mt5-small-finetuned-books-summarization

This model is a fine-tuned version of google/mt5-small on the None dataset. It achieves the following results on the evaluation set:

• Loss: 3.4465
• Rouge1: 10.6276
• Rouge2: 3.4285
• Rougel: 10.246
• Rougelsum: 10.2954

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: 2e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
11.2862	1.0	1209	4.1148	6.5572	1.4127	6.3533	6.3795
5.2609	2.0	2418	3.5019	10.6861	3.0623	10.2926	10.2771
4.7793	3.0	3627	3.4465	10.6276	3.4285	10.246	10.2954

Framework versions

• Transformers 5.15.0
• Pytorch 2.11.0+cu128
• Datasets 5.0.1
• Tokenizers 0.22.2