---
base_model: october-sd/pegasus-xsum-finetuned-en-sum
tags:
- summarization
- generated_from_trainer
model-index:
- name: pegasus-xsum-finetuned-en-sum
  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-xsum-finetuned-en-sum

This model is a fine-tuned version of [october-sd/pegasus-xsum-finetuned-en-sum](https://huggingface.co/october-sd/pegasus-xsum-finetuned-en-sum) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5095

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 507  | 1.4958          |
| No log        | 2.0   | 1014 | 1.5115          |
| No log        | 3.0   | 1522 | 1.5094          |
| No log        | 4.0   | 2028 | 1.5095          |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.2
- Datasets 2.15.0
- Tokenizers 0.15.2