bert-small2bert-small-finetuned-cnn_daily_mail-summarization-finetuned-multi-news

This model is a fine-tuned version of mrm8488/bert-small2bert-small-finetuned-cnn_daily_mail-summarization on the multi_news dataset. It achieves the following results on the evaluation set:

• Loss: 3.0185
• Rouge1: 38.9616
• Rouge2: 14.1539
• Rougel: 21.1788
• Rougelsum: 35.314

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
3.3679	1.0	11243	3.1314	38.4459	13.7777	20.8772	34.8321
3.1115	2.0	22486	3.0589	38.7419	13.9355	20.9911	35.0988
2.9826	3.0	33729	3.0311	38.7345	14.0365	21.0571	35.1604
2.8986	4.0	44972	3.0185	38.9616	14.1539	21.1788	35.314

Framework versions

• Transformers 4.20.1
• Pytorch 1.12.0+cu113
• Datasets 2.3.2
• Tokenizers 0.12.1