pegasus-samsum-test

This model is a fine-tuned version of google/pegasus-cnn_dailymail on the samsum dataset. The model is trained in Chapter 6: Summarization in the NLP with Transformers book. You can find the full code in the accompanying Github repository.

It achieves the following results on the evaluation set:

• Loss: 1.4875

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
1.7012	0.54	500	1.4875

Framework versions

• Transformers 4.12.0.dev0
• Pytorch 1.9.1+cu102
• Datasets 1.12.1
• Tokenizers 0.10.3