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distilbart-cnn-12-6-finetuned-1.1.1
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: 0.1031
- Rouge1: 80.2783
- Rouge2: 76.9012
- Rougel: 79.1544
- Rougelsum: 79.3582
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 |
|---|---|---|---|---|---|---|---|
| 0.1389 | 1.0 | 1161 | 0.1130 | 79.3969 | 75.5992 | 78.117 | 78.3237 |
| 0.0881 | 2.0 | 2322 | 0.1031 | 80.2783 | 76.9012 | 79.1544 | 79.3582 |
Framework versions
- Transformers 4.22.2
- Pytorch 1.12.1+cu113
- Datasets 2.5.2
- Tokenizers 0.12.1
