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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-rewriter |
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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-rewriter |
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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: 1.3424 |
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- Rouge1: 46.6856 |
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- Rouge2: 31.6377 |
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- Rougel: 33.2741 |
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- Rougelsum: 44.5003 |
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- Gen Len: 126.58 |
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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: 4 |
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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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| No log | 1.0 | 450 | 1.4020 | 47.0593 | 32.2065 | 33.9168 | 44.901 | 126.32 | |
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| 1.9944 | 2.0 | 900 | 1.3567 | 46.2635 | 30.9959 | 32.933 | 44.1659 | 126.48 | |
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| 1.6511 | 3.0 | 1350 | 1.3449 | 46.1544 | 30.7257 | 32.693 | 43.9977 | 126.4 | |
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| 1.5951 | 4.0 | 1800 | 1.3424 | 46.6856 | 31.6377 | 33.2741 | 44.5003 | 126.58 | |
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### Framework versions |
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- Transformers 4.17.0 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 2.0.0 |
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- Tokenizers 0.11.6 |
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