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--- |
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tags: |
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- generated_from_trainer |
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metrics: |
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- rouge |
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model-index: |
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- name: pegasus-newsroom-summarizer_30216 |
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results: [] |
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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-newsroom-summarizer_30216 |
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This model is a fine-tuned version of [google/pegasus-newsroom](https://huggingface.co/google/pegasus-newsroom) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9637 |
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- Rouge1: 52.0929 |
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- Rouge2: 34.6709 |
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- Rougel: 41.1615 |
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- Rougelsum: 48.4141 |
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- Gen Len: 102.017 |
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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: 3 |
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- mixed_precision_training: Native AMP |
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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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| 1.0592 | 1.0 | 12086 | 0.9743 | 51.6187 | 34.1687 | 40.5959 | 47.9305 | 104.3352 | |
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| 0.9742 | 2.0 | 24172 | 0.9647 | 52.1837 | 34.7301 | 41.2599 | 48.4955 | 101.2771 | |
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| 0.9371 | 3.0 | 36258 | 0.9637 | 52.0929 | 34.6709 | 41.1615 | 48.4141 | 102.017 | |
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### Framework versions |
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- Transformers 4.23.1 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.6.1 |
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- Tokenizers 0.13.1 |
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