pegasus-xsum_summarization

This model is a fine-tuned version of google/pegasus-xsum on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.7876
• Rouge1: 25.7148
• Rouge2: 10.9685
• Rougel: 21.6394
• Rougelsum: 22.3122

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: 5.6e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 8

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
1.633	1.0	50	1.8839	24.9703	9.6517	19.9759	21.088
1.3917	2.0	100	1.8565	24.4395	9.1755	19.5702	20.5489
1.2576	3.0	150	1.8361	24.8266	10.2009	20.074	21.382
1.1191	4.0	200	1.8226	25.9635	11.7704	21.7787	22.365
1.1138	5.0	250	1.8239	26.7874	12.2832	22.7792	23.4501
1.0338	6.0	300	1.8094	26.3543	12.0501	22.3172	23.1194
1.0084	7.0	350	1.7923	25.5686	11.0213	21.5288	21.8892
1.0098	8.0	400	1.7876	25.7148	10.9685	21.6394	22.3122

Framework versions

• Transformers 4.20.1
• Pytorch 1.12.0
• Datasets 2.3.2
• Tokenizers 0.12.1