HGV1408/pegasus_samsum

---
tags:
- generated_from_trainer
datasets:
- samsum
model-index:
- name: pegasus-samsum
results: []
---

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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.
It achieves the following results on the evaluation set:
- Loss: 1.4834

## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- 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

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.6997 | 0.54 | 500 | 1.4834 |

### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3

原始信息汇总

pegasus-samsum

模型描述

该模型是基于google/pegasus-cnn_dailymail在samsum数据集上微调的版本。在评估集上取得了以下结果：

• 损失值：1.4834

训练和评估数据

更多信息需要补充。

训练过程

训练超参数

在训练过程中使用了以下超参数：

• 学习率：5e-05
• 训练批次大小：1
• 评估批次大小：1
• 随机种子：42
• 梯度累积步骤：16
• 总训练批次大小：16
• 优化器：Adam，参数为betas=(0.9,0.999)和epsilon=1e-08
• 学习率调度器类型：线性
• 学习率调度器预热步骤：500
• 训练周期数：1

训练结果

训练损失	周期	步骤	验证损失
1.6997	0.54	500	1.4834

框架版本

• Transformers 4.30.2
• Pytorch 2.0.0
• Datasets 2.1.0
• Tokenizers 0.13.3