bart-large-asqa-cb

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

• Loss: 2.4791
• Rougelsum: 38.2862

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-06
• 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: 20
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rougelsum
3.347	1.0	545	2.5353	37.3812
2.7829	2.0	1090	2.5087	37.6431
2.6973	3.0	1635	2.4906	37.9194
2.6125	4.0	2180	2.4812	38.1180
2.5697	5.0	2725	2.4762	38.1616
2.5086	6.0	3270	2.4773	38.1370
2.4678	7.0	3815	2.4831	37.9346
2.4404	8.0	4360	2.4896	38.1150
2.3866	9.0	4905	2.4775	38.2222
2.3791	10.0	5450	2.4791	38.2862

Framework versions

• Transformers 4.23.0.dev0
• Pytorch 1.12.1+cu102
• Datasets 2.4.0
• Tokenizers 0.12.1