Edit model card

distilbart-cnn-12-6-finetuned-1.3.1

This model is a fine-tuned version of sshleifer/distilbart-cnn-12-6 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.7396
  • Rouge1: 50.4939
  • Rouge2: 23.7745
  • Rougel: 35.3779
  • Rougelsum: 45.8578

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: 5e-05
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 2

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum
2.0871 1.0 982 1.8224 49.5128 23.1207 34.3412 44.7552
1.5334 2.0 1964 1.7396 50.4939 23.7745 35.3779 45.8578

Framework versions

  • Transformers 4.25.1
  • Pytorch 1.12.1+cu113
  • Datasets 2.7.1
  • Tokenizers 0.13.2
Downloads last month
3
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.