20% of the training data

license: apache-2.0 tags: - generated_from_trainer datasets: - xsum metrics: - rouge model-index: - name: t5-small-finetuned-xsum-wei1 results: - task: name: Sequence-to-sequence Language Modeling type: text2text-generation dataset: name: xsum type: xsum args: default metrics: - name: Rouge1 type: rouge value: 27.5875

t5-small-finetuned-xsum-wei1

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

• Loss: 2.5287
• Rouge1: 27.5875
• Rouge2: 7.4083
• Rougel: 21.5654
• Rougelsum: 21.5716
• Gen Len: 18.8205

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: 12
• eval_batch_size: 12
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
2.7677	1.0	3401	2.5441	27.4235	7.2208	21.3535	21.3636	18.8311
2.735	2.0	6802	2.5287	27.5875	7.4083	21.5654	21.5716	18.8205

Framework versions

• Transformers 4.11.3
• Pytorch 1.9.0+cu111
• Datasets 1.14.0
• Tokenizers 0.10.3