bart-large-cnn-samsum-dc

This model is a fine-tuned version of philschmid/bart-large-cnn-samsum on the None dataset. It achieves the following results on the evaluation set:

• Loss: 1.7404
• Rouge1: 32.5028
• Rouge2: 13.6008
• Rougel: 23.6102
• Rougelsum: 25.0002

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: 5.6e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
1.9176	1.0	2676	1.7297	31.7614	13.0816	22.9243	24.6866
1.4492	2.0	5352	1.5775	32.2161	13.4673	23.7824	25.0772
1.1499	3.0	8028	1.5778	33.1269	14.0686	24.2058	25.39
0.8947	4.0	10704	1.6344	32.9016	13.9786	24.1741	25.5371
0.6905	5.0	13380	1.7404	32.5028	13.6008	23.6102	25.0002

Framework versions

• Transformers 4.38.2
• Pytorch 2.2.1+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2