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: 0.1332
• Rouge1: 68.938
• Rouge2: 57.0751
• Rougel: 63.1918
• Rougelsum: 67.2288
• Gen Len: 119.76

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	0.4444	54.7967	41.6412	48.0493	53.3043	118.1
No log	2.0	198	0.2934	60.514	46.8988	53.0023	58.9903	114.62
No log	3.0	297	0.1886	69.1369	57.4931	64.4281	67.5744	121.52
No log	4.0	396	0.1482	67.7496	55.4617	62.6617	66.1207	117.74
No log	5.0	495	0.1332	68.938	57.0751	63.1918	67.2288	119.76

Framework versions

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