bart-base-finetuned-summarization-cnn-ver1.1

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bart-base-finetuned-summarization-cnn-ver1.1

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

• Loss: 2.3824
• Bertscore-mean-precision: 0.8904
• Bertscore-mean-recall: 0.8610
• Bertscore-mean-f1: 0.8753
• Bertscore-median-precision: 0.8893
• Bertscore-median-recall: 0.8606
• Bertscore-median-f1: 0.8744

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
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Framework versions

• Transformers 4.24.0
• Pytorch 1.12.1+cu113
• Datasets 2.7.1
• Tokenizers 0.13.2