ML5-fine-tuning-xsum

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

• Loss: 7.4333
• Rouge1: 0.5714
• Rouge2: 0.0
• Rougel: 0.5714
• Rougelsum: 0.5714

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: 0.001
• 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: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
18.7065	1.0	7	9.6966	0.0	0.0	0.0	0.0
10.3198	2.0	14	7.4333	0.5714	0.0	0.5714	0.5714

Framework versions

• Transformers 4.45.2
• Pytorch 2.3.0+cu121
• Datasets 3.0.1
• Tokenizers 0.20.1