LED-finetuned-PUBMED8K

This model is a fine-tuned version of allenai/led-base-16384 on the scientific_papers dataset. It achieves the following results on the evaluation set:

• Loss: 2.7101
• Rouge2 Precision: 0.096
• Rouge2 Recall: 0.1461
• Rouge2 Fmeasure: 0.1018

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: 2
• eval_batch_size: 2
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 8
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 1
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge2 Precision	Rouge2 Recall	Rouge2 Fmeasure
2.9289	0.8	10	2.7294	0.1016	0.1442	0.0924

Framework versions

• Transformers 4.27.4
• Pytorch 2.0.0+cu118
• Datasets 2.11.0
• Tokenizers 0.13.3