easyTermsSummerizer

This model is a fine-tuned version of sshleifer/distilbart-cnn-12-6 on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.8124
• Rouge1: 0.7533
• Rouge2: 0.6964
• Rougel: 0.6806
• Rougelsum: 0.6793

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: 5e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
No log	1.0	2	2.2083	0.7332	0.6595	0.6374	0.6376
No log	2.0	4	1.9331	0.7776	0.7268	0.6991	0.7005
No log	3.0	6	1.8124	0.7533	0.6964	0.6806	0.6793

Framework versions

• Transformers 4.27.3
• Pytorch 1.13.0
• Datasets 2.1.0
• Tokenizers 0.13.2