mt5_summarize_japanese-6051-japanese

This model is a fine-tuned version of tsmatz/mt5_summarize_japanese on the xlsum dataset. It achieves the following results on the evaluation set:

• Loss: 1.1045
• Rouge1: 0.3394
• Rouge2: 0.0501
• Rougel: 0.3328
• Rougelsum: 0.3321
• Gen Len: 31.8808

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: 4
• eval_batch_size: 4
• seed: 42
• gradient_accumulation_steps: 16
• total_train_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
1.3889	4.5	500	1.1112	0.3381	0.05	0.3306	0.3302	31.3127
1.3351	8.99	1000	1.1045	0.3394	0.0501	0.3328	0.3321	31.8808

Framework versions

• Transformers 4.36.2
• Pytorch 2.1.2+cu121
• Datasets 2.15.0
• Tokenizers 0.15.0