EE21/2-BART-ToSSimplify

02_ToS-BART

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

• Loss: 0.5697
• Rouge1: 0.6086
• Rouge2: 0.4577
• Rougel: 0.5072
• Rougelsum: 0.5071
• Gen Len: 110.7293

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: 3e-05
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• num_epochs: 6
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	360	0.5018	0.5957	0.44	0.4873	0.4876	110.8398
0.049	2.0	720	0.5468	0.5923	0.4364	0.4812	0.4813	111.6133
0.0789	3.0	1080	0.5157	0.6035	0.4439	0.4933	0.4934	110.1768
0.0789	4.0	1440	0.5905	0.5873	0.4279	0.4781	0.4781	110.8343
0.044	5.0	1800	0.5581	0.6046	0.4544	0.5023	0.502	110.8674
0.0231	6.0	2160	0.5697	0.6086	0.4577	0.5072	0.5071	110.7293

Framework versions

• Transformers 4.35.2
• Pytorch 2.1.0+cu121
• Datasets 2.15.0
• Tokenizers 0.15.0