README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
  - summarization
datasets:
  - xsum
  - autoevaluate/xsum-sample
metrics:
  - rouge
model-index:
  - name: summarization
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: xsum
          type: xsum
          args: default
        metrics:
          - name: Rouge1
            type: rouge
            value: 23.9405

summarization

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

• Loss: 2.6690
• Rouge1: 23.9405
• Rouge2: 5.0879
• Rougel: 18.4981
• Rougelsum: 18.5032
• Gen Len: 18.7376

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
• training_steps: 1000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
2.9249	0.08	1000	2.6690	23.9405	5.0879	18.4981	18.5032	18.7376

Framework versions

• Transformers 4.19.2
• Pytorch 1.11.0+cu113
• Datasets 2.2.2
• Tokenizers 0.12.1