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--- |
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license: apache-2.0 |
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datasets: |
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- MEDIQA-Chat-2023-taskA |
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metrics: |
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- rouge |
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model-index: |
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- name: BioBart_Large_Dialouge_Summarization_taskA |
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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: MEDIQA-Chat-2023-taskA |
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type: MEDIQA-Chat-2023-taskA |
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config: MEDIQA-Chat-2023-taskA |
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split: train |
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args: MEDIQA-Chat-2023-taskA |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 28.7953 |
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--- |
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# BioBart_Large_Dialouge_Summarization_taskA |
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This model is a fine-tuned version of [GanjinZero/biobart-large](https://https://huggingface.co/GanjinZero/biobart-large) on the [Task A-Short Dialogue2Note Summarization dataset](https://github.com/abachaa/MEDIQA-Chat-2023) |
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It achieves the following results on the evaluation set: |
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- Loss: 2.7487 |
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- Rouge1: 28.7953 |
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- Rouge2: 13.7224 |
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- Rougel: 27.8491 |
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- Rougelsum: 28.6028 |
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- Gen Len: 19.34 |
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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: 2e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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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 | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| |
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| No log | 1.0 | 1842 | 2.739522 | 29.7742 | 15.4000 | 29.0754 | 29.706200 | 19.5600 | |
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| No log | 2.0 | 3684 | 2.705775 | 28.6469 | 13.7595 | 27.7582 | 28.486700 | 19.3700 | |
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| No log | 3.0 | 5526 | 2.748785 | 28.7953 | 13.7224 | 27.8491 | 28.602800 | 19.3400 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- datasets 2.10.1 |
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- tokenizers 0.13.2 |
