T5 Small Finetuned Cnn

🚀 t5-small-finetuned-cnn

This model is a fine - tuned version of t5-small on the cnn_dailymail dataset, aiming to achieve high - quality text summarization.

🚀 Quick Start

This model is a fine-tuned version of t5-small on the cnn_dailymail dataset. It achieves the following results on the evaluation set:

• Loss: 1.8436
• Rouge1: 33.2082
• Rouge2: 16.798
• Rougel: 28.9573
• Rougelsum: 31.1044

✨ Features

• Summarization: Specialized for text summarization tasks.
• Fine - tuned: Based on the pre - trained t5 - small model, fine - tuned on the cnn_dailymail dataset.
• Metrics - driven: Evaluated using ROUGE metrics, achieving good performance.

📦 Installation

No specific installation steps are provided in the original document, so this section is skipped.

💻 Usage Examples

No code examples are provided in the original document, so this section is skipped.

📚 Documentation

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: 5.6e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 8

Training results

Framework versions

• Transformers 4.14.0
• Pytorch 1.5.0
• Datasets 2.3.2
• Tokenizers 0.10.3

🔧 Technical Details

No detailed technical implementation information is provided in the original document, so this section is skipped.

📄 License

This model is licensed under the Apache - 2.0 license.