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distilbart-cnn-12-6-finetuned-1.1.0
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: 0.0274
- Rouge1: 84.662
- Rouge2: 83.5616
- Rougel: 84.4282
- Rougelsum: 84.4667
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 |
|---|---|---|---|---|---|---|---|
| 0.0911 | 1.0 | 97 | 0.0286 | 85.8678 | 84.7683 | 85.7147 | 85.6949 |
| 0.0442 | 2.0 | 194 | 0.0274 | 84.662 | 83.5616 | 84.4282 | 84.4667 |
Framework versions
- Transformers 4.22.2
- Pytorch 1.12.1+cu113
- Datasets 2.5.2
- Tokenizers 0.12.1
