distilbart-cnn-12-6-summarization_final_labeled_data

This model is a fine-tuned version of sshleifer/distilbart-cnn-12-6 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0858
• Rouge1: 76.5974
• Rouge2: 66.1659
• Rougel: 71.9284
• Rougelsum: 75.2459
• Gen Len: 122.5

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: 2
• eval_batch_size: 2
• seed: 42
• 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
No log	1.0	99	0.2852	61.0841	45.81	52.9835	59.0452	116.92
No log	2.0	198	0.1547	71.534	59.9905	66.4697	70.5213	117.56
No log	3.0	297	0.1100	71.6464	59.0112	67.3835	70.5206	117.24
No log	4.0	396	0.0960	77.9213	67.6116	73.7888	76.8473	123.62
No log	5.0	495	0.0858	76.5974	66.1659	71.9284	75.2459	122.5

Framework versions

• Transformers 4.20.1
• Pytorch 1.11.0
• Datasets 2.1.0
• Tokenizers 0.12.1