distilbart-cnn-12-6-finetuned-1.2.1
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: 1.9404
- Rouge1: 30.4308
- Rouge2: 13.2594
- Rougel: 25.8203
- Rougelsum: 25.9617
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: 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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 2.5124 | 1.0 | 1171 | 2.0753 | 29.493 | 12.3563 | 24.8091 | 24.9317 |
| 1.7628 | 2.0 | 2342 | 1.9404 | 30.4308 | 13.2594 | 25.8203 | 25.9617 |
Framework versions
- Transformers 4.22.2
- Pytorch 1.12.1+cu113
- Datasets 2.5.2
- Tokenizers 0.12.1