bart-large-cnn-reddit-summary

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: 1.8583
• Rouge1: 0.4709
• Rouge2: 0.1924
• Rougel: 0.3079
• Rougelsum: 0.3439
• Gen Len: 97.7071

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: 3
• eval_batch_size: 3
• seed: 42
• gradient_accumulation_steps: 3
• total_train_batch_size: 9
• 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
1.82	1.0	1126	1.7804	0.4605	0.1876	0.3019	0.3362	93.7606
1.5081	2.0	2252	1.7577	0.4656	0.1908	0.304	0.3408	97.3503
1.2919	3.0	3378	1.7755	0.4709	0.1945	0.3096	0.3447	96.6052
1.1352	4.0	4504	1.8307	0.4708	0.1945	0.3088	0.345	97.0
1.0327	5.0	5630	1.8583	0.4709	0.1924	0.3079	0.3439	97.7071

Framework versions

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