bart-large-cnn-reddit-summary-v2

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: 1.9771
• Rouge1: 0.4603
• Rouge2: 0.1837
• Rougel: 0.2955
• Rougelsum: 0.3192
• Gen Len: 95.826

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
1.904	1.0	1125	1.8620	0.4543	0.1821	0.2935	0.3157	91.077
1.5708	2.0	2251	1.8475	0.4557	0.183	0.2965	0.3187	90.2955
1.3314	3.0	3377	1.8665	0.4617	0.1871	0.2988	0.3213	94.3165
1.1664	4.0	4502	1.9205	0.4609	0.1849	0.2952	0.3184	98.4065
1.0452	5.0	5625	1.9771	0.4603	0.1837	0.2955	0.3192	95.826

Framework versions

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