noviciusss/flan-t5-base-samsum

SamSum

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

• Loss: nan
• Rouge1: 49.01
• Rouge2: 25.06
• Rougel: 40.97
• Rougelsum: 45.4
• Bertscore Precision: 73.48
• Bertscore Recall: 71.67
• Bertscore F1: 72.25
• Meteor: 42.51
• Bleu: 18.19

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: 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: 3
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Bertscore Precision	Bertscore Recall	Bertscore F1	Meteor	Bleu
0.0	1.0	1842	nan	49.01	25.06	40.97	45.4	73.48	71.67	72.25	42.51	18.19
0.0	2.0	3684	nan	49.01	25.06	40.97	45.4	73.48	71.67	72.25	42.51	18.19
0.0	3.0	5526	nan	49.01	25.06	40.97	45.4	73.48	71.67	72.25	42.51	18.19

Framework versions

• PEFT 0.17.1
• Transformers 4.57.0
• Pytorch 2.8.0+cu126
• Datasets 4.0.0
• Tokenizers 0.22.1 so this is updates model card with new evaluation scores update it to look good