long-t5-tglobal-base-finetuned-scisumm

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

• Loss: 1.3892
• Rouge1: 0.1745
• Rouge2: 0.1583
• Rougel: 0.1721
• Rougelsum: 0.1726
• Gen Len: 19.0

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: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 16
• total_train_batch_size: 128
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	0.99	28	1.4853	0.1408	0.1085	0.1354	0.1355	19.0
No log	1.97	56	1.4135	0.1637	0.1384	0.1573	0.1578	19.0
No log	3.0	85	1.3955	0.1758	0.1583	0.1733	0.1738	19.0
No log	3.95	112	1.3892	0.1745	0.1583	0.1721	0.1726	19.0

Framework versions

• Transformers 4.38.1
• Pytorch 2.1.0+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2