t5-small-finetuned-stock-news-3

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

• Loss: 0.5388
• Rouge1: 46.5843
• Rouge2: 39.8053
• Rougel: 45.0579
• Rougelsum: 45.1153

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
0.6486	1.0	2061	0.5804	46.121	39.3055	44.5881	44.6641
0.5558	2.0	4122	0.5550	46.3546	39.6639	44.9562	44.9928
0.518	3.0	6183	0.5472	46.6276	39.8816	45.1918	45.251
0.4974	4.0	8244	0.5384	46.6196	39.7899	45.0584	45.1347
0.4794	5.0	10305	0.5385	46.6275	39.7555	45.0597	45.1392
0.4714	6.0	12366	0.5388	46.5843	39.8053	45.0579	45.1153

Framework versions

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