README.md

metadata

tags:
  - generated_from_trainer
datasets:
  - reddit
metrics:
  - rouge
model-index:
  - name: pegasus-xsum-reddit-clean-4
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: reddit
          type: reddit
          args: default
        metrics:
          - name: Rouge1
            type: rouge
            value: 27.7525

pegasus-xsum-reddit-clean-4

This model is a fine-tuned version of google/pegasus-xsum on the reddit dataset. It achieves the following results on the evaluation set:

• Loss: 2.7697
• Rouge1: 27.7525
• Rouge2: 7.9823
• Rougel: 20.9276
• Rougelsum: 22.6678

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: 5.6e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
3.0594	1.0	1906	2.8489	27.9837	8.0824	20.9135	22.7261
2.861	2.0	3812	2.7793	27.8298	8.048	20.8653	22.6781
2.7358	3.0	5718	2.7697	27.7525	7.9823	20.9276	22.6678

Framework versions

• Transformers 4.20.1
• Pytorch 1.11.0
• Datasets 2.1.0
• Tokenizers 0.12.1