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--- |
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base_model: google/pegasus-cnn_dailymail |
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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-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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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: 0.4616 |
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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-samsum |
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This model is a fine-tuned version of [google/pegasus-cnn_dailymail](https://huggingface.co/google/pegasus-cnn_dailymail) on the samsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3665 |
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- Rouge1: 0.4616 |
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- Rouge2: 0.2275 |
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- Rougel: 0.3725 |
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- Rougelsum: 0.3738 |
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- Gen Len: 35.6667 |
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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: 5.750420024069848e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 128 |
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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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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 4 |
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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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| 2.2186 | 0.87 | 100 | 1.7567 | 0.3571 | 0.1437 | 0.2779 | 0.2797 | 46.7733 | |
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| 1.7368 | 1.74 | 200 | 1.4933 | 0.4347 | 0.2053 | 0.3459 | 0.3461 | 35.4533 | |
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| 1.6744 | 2.61 | 300 | 1.4059 | 0.4547 | 0.2179 | 0.3629 | 0.3634 | 35.68 | |
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| 1.5978 | 3.47 | 400 | 1.3665 | 0.4616 | 0.2275 | 0.3725 | 0.3738 | 35.6667 | |
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### Framework versions |
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- Transformers 4.33.1 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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