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---
base_model: google/pegasus-cnn_dailymail
tags:
- generated_from_trainer
model-index:
- name: pegasus-samsum-nlp-with-transformers-ch06
results: []
datasets:
- samsum
language:
- en
metrics:
- rouge
pipeline_tag: summarization
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# pegasus-samsum-nlp-with-transformers-ch06
This model is a fine-tuned version of [google/pegasus-cnn_dailymail](https://huggingface.co/google/pegasus-cnn_dailymail) on the [SAMSum](https://huggingface.co/datasets/samsum) dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4839
It achieves the following ROUGE scores on the test set:
- rouge1: 0.555556
- rouge2: 0.230769
- rougeL: 0.518519
- rougeLsum: 0.518519
**Quick human evaluation of summarization quality:** the results are generally good, after visual inspection of the summaries generated on test set conversations. However it seems some entities/attributions are incorrect (saw an example where model confuses peoples' roles in multi-person chat)
## Model description
PEGASUS doc can be found here: [https://huggingface.co/docs/transformers/model_doc/pegasus](https://huggingface.co/docs/transformers/model_doc/pegasus)
## Intended uses & limitations
This model was trained while studying the NLP With Transformers book; it is not intended to be used for any real applications.
## Training and evaluation data
The finetuning data is the SAMSum dataset only.
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.6592 | 0.54 | 500 | 1.4839 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2 |