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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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- pszemraj/scientific_lay_summarisation-elife-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-scientific_lay_summarisation-elife-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-elife-norm |
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type: pszemraj/scientific_lay_summarisation-elife-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: 47.1446 |
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pipeline_tag: summarization |
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inference: False |
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--- |
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# long-t5-tglobal-xl-sci-simplify-elife |
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This model is a fine-tuned version of [google/long-t5-tglobal-xl](https://huggingface.co/google/long-t5-tglobal-xl) on the pszemraj/scientific_lay_summarisation-elife-norm dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6666 |
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- Rouge1: 47.1446 |
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- Rouge2: 14.2158 |
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- Rougel: 23.3524 |
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- Rougelsum: 44.6063 |
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- Gen Len: 431.22 |
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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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the `pszemraj/scientific_lay_summarisation-elife-norm` dataset, input 16384 tokens then truncate, output 1024 tokens then truncate. |
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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: 1 |
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- eval_batch_size: 1 |
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- seed: 6963 |
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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: 2.0 |
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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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| 1.7959 | 1.0 | 543 | 1.6770 | 44.4187 | 12.6752 | 22.4669 | 41.944 | 456.33 | |
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| 1.7578 | 2.0 | 1086 | 1.6666 | 47.1446 | 14.2158 | 23.3524 | 44.6063 | 431.22 | |
