BioBart_on_pubmed

This model is a fine-tuned version of GanjinZero/biobart-v2-base on the None dataset. It achieves the following results on the evaluation set:

• Loss: 3.3101
• Rouge1: 0.0659
• Rouge2: 0.0
• Rougel: 0.044
• Rougelsum: 0.0659
• Gen Len: 20.0

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: 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: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	4	4.4216	0.0659	0.0	0.044	0.0659	20.0
No log	2.0	8	3.4773	0.0659	0.0	0.044	0.0659	20.0
No log	3.0	12	3.3401	0.0659	0.0	0.044	0.0659	20.0
No log	4.0	16	3.3101	0.0659	0.0	0.044	0.0659	20.0

Framework versions

• Transformers 4.31.0
• Pytorch 2.0.1+cu118
• Datasets 2.14.4
• Tokenizers 0.13.3