README.md

metadata

tags:
  - generated_from_trainer
datasets:
  - xsum
metrics:
  - rouge
model-index:
  - name: large-3-3
    results:
      - task:
          name: Summarization
          type: summarization
        dataset:
          name: xsum
          type: xsum
          config: default
          split: validation
          args: default
        metrics:
          - name: Rouge1
            type: rouge
            value: 38.9375

large-3-3

This model is a fine-tuned version of x/large-3-3/ on the xsum dataset. It achieves the following results on the evaluation set:

• Loss: 1.7469
• Rouge1: 38.9375
• Rouge2: 15.8853
• Rougel: 31.2177
• Rougelsum: 31.2093
• Gen Len: 26.5882

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: 0.0001
• train_batch_size: 16
• eval_batch_size: 32
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: constant
• num_epochs: 3.0

Training results

Framework versions

• Transformers 4.27.0.dev0
• Pytorch 1.13.1+cu117
• Datasets 2.10.0
• Tokenizers 0.13.2