t5-small-finetuned-cnn-news

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

• Loss: 2.2247
• Rouge1: 24.3421
• Rouge2: 9.2344
• Rougel: 19.8499
• Rougelsum: 22.4753

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: 0.00056
• train_batch_size: 8
• eval_batch_size: 8
• 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: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
2.082	1.0	718	2.1358	24.2675	9.2838	19.9394	22.4848
1.8509	2.0	1436	2.1768	24.6433	9.849	20.3102	22.6151
1.6881	3.0	2154	2.1883	24.8843	9.45	20.4272	23.0716
1.569	4.0	2872	2.2127	25.0234	9.9727	20.8242	23.2797
1.4801	5.0	3590	2.2247	24.3421	9.2344	19.8499	22.4753

Framework versions

• Transformers 4.48.3
• Pytorch 2.6.0+cu124
• Datasets 3.4.0
• Tokenizers 0.21.0