bart-base-summarization-medical-46

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

• Loss: 2.1274
• Rouge1: 0.4211
• Rouge2: 0.2237
• Rougel: 0.3559
• Rougelsum: 0.356
• Gen Len: 18.296

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: 3e-05
• train_batch_size: 4
• eval_batch_size: 1
• seed: 46
• gradient_accumulation_steps: 4
• total_train_batch_size: 16
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 6
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
2.7041	1.0	1250	2.2079	0.4109	0.2179	0.35	0.3501	18.052
2.6134	2.0	2500	2.1641	0.4151	0.2203	0.3517	0.3518	18.103
2.5664	3.0	3750	2.1450	0.4163	0.22	0.353	0.3529	18.051
2.5501	4.0	5000	2.1328	0.4191	0.2217	0.353	0.3528	18.228
2.535	5.0	6250	2.1268	0.4221	0.2253	0.3569	0.3568	18.235
2.5102	6.0	7500	2.1274	0.4211	0.2237	0.3559	0.356	18.296

Framework versions

• PEFT 0.12.0
• Transformers 4.42.4
• Pytorch 2.3.1+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1