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distilbart-cnn-12-6-samsum
This model is a fine-tuned version of sshleifer/distilbart-cnn-12-6 on the samsum dataset. It achieves the following results on the evaluation set:
- Loss: 1.4753
- Rouge1: 39.3733
- Rouge2: 19.4821
- Rougel: 29.8944
- Rougelsum: 36.7688
- Gen Len: 59.4750
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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 1.4685 | 1.0 | 14732 | 1.4753 | 39.3733 | 19.4821 | 29.8944 | 36.7688 | 59.4750 |
Framework versions
- Transformers 4.30.2
- Pytorch 1.12.1
- Datasets 2.13.1
- Tokenizers 0.11.0
