t5-base-finetuned-insightSumm

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

• Loss: 0.3468
• Rouge1: 89.0966
• Rouge2: 86.6051
• Rougel: 88.8728
• Rougelsum: 88.889

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: 0.0001
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Use 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
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
0.2422	1.0	3168	0.3808	88.8773	86.4338	88.6606	88.6678
0.2168	2.0	6336	0.3629	88.901	86.4648	88.69	88.7004
0.6073	3.0	9504	0.3476	89.0149	86.5261	88.7853	88.8021
0.3439	4.0	12672	0.3468	89.0966	86.6051	88.8728	88.889
0.4147	5.0	15840	0.3453	89.0389	86.5558	88.8189	88.8349

Framework versions

• Transformers 4.49.0
• Pytorch 2.7.0+cu126
• Datasets 3.5.1
• Tokenizers 0.21.1