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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-xsum-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: 92.4371 |
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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-xsum-finetuned-paws |
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This model is a fine-tuned version of [google/pegasus-xsum](https://huggingface.co/google/pegasus-xsum) on the paws dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.1199 |
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- Rouge1: 92.4371 |
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- Rouge2: 75.4061 |
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- Rougel: 84.1519 |
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- Rougelsum: 84.1958 |
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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: 32 |
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- eval_batch_size: 16 |
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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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| 2.1481 | 1.46 | 1000 | 2.0112 | 93.7727 | 73.3021 | 84.2963 | 84.2506 | |
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| 2.0113 | 2.93 | 2000 | 2.0579 | 93.813 | 73.4119 | 84.3674 | 84.2693 | |
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| 2.054 | 4.39 | 3000 | 2.0890 | 93.3926 | 73.3727 | 84.2814 | 84.1649 | |
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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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