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--- |
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base_model: google/pegasus-x-large |
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tags: |
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- summarization |
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- summary |
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- booksum |
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- long-document |
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- long-form |
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datasets: |
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- ubaada/booksum-complete-cleaned |
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language: |
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- en |
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pipeline_tag: summarization |
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metrics: |
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- rouge |
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model-index: |
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- name: ubaada/pegasus-x-large-booksum-16k |
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results: |
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- task: |
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type: summarization |
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name: Summarization |
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dataset: |
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name: ubaada/booksum-complete-cleaned |
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type: BookSum |
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config: ubaada--booksum |
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split: test |
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metrics: |
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- type: rouge |
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value: 30.947853 |
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name: ROUGE-1 |
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verified: false |
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- type: rouge |
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value: 5.568146 |
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name: ROUGE-2 |
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verified: false |
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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-x-large-booksum-16k |
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This model is a fine-tuned version of [google/pegasus-x-large](https://huggingface.co/google/pegasus-x-large) on [ubaada/booksum-complete-cleaned](https://huggingface.co/datasets/ubaada/booksum-complete-cleaned). It was trained on the 'train' split of chapters sub-dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.9677 |
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- Rouge1: 0.3504 |
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- Rouge2: 0.0525 |
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- Rougel: 0.1398 |
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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: 8 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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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: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | |
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|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:| |
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| 1.417 | 0.9996 | 628 | 1.9677 | 0.3504 | 0.0525 | 0.1398 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.2.0 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
