distilbart-cnn-12-3-finetuned-pubmed

This model is a fine-tuned version of sshleifer/distilbart-cnn-12-3 on the pub_med_summarization_dataset dataset. It achieves the following results on the evaluation set:

• Loss: 2.1743
• Rouge1: 40.5642
• Rouge2: 16.9812
• Rougel: 25.3449
• Rougelsum: 36.46
• Gen Len: 141.95

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
2.469	1.0	4000	2.2956	38.3713	15.2594	23.6734	34.1634	141.707
2.2527	2.0	8000	2.1994	39.5939	16.2376	24.6363	35.5106	141.831
2.0669	3.0	12000	2.1780	40.078	16.6705	25.1119	35.9605	141.8475
1.9275	4.0	16000	2.1669	40.0825	16.6169	24.9702	36.0191	141.928
1.8102	5.0	20000	2.1743	40.5642	16.9812	25.3449	36.46	141.95

Framework versions

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