t5-small-finetuned-stock-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: 0.4747
• Rouge1: 46.0644
• Rouge2: 39.4287
• Rougel: 44.2891
• Rougelsum: 44.7063

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: 2.5e-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: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
0.7374	1.0	536	0.5167	45.1623	38.2243	43.3029	43.7977
0.6017	2.0	1072	0.4906	45.8833	39.0776	44.0058	44.4512
0.5731	3.0	1608	0.4768	45.8351	39.1234	43.9974	44.4038
0.5594	4.0	2144	0.4747	46.0644	39.4287	44.2891	44.7063

Framework versions

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