distilbart-xsum-6-6-finetuned-bbc-news-on-extractive

This model is a fine-tuned version of sshleifer/distilbart-xsum-6-6 on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.5869
• Rouge1: 39.4885
• Rouge2: 31.7487
• Rougel: 31.9013
• Rougelsum: 34.0825

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: 4
• eval_batch_size: 4
• 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
1.4649	1.0	445	1.5047	39.1053	31.6651	32.3242	33.9332
1.2224	2.0	890	1.4986	39.4115	31.7894	32.1057	34.0454
1.0099	3.0	1335	1.5322	39.5936	31.9984	32.2283	34.1798
0.8687	4.0	1780	1.5869	39.4885	31.7487	31.9013	34.0825

Framework versions

• Transformers 4.21.2
• Pytorch 1.12.1+cu113
• Datasets 2.4.0
• Tokenizers 0.12.1