README.md

metadata

tags:
  - generated_from_trainer
datasets:
  - xsum
language:
  - en
metrics:
  - rouge
model-index:
  - name: t5-small-finetuned-xsum-finetuned-xsum
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: xsum
          type: xsum
          args: default
        metrics:
          - name: Rouge1
            type: rouge
            value: 27.7165

t5-small-finetuned-xsum-finetuned-xsum

This model is a fine-tuned version of st3rl4nce/t5-small-finetuned-xsum on the xsum dataset. It achieves the following results on the evaluation set:

• eval_loss: 2.5146
• eval_rouge1: 27.7165
• eval_rouge2: 7.3585
• eval_rougeL: 21.7684
• eval_rougeLsum: 21.7758
• eval_gen_len: 18.8131
• eval_runtime: 667.5713
• eval_samples_per_second: 16.975
• eval_steps_per_second: 1.062
• epoch: 0.01
• step: 113

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: 1
• mixed_precision_training: Native AMP

Framework versions

• Transformers 4.28.1
• Pytorch 2.0.0+cu118
• Datasets 2.12.0
• Tokenizers 0.13.3