t5-base-finetuned-multi-oe

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

• Loss: 0.3997
• Rouge1: 56.4636
• Rouge2: 47.4489
• Rougel: 55.7059
• Rougelsum: 55.6603
• Gen Len: 10.5588

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: 0.002
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 4
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	354	0.5103	47.6274	37.6787	46.9405	46.9707	11.8874
0.8047	2.0	708	0.3980	52.6268	43.1111	52.1378	52.1641	9.9629
0.2857	3.0	1062	0.3885	55.0986	45.8185	54.3495	54.363	10.754
0.2857	4.0	1416	0.3997	56.4636	47.4489	55.7059	55.6603	10.5588

Framework versions

• Transformers 4.35.0
• Pytorch 2.1.0+cu118
• Datasets 2.14.6
• Tokenizers 0.14.1