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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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base_model: google/pegasus-newsroom |
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model-index: |
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- name: pegasus-newsroom-headline_writer_oct22 |
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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-headline_writer_oct22 |
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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: 1.3462 |
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- Rouge1: 41.8799 |
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- Rouge2: 23.1785 |
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- Rougel: 35.5346 |
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- Rougelsum: 35.6203 |
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- Gen Len: 34.3108 |
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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: 1 |
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- eval_batch_size: 1 |
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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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| 1.4364 | 1.0 | 38400 | 1.3730 | 41.9525 | 23.0823 | 35.5435 | 35.6485 | 34.1161 | |
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| 1.2483 | 2.0 | 76800 | 1.3430 | 42.1538 | 23.3302 | 35.8119 | 35.9063 | 33.9333 | |
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| 1.1873 | 3.0 | 115200 | 1.3462 | 41.8799 | 23.1785 | 35.5346 | 35.6203 | 34.3108 | |
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### Framework versions |
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- Transformers 4.22.2 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.5.2 |
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- Tokenizers 0.12.1 |
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