plain-bart-on-presummarized-tod-wcep

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

• Loss: 2.3043
• Rouge1: 34.5939
• Rouge2: 13.9925
• Rougel: 24.4982
• Rougelsum: 27.7893
• Gen Len: 66.2392

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: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
2.4866	1.0	510	2.3191	34.0155	13.6965	24.0706	27.3858	66.8784
2.1347	2.0	1020	2.2952	34.1203	13.7453	24.0993	27.4503	67.0735
1.9605	3.0	1530	2.3043	34.5939	13.9925	24.4982	27.7893	66.2392

Framework versions

• Transformers 4.39.3
• Pytorch 2.1.2
• Datasets 2.18.0
• Tokenizers 0.15.2