t5-small-finetuned-multinews

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

• Loss: 2.7276
• Rouge1: 14.7073
• Rouge2: 4.8849
• Rougel: 11.336
• Rougelsum: 13.1015
• Gen Len: 18.98

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: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
3.2539	1.0	506	2.8142	14.3316	4.7443	11.1018	12.8337	18.98
3.0164	2.0	1012	2.7613	14.749	4.9494	11.3621	13.1838	18.98
2.9764	3.0	1518	2.7402	14.7452	4.8903	11.367	13.1816	18.98
2.9514	4.0	2024	2.7307	14.7309	4.8615	11.3391	13.1464	18.98
2.9446	5.0	2530	2.7276	14.7073	4.8849	11.336	13.1015	18.98

Framework versions

• Transformers 4.40.1
• Pytorch 1.13.1+cu117
• Datasets 2.19.0
• Tokenizers 0.19.1