Bart Base Facebook

🚀 bart-base-facebook

This is a fine - tuned version of facebook/bart-base on the xsum dataset, designed for text summarization tasks.

🚀 Quick Start

This model is a fine - tuned version of facebook/bart-base on the xsum dataset. It achieves the following results on the evaluation set:

• Loss: 2.1877
• Rouge1: 0.7146
• Rouge2: 0.3305
• Rougel: 0.2988
• Rougelsum: 0.6822

✨ Features

• Fine - tuned: Based on facebook/bart-base and fine - tuned on the xsum dataset.
• Task - specific: Suitable for sequence - to - sequence language modeling tasks, especially text summarization.
• Good Metrics: Achieves relatively high Rouge scores on the evaluation set.

📚 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: 10
• eval_batch_size: 10
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon = 1e - 08
• lr_scheduler_type: linear
• num_epochs: 5

Training results

Framework versions

• Transformers 4.22.2
• Pytorch 1.12.1+cu113
• Datasets 2.5.2
• Tokenizers 0.12.1

📄 License

This model is licensed under the Apache 2.0 license.