metadata

tags:
  - xsum_v1_last
  - generated_from_trainer
datasets:
  - xsum
metrics:
  - rouge
model-index:
  - name: pegasus-large-finetune-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: 5.0462

pegasus-large-finetune-xsum

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

Loss: 10.0826
Rouge1: 5.0462
Rouge2: 0.6914
Rougel: 3.5071
Rougelsum: 3.9548

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
11.4044	1.0	13	10.7501	5.5154	0.5561	3.8425	4.2435
10.5741	2.0	26	10.2309	5.4282	0.7228	3.5759	4.0538
10.0146	3.0	39	10.0826	5.0462	0.6914	3.5071	3.9548

Framework versions

Transformers 4.18.0
Pytorch 1.13.0
Datasets 2.6.1
Tokenizers 0.11.0