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- name: results |
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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: pubmed-summarization |
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type: pubmed-summarization |
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config: section |
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split: validation |
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args: section |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 42.9685 |
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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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# results |
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This model is a fine-tuned version of [pszemraj/led-base-book-summary](https://huggingface.co/pszemraj/led-base-book-summary) on the pubmed-summarization dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.2031 |
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- Rouge1: 42.9685 |
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- Rouge2: 16.6913 |
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- Rougel: 24.0898 |
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- Rougelsum: 38.3268 |
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- Gen Len: 272.131 |
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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: 8e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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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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- lr_scheduler_warmup_steps: 1000 |
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- num_epochs: 1 |
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- label_smoothing_factor: 0.1 |
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### Training results |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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