bart-large-asqa-ob

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: 1.5919
• Rougelsum: 19.1048

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
No log	1.0	355	1.6256	18.3700
1.8462	2.0	710	1.5966	18.3464
1.6704	3.0	1065	1.5906	18.6009
1.6704	4.0	1420	1.5841	18.2794
1.6087	5.0	1775	1.5852	18.4272
1.5364	6.0	2130	1.5989	18.9977
1.5364	7.0	2485	1.5902	18.7631
1.4746	8.0	2840	1.5917	18.9565
1.4336	9.0	3195	1.5919	19.1048

Framework versions

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