README.md

metadata

library_name: transformers
license: apache-2.0
base_model: t5-small
tags:
  - summarization
  - generated_from_trainer
datasets:
  - xsum
metrics:
  - rouge
model-index:
  - name: t5-small-finetuned-xsum
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: xsum
          type: xsum
          config: default
          split: validation
          args: default
        metrics:
          - name: Rouge1
            type: rouge
            value: 28.3991

t5-small-finetuned-xsum

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

• Loss: 2.4727
• Rouge1: 28.3991
• Rouge2: 7.8164
• Rougel: 22.3432
• Rougelsum: 22.3542
• Gen Len: 18.8247

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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 1
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
2.7009	1.0	12753	2.4727	28.3991	7.8164	22.3432	22.3542	18.8247

Framework versions

• Transformers 4.46.3
• Pytorch 2.5.1+cu121
• Datasets 3.2.0
• Tokenizers 0.20.3