metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - reddit
metrics:
  - rouge
model-index:
  - name: distilbart-cnn-6-6-reddit
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: reddit
          type: reddit
          config: default
          split: train
          args: default
        metrics:
          - name: Rouge1
            type: rouge
            value: 0.1849

distilbart-cnn-6-6-reddit

This model is a fine-tuned version of sshleifer/distilbart-cnn-6-6 on the reddit dataset. It achieves the following results on the evaluation set:

Loss: 2.9883
Rouge1: 0.1849
Rouge2: 0.0437
Rougel: 0.1273
Rougelsum: 0.1601

More information and training script

You can find more information about how this model was trained, including the actual training script in this github repository.

Training and evaluation data

I made a split in a train and test set. The test size is 1% of the total dataset, which comes down to about 38k samples.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 0.0001
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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
3.13	1.0	238116	3.2736	0.1773	0.0392	0.1223	0.1539
2.8586	2.0	476232	3.0449	0.1846	0.0431	0.127	0.1601
2.7844	3.0	714348	2.9883	0.1849	0.0437	0.1273	0.1601

Framework versions

Transformers 4.25.1
Pytorch 1.13.1+cu116
Datasets 2.8.0
Tokenizers 0.13.2