t5-small-finetuned-aspectExtract

This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:

• Loss: 1.3266
• Rouge1: 66.8064
• Rouge2: 41.6459
• Rougel: 66.027
• Rougelsum: 66.0431
• Gen Len: 3.7994

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: 64
• eval_batch_size: 64
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
1.823	1.0	1583	1.5166	65.1022	38.5519	64.2732	64.2982	3.7113
1.5931	2.0	3166	1.3623	66.4726	41.1602	65.6868	65.6907	3.7859
1.5285	3.0	4749	1.3266	66.8064	41.6459	66.027	66.0431	3.7994

Framework versions

• Transformers 4.39.0
• Pytorch 2.2.1+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2