distilbart-cnn-12-6-finetuned-1.3.0
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: 50.4996
- Rouge2: 23.7554
- Rougel: 35.3613
- Rougelsum: 45.8275
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 | 49.5261 | 23.1091 | 34.3266 | 44.7491 |
| 1.5334 | 2.0 | 1964 | 1.7396 | 50.4996 | 23.7554 | 35.3613 | 45.8275 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2
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