t5-small-finetuned-xsum-custom-2

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

• Loss: 2.3786
• Rouge1: 31.4362
• Rouge2: 9.6838
• Rougel: 25.2999
• Rougelsum: 25.2866

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: 4e-05
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• optimizer: Use OptimizerNames.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: 6

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
2.8203	1.0	5014	2.4866	29.4445	8.3337	23.5606	23.5476
2.6588	2.0	10028	2.4326	30.325	8.9839	24.2942	24.2757
2.5898	3.0	15042	2.4066	30.6845	9.2984	24.7842	24.7798
2.5414	4.0	20056	2.3909	31.2002	9.4684	25.0031	24.996
2.5094	5.0	25070	2.3796	31.3796	9.6549	25.2979	25.2858
2.4899	6.0	30084	2.3786	31.4362	9.6838	25.2999	25.2866

Framework versions

• Transformers 4.51.3
• Pytorch 2.6.0+cu124
• Datasets 3.5.1
• Tokenizers 0.21.1