---
tags:
- generated_from_trainer
datasets:
- aeslc
metrics:
- rouge
model-index:
- name: pegasus-large-finetuned-aeslc-test
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: aeslc
      type: aeslc
      config: default
      split: test
      args: default
    metrics:
    - name: Rouge1
      type: rouge
      value: 32.3073
---

<!-- 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-large-finetuned-aeslc-test

This model is a fine-tuned version of [google/pegasus-large](https://huggingface.co/google/pegasus-large) on the aeslc dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1200
- Rouge1: 32.3073
- Rouge2: 17.5238
- Rougel: 31.3366
- Rougelsum: 31.3175
- Gen Len: 11.6343

## 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: 2
- eval_batch_size: 2
- seed: 42
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 3.3149        | 1.0   | 7218 | 3.1200          | 32.3073 | 17.5238 | 31.3366 | 31.3175   | 11.6343 |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3