mt5-small_summarization

This model is a fine-tuned version of google/mt5-small on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 3.1774
• Rouge1: 18.2118
• Rouge2: 6.6244
• Rougel: 15.4682
• Rougelsum: 15.3942

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
17.7253	1.0	50	7.6921	6.677	1.1111	6.5586	6.6861
9.8457	2.0	100	4.5604	12.8991	1.9103	11.2559	10.9036
6.2403	3.0	150	3.9071	16.463	4.0695	14.3098	14.4065
5.2032	4.0	200	3.4869	17.6601	4.0878	14.2931	14.2743
4.8331	5.0	250	3.3472	18.5241	5.3312	15.8993	16.0559
4.526	6.0	300	3.2346	19.0264	5.7839	15.8013	16.1208
4.5378	7.0	350	3.1927	18.9843	6.992	16.3787	16.3574
4.3278	8.0	400	3.1774	18.2118	6.6244	15.4682	15.3942

Framework versions

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