conversation-summ

This model is a fine-tuned version of facebook/bart-large-xsum on the samsum dataset. It achieves the following results on the evaluation set:

• Loss: 0.4048
• Rouge1: 51.7796
• Rouge2: 26.1341
• Rougel: 41.4013
• Rougelsum: 41.4563
• Gen Len: 29.656

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: 1
• eval_batch_size: 1
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 2
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
0.5781	1.0	500	0.3637	50.8871	26.6178	41.8757	41.9291	25.16
0.2183	2.0	1000	0.3586	50.7919	25.4277	40.8428	40.8421	27.712
0.1354	3.0	1500	0.4048	51.7796	26.1341	41.4013	41.4563	29.656

Framework versions

• Transformers 4.26.0
• Pytorch 1.13.1+cu116
• Datasets 2.9.0
• Tokenizers 0.13.2