---
base_model: google/pegasus-cnn_dailymail
tags:
- generated_from_trainer
datasets:
- samsum
model-index:
- name: pegasus-samsum
  results: []
pipeline_tag: text2text-generation
widget:
- text: "Leon: did you find the job yet? \nArthur: no bro, still unemployed :D \nLeon: hahaha, LIVING LIFE \nArthur: i love it, waking up at noon, watching sports - what else could a man want? \nLeon: a paycheck? ;) \nArthur: don't be mean... \nLeon: but seriously, my mate has an offer as a junior project manager at his company, are you interested? \nArthur: sure thing, do you have any details? \nLeon: <file_photo> \nArthur: that actually looks nice, should I reach out directly to your friend or just apply to this email address from the screenshot? \nLeon: it's his email, you can send your resume directly and I will mention to him who you are :)"

---

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# pegasus-samsum

This model is a fine-tuned version of [google/pegasus-cnn_dailymail](https://huggingface.co/google/pegasus-cnn_dailymail) on the samsum dataset.

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- 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



### Framework versions

- Transformers 4.35.0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.14.1