bart-large-cnn-finetuned-scientific-articles
This model is a fine-tuned version of facebook/bart-large-cnn on the scientific_papers dataset. It achieves the following results on the evaluation set:
- Loss: 2.6416
- Rouge1: 34.2136
- Rouge2: 11.6215
- Rougel: 20.2516
- Rougelsum: 30.6019
Model description
More information needed
Intended uses & limitations
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Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5.6e-05
- train_batch_size: 9
- eval_batch_size: 9
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
---|---|---|---|---|---|---|---|
3.3695 | 1.0 | 56 | 2.8464 | 32.133 | 10.3816 | 18.7538 | 29.311 |
2.7639 | 2.0 | 112 | 2.6667 | 31.5794 | 10.8708 | 19.2408 | 28.6171 |
2.517 | 3.0 | 168 | 2.6220 | 33.1806 | 11.2477 | 19.7199 | 30.1012 |
2.2989 | 4.0 | 224 | 2.6031 | 32.7604 | 10.9356 | 19.4766 | 29.6503 |
2.0883 | 5.0 | 280 | 2.6416 | 34.2136 | 11.6215 | 20.2516 | 30.6019 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for GabsAki/bart-large-cnn-finetuned-scientific-articles
Base model
facebook/bart-large-cnn