t5-small-finetuned-samsum

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

• Loss: 1.7651
• Rouge1: 41.6124
• Rouge2: 18.7668
• Rougel: 35.0271
• Rougelsum: 38.5305
• Gen Len: 16.6381

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
2.044	1.0	921	1.8159	41.1358	18.1022	34.3309	38.1969	16.5232
1.9796	2.0	1842	1.7915	41.4713	18.6313	34.7999	38.4147	16.566
1.9487	3.0	2763	1.7724	41.6106	18.6119	34.7796	38.5737	16.7213
1.9265	4.0	3684	1.7687	41.6027	18.8083	34.8846	38.566	16.676
1.9176	5.0	4605	1.7651	41.6124	18.7668	35.0271	38.5305	16.6381

Framework versions

• Transformers 4.40.0
• Pytorch 2.2.1+cu121
• Datasets 2.19.0
• Tokenizers 0.19.1