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--- |
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tags: |
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- paraphrasing |
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- generated_from_trainer |
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datasets: |
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- paws |
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metrics: |
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- rouge |
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model-index: |
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- name: pegasus-pubmed-finetuned-paws |
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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: paws |
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type: paws |
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args: labeled_final |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 56.8108 |
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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-pubmed-finetuned-paws |
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This model is a fine-tuned version of [google/pegasus-pubmed](https://huggingface.co/google/pegasus-pubmed) on the paws dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.5012 |
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- Rouge1: 56.8108 |
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- Rouge2: 36.2576 |
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- Rougel: 51.1666 |
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- Rougelsum: 51.2193 |
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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: 0.0001 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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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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- mixed_precision_training: Native AMP |
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- label_smoothing_factor: 0.1 |
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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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| No log | 0.73 | 1000 | 3.8839 | 51.2731 | 29.8072 | 45.767 | 45.5732 | |
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| 4.071 | 1.47 | 2000 | 3.6459 | 52.756 | 31.9185 | 48.0092 | 48.0544 | |
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| 3.5467 | 2.2 | 3000 | 3.5849 | 54.8127 | 33.1959 | 49.326 | 49.4971 | |
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| 3.5467 | 2.93 | 4000 | 3.5267 | 55.387 | 33.9516 | 50.683 | 50.6313 | |
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| 3.3654 | 3.66 | 5000 | 3.5031 | 57.5279 | 35.2664 | 51.9903 | 52.258 | |
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| 3.2844 | 4.4 | 6000 | 3.5296 | 56.0536 | 33.395 | 50.9909 | 51.244 | |
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### Framework versions |
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- Transformers 4.18.0 |
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- Pytorch 1.11.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.12.1 |
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