distilbart-cnn-12-6-finetuned-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: 0.5040
- Rouge1: 41.0557
- Rouge2: 20.8627
- Rougel: 31.6375
- Rougelsum: 38.3023
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 0.5843 | 1.0 | 921 | 0.5095 | 40.4545 | 21.2232 | 31.2992 | 37.9698 |
| 0.4562 | 2.0 | 1842 | 0.5010 | 40.9057 | 21.0576 | 31.4701 | 38.2105 |
| 0.3938 | 3.0 | 2763 | 0.5040 | 41.0557 | 20.8627 | 31.6375 | 38.3023 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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Base model
sshleifer/distilbart-cnn-12-6