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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-summarizer_02 |
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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_02 |
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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: 1.2204 |
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- Rouge1: 52.4459 |
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- Rouge2: 35.2568 |
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- Rougel: 41.6213 |
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- Rougelsum: 48.7859 |
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- Gen Len: 98.0627 |
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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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| 1.3231 | 1.0 | 16113 | 1.2305 | 52.1565 | 34.8681 | 41.3189 | 48.4258 | 95.9049 | |
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| 1.3001 | 2.0 | 32226 | 1.2186 | 52.4921 | 35.2661 | 41.6264 | 48.8168 | 98.9241 | |
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| 1.2372 | 3.0 | 48339 | 1.2204 | 52.4459 | 35.2568 | 41.6213 | 48.7859 | 98.0627 | |
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### Framework versions |
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- Transformers 4.12.3 |
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- Pytorch 1.9.0+cu111 |
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- Datasets 1.15.1 |
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- Tokenizers 0.10.3 |
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