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distilbart-cnn-12-6-finetuned-arxiv
This model is a fine-tuned version of sshleifer/distilbart-cnn-12-6 on the scientific_papers dataset. It achieves the following results on the evaluation set:
- Loss: 2.5467
- Rouge1: 40.0881
- Rouge2: 14.5466
- Rougel: 23.3775
- Rougelsum: 35.8672
- Gen Len: 122.4665
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: 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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 2.6567 | 1.0 | 12690 | 2.5467 | 40.0881 | 14.5466 | 23.3775 | 35.8672 | 122.4665 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1
