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--- |
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license: |
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- bsd-3-clause |
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- apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- pszemraj/scientific_lay_summarisation-plos-norm |
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metrics: |
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- rouge |
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model-index: |
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- name: long-t5-tglobal-xl-16384-book-summary-scientific_lay_summarisation-plos-norm-16384-summ-v1 |
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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: pszemraj/scientific_lay_summarisation-plos-norm |
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type: pszemraj/scientific_lay_summarisation-plos-norm |
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split: validation |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 44.3203 |
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inference: False |
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--- |
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# long-t5-tglobal-xl-16384-booksci-summary-plos-10k |
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This model is a fine-tuned version of [pszemraj/long-t5-tglobal-xl-16384-book-summary](https://huggingface.co/pszemraj/long-t5-tglobal-xl-16384-book-summary) on the pszemraj/scientific_lay_summarisation-plos-norm dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.5041 |
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- Rouge1: 44.3203 |
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- Rouge2: 11.0576 |
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- Rougel: 22.7584 |
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- Rougelsum: 40.1462 |
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- Gen Len: 256.66 |
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## Model description |
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Another test of further fine-tuning booksum-based models, this one fine-tuned on the PLOS subset of lay-summaries for about 10k examples input, to make it roughly equivalent to [this checkpoint](https://huggingface.co/pszemraj/long-t5-tglobal-xl-16384-booksci-summary-v1) fine-tuned on the ELIFE subset for two epochs (also around 10k examples). |
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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: 3e-05 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 165 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 8 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.02 |
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- num_epochs: 1.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| |
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| 1.7715 | 0.28 | 350 | 1.5310 | 43.4729 | 10.4616 | 22.1928 | 39.505 | 260.87 | |
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| 1.9307 | 0.56 | 700 | 1.5102 | 44.1634 | 10.9336 | 22.3896 | 40.2939 | 253.58 | |
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| 1.2981 | 0.84 | 1050 | 1.5046 | 44.2728 | 10.8455 | 22.4122 | 40.3019 | 261.29 | |
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