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--- |
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license: apache-2.0 |
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base_model: google/flan-t5-small |
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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: flan-t5-small-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: 8.0297 |
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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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# flan-t5-small-finetuned-scientific-articles |
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This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on the scientific_papers dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.6792 |
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- Rouge1: 8.0297 |
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- Rouge2: 2.5421 |
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- Rougel: 6.6908 |
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- Rougelsum: 7.3431 |
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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: 9 |
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- eval_batch_size: 9 |
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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: 5 |
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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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| 3.0943 | 1.0 | 56 | 2.8262 | 3.9456 | 1.1211 | 3.3527 | 3.6682 | |
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| 3.0216 | 2.0 | 112 | 2.7682 | 6.0659 | 1.6822 | 5.2499 | 5.7102 | |
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| 2.9495 | 3.0 | 168 | 2.7316 | 7.4704 | 2.4232 | 6.2443 | 6.913 | |
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| 2.9057 | 4.0 | 224 | 2.7050 | 7.8789 | 2.6559 | 6.5559 | 7.1858 | |
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| 2.8622 | 5.0 | 280 | 2.6792 | 8.0297 | 2.5421 | 6.6908 | 7.3431 | |
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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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