This model is a fine-tuned version of ccdv/lsg-bart-base-16384-mediasum on the pubmed-summarization dataset. It achieves the following results on the evaluation set:

Loss: 2.7293

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: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss
3.4477	0.2	100	3.1109
3.0893	0.4	200	2.8719
2.8441	0.6	300	2.7832
2.9203	0.8	400	2.7402
2.9796	1.0	500	2.7293

Framework versions

Transformers 4.38.2
Pytorch 2.1.0+cu121
Datasets 2.18.0
Tokenizers 0.15.2

ashishbaraiya/bart-fine-tuned-on-summarization

bart-fine-tuned-on-summarization

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

ashishbaraiya/
bart-fine-tuned-on-summarization