distilbart-xsum-12-1-finetuned-pubmed

This model is a fine-tuned version of sshleifer/distilbart-xsum-12-1 on the pub_med_summarization_dataset dataset. It achieves the following results on the evaluation set:

• Loss: 2.8236
• Rouge1: 27.0012
• Rouge2: 12.728
• Rougel: 19.8685
• Rougelsum: 25.0485
• Gen Len: 59.969

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: 2e-05
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
3.3604	1.0	4000	3.1575	25.0078	11.5381	18.4246	23.1605	54.8935
3.0697	2.0	8000	2.9478	26.4947	12.5411	19.4328	24.6123	57.948
2.8638	3.0	12000	2.8672	26.8856	12.7568	19.8949	24.8745	59.6245
2.7243	4.0	16000	2.8347	26.7347	12.5152	19.6516	24.7756	60.439
2.6072	5.0	20000	2.8236	27.0012	12.728	19.8685	25.0485	59.969

Framework versions

• Transformers 4.17.0
• Pytorch 1.10.0+cu111
• Datasets 1.18.3
• Tokenizers 0.11.6