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--- |
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base_model: google/pegasus-x-large |
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tags: |
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- summarization |
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- generated_from_trainer |
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datasets: |
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- samsum |
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metrics: |
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- rouge |
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model-index: |
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- name: pegasus-x-large-finetuned-samsum1000 |
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results: |
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- task: |
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name: Sequence-to-sequence Language Modeling |
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type: text2text-generation |
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dataset: |
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name: samsum |
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type: samsum |
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config: samsum |
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split: validation |
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args: samsum |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 46.6996 |
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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-x-large-finetuned-samsum1000 |
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This model is a fine-tuned version of [google/pegasus-x-large](https://huggingface.co/google/pegasus-x-large) on the samsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4802 |
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- Rouge1: 46.6996 |
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- Rouge2: 21.5586 |
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- Rougel: 38.1002 |
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- Rougelsum: 41.42 |
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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: 5.6e-05 |
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- train_batch_size: 2 |
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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: 10 |
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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 | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:| |
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| 1.7681 | 1.0 | 500 | 1.4689 | 47.1766 | 21.8869 | 38.8854 | 42.9534 | |
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| 1.4626 | 2.0 | 1000 | 1.4781 | 46.6978 | 20.786 | 37.764 | 41.2028 | |
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| 1.3591 | 3.0 | 1500 | 1.4804 | 47.1756 | 21.8821 | 38.2072 | 41.6812 | |
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| 1.3466 | 4.0 | 2000 | 1.4804 | 46.9411 | 21.5169 | 38.18 | 41.471 | |
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| 1.3464 | 5.0 | 2500 | 1.4803 | 46.8083 | 21.5333 | 38.1539 | 41.4872 | |
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| 1.3353 | 6.0 | 3000 | 1.4804 | 46.6675 | 21.1336 | 37.7059 | 41.0869 | |
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| 1.3483 | 7.0 | 3500 | 1.4803 | 46.6768 | 21.1916 | 37.7642 | 41.1696 | |
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| 1.3536 | 8.0 | 4000 | 1.4804 | 46.7311 | 21.5169 | 38.057 | 41.42 | |
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| 1.3533 | 9.0 | 4500 | 1.4802 | 46.6403 | 21.529 | 37.9922 | 41.3437 | |
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| 1.3469 | 10.0 | 5000 | 1.4802 | 46.6996 | 21.5586 | 38.1002 | 41.42 | |
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### Framework versions |
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- Transformers 4.37.1 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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