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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-multi_news_wires_hdwriter42k |
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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-multi_news_wires_hdwriter42k |
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This model is a fine-tuned version of [google/pegasus-multi_news](https://huggingface.co/google/pegasus-multi_news) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6427 |
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- Rouge1: 37.3045 |
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- Rouge2: 17.2478 |
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- Rougel: 30.7768 |
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- Rougelsum: 31.3514 |
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- Gen Len: 34.6955 |
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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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| 1.7914 | 1.0 | 16875 | 1.6849 | 36.6608 | 17.005 | 30.4166 | 30.9289 | 35.4077 | |
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| 1.6658 | 2.0 | 33750 | 1.6452 | 37.2837 | 17.3162 | 30.8358 | 31.3382 | 34.7757 | |
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| 1.5478 | 3.0 | 50625 | 1.6427 | 37.3045 | 17.2478 | 30.7768 | 31.3514 | 34.6955 | |
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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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