bart-large-cnn-finetuned-paper2

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

• Loss: 2.8687
• Rouge1: 42.0833
• Rouge2: 11.2567
• Rougel: 20.4102
• Rougelsum: 39.6393
• Gen Len: 1.0

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: 5e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• 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
3.103	1.0	2247	3.0353	39.9795	11.4924	19.361	37.9463	1.0
2.88	2.0	4494	2.9419	37.5726	10.4306	18.8578	35.2105	1.0
2.7435	3.0	6741	2.8970	42.6588	12.12	21.4085	40.0235	1.0
2.6335	4.0	8988	2.8748	39.3861	11.49	19.3988	36.5892	1.0
2.5458	5.0	11235	2.8687	42.0833	11.2567	20.4102	39.6393	1.0

Framework versions

• Transformers 4.48.3
• Pytorch 2.6.0+cu124
• Datasets 3.4.0
• Tokenizers 0.21.0