distilbart-xsum-12-3-finetuned-xsum

This model is a fine-tuned version of sshleifer/distilbart-xsum-12-3 on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 2.5886
• Rouge1: 26.2164
• Rouge2: 8.042
• Rougel: 17.5545
• Rougelsum: 21.4745
• Gen Len: 62.0

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: 2e-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
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
3.295	1.0	1041	3.0302	26.1938	8.0525	17.4251	21.3971	61.7637
2.9061	2.0	2082	2.7844	26.3284	7.8489	17.3299	21.487	61.951
2.7181	3.0	3123	2.6605	25.3295	7.5429	16.8791	21.0243	62.0
2.5903	4.0	4164	2.6097	25.5526	7.6456	17.1916	21.0674	61.9885
2.5327	5.0	5205	2.5886	26.2164	8.042	17.5545	21.4745	62.0

Framework versions

• Transformers 4.38.1
• Pytorch 2.1.2
• Datasets 2.18.0
• Tokenizers 0.15.2