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--- |
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base_model: google/pegasus-large |
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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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- scientific_papers |
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metrics: |
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- rouge |
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model-index: |
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- name: pegasus-large-finetuned-scientific-articles |
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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: scientific_papers |
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type: scientific_papers |
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config: pubmed |
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split: train |
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args: pubmed |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 32.8743 |
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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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# pegasus-large-finetuned-scientific-articles |
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This model is a fine-tuned version of [google/pegasus-large](https://huggingface.co/google/pegasus-large) on the scientific_papers dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.4553 |
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- Rouge1: 32.8743 |
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- Rouge2: 10.8417 |
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- Rougel: 20.3101 |
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- Rougelsum: 28.3673 |
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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: 5.6e-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: 500 |
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- num_epochs: 3 |
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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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| 3.0377 | 1.0 | 252 | 2.5409 | 30.5637 | 9.5168 | 18.2596 | 26.2196 | |
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| 2.6145 | 2.0 | 504 | 2.4722 | 31.5518 | 9.9698 | 19.9187 | 26.695 | |
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| 2.4322 | 3.0 | 756 | 2.4553 | 32.8743 | 10.8417 | 20.3101 | 28.3673 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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