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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-headline |
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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-headline |
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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: 1.4421 |
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- Rouge1: 41.616 |
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- Rouge2: 22.922 |
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- Rougel: 35.2189 |
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- Rougelsum: 35.3561 |
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- Gen Len: 33.9532 |
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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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| 1.6637 | 1.0 | 31200 | 1.4877 | 41.0996 | 22.579 | 34.9311 | 35.0611 | 34.3431 | |
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| 1.4395 | 2.0 | 62400 | 1.4388 | 41.6075 | 22.8274 | 35.2051 | 35.3526 | 33.7965 | |
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| 1.3137 | 3.0 | 93600 | 1.4421 | 41.616 | 22.922 | 35.2189 | 35.3561 | 33.9532 | |
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### Framework versions |
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- Transformers 4.12.2 |
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- Pytorch 1.9.0+cu111 |
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- Datasets 1.14.0 |
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- Tokenizers 0.10.3 |
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