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---
tags:
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: pegasus-xsum-finetuned-samsum-v2
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: samsum
      type: samsum
      config: samsum
      split: train
      args: samsum
    metrics:
    - name: Rouge1
      type: rouge
      value: 48.6788
---

<!-- 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-xsum-finetuned-samsum-v2

This model is a fine-tuned version of [google/pegasus-xsum](https://huggingface.co/google/pegasus-xsum) on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5349
- Rouge1: 48.6788
- Rouge2: 24.4294
- Rougel: 40.7392
- Rougelsum: 44.5412
- Gen Len: 17.4976

## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.7107        | 1.0   | 1841 | 1.5349          | 48.6788 | 24.4294 | 40.7392 | 44.5412   | 17.4976 |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2