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update model card README.md
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README.md
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---
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tags:
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- generated_from_trainer
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datasets:
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- pub_med_summarization_dataset
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metrics:
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- rouge
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model-index:
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- name: pegasus-cnn_dailymail-finetuned-pubmed
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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: pub_med_summarization_dataset
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type: pub_med_summarization_dataset
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args: document
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metrics:
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- name: Rouge1
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type: rouge
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value: 37.2569
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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-cnn_dailymail-finetuned-pubmed
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This model is a fine-tuned version of [google/pegasus-cnn_dailymail](https://huggingface.co/google/pegasus-cnn_dailymail) on the pub_med_summarization_dataset dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.8050
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- Rouge1: 37.2569
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- Rouge2: 15.8205
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- Rougel: 24.1969
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- Rougelsum: 34.0331
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- Gen Len: 125.892
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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: 2
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- eval_batch_size: 2
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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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- num_epochs: 5
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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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| 2.2449 | 1.0 | 1000 | 1.8942 | 36.4494 | 14.9948 | 23.8279 | 33.3081 | 124.482 |
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| 2.0803 | 2.0 | 2000 | 1.8440 | 36.998 | 15.4992 | 24.091 | 33.6614 | 125.678 |
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| 2.0166 | 3.0 | 3000 | 1.8176 | 37.4703 | 16.0358 | 24.5735 | 34.1789 | 125.094 |
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| 1.9911 | 4.0 | 4000 | 1.8055 | 37.1338 | 15.7921 | 24.1412 | 33.8293 | 125.874 |
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| 1.9419 | 5.0 | 5000 | 1.8050 | 37.2569 | 15.8205 | 24.1969 | 34.0331 | 125.892 |
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### Framework versions
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- Transformers 4.17.0
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- Pytorch 1.9.1
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- Datasets 1.18.4
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- Tokenizers 0.11.6
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