t5-small-finetuned-xsum

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

• Loss: 0.2612
• Rouge1: 0.1351
• Rouge2: 0.0901
• Rougel: 0.1351
• Rougelsum: 0.1351
• Gen Len: 20.0

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: 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	Gen Len
0.2617	1.0	833	0.2698	1.4344	0.6532	1.5148	1.4595	20.0
0.2891	2.0	1666	0.2693	0.5721	0.2252	0.5856	0.5495	20.0
0.2887	3.0	2499	0.2621	0.1802	0.0901	0.1952	0.1952	20.0
0.2881	4.0	3332	0.2623	0.1351	0.0901	0.1351	0.1351	20.0
0.2829	5.0	4165	0.2620	0.1351	0.0901	0.1351	0.1351	20.0
0.3004	6.0	4998	0.2612	0.1351	0.0901	0.1351	0.1351	20.0

Framework versions

• Transformers 4.48.3
• Pytorch 2.5.1+cu124
• Datasets 3.3.2
• Tokenizers 0.21.0