---
library_name: transformers
base_model: google/pegasus-cnn_dailymail
tags:
- generated_from_trainer
model-index:
- name: pegasus-samsum
  results: []
---

<!-- 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

This model is a fine-tuned version of [google/pegasus-cnn_dailymail](https://huggingface.co/google/pegasus-cnn_dailymail) on the SAMsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3986

## Model description

The model uses PEGASUS pretrained on cnn-dailymail and it is fine-tuned on the SAMsum dataset in order to get summaries out of conversations 

## Intended uses & limitations

Summarization on conversations

## Training and evaluation data

The training args are the following:
                                 num_train_epochs=1,
                                 warmup_steps=500,
                                 per_device_train_batch_size=1,
                                 per_gpu_eval_batch_size=1,
                                 weight_decay=0.01,
                                 logging_steps=10, 
                                 push_to_hub=True,
                                 evaluation_strategy='steps', 
                                 eval_steps=500,
                                 save_steps=1e6,
                                 gradient_accumulation_steps=16,
                                 remove_unused_columns=False,

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.5449        | 0.5431 | 500  | 1.3986          |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.20.3