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--- |
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tags: |
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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-large-samsum |
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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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args: samsum |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 48.0968 |
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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-large-samsum |
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This model is a fine-tuned version of [google/pegasus-large](https://huggingface.co/google/pegasus-large) on the samsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4109 |
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- Rouge1: 48.0968 |
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- Rouge2: 24.6663 |
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- Rougel: 40.2569 |
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- Rougelsum: 44.0137 |
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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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- gradient_accumulation_steps: 64 |
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- total_train_batch_size: 64 |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:| |
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| No log | 1.0 | 230 | 1.4646 | 45.0631 | 22.5567 | 38.0518 | 41.2694 | |
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| No log | 2.0 | 460 | 1.4203 | 47.4122 | 24.158 | 39.7414 | 43.3485 | |
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| 1.699 | 3.0 | 690 | 1.4109 | 48.0968 | 24.6663 | 40.2569 | 44.0137 | |
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### Framework versions |
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- Transformers 4.20.1 |
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- Pytorch 1.12.0+cu113 |
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- Datasets 2.3.2 |
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- Tokenizers 0.12.1 |
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