summary

This model is a fine-tuned version of Langboat/mengzi-t5-base on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.9630
• Rouge-1: 0.4964
• Rouge-2: 0.3280
• Rouge-l: 0.4232

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: 8
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 32
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge-1	Rouge-2	Rouge-l
2.4098	1.0	154	2.1446	0.4972	0.3216	0.4191
1.9617	2.0	308	1.9971	0.4864	0.3178	0.4148
1.9305	3.0	462	1.9630	0.4964	0.3280	0.4232

Framework versions

• Transformers 4.52.4
• Pytorch 2.7.1+cu118
• Datasets 3.6.0
• Tokenizers 0.21.1