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pegasus-arxiv-finetuned-pubmed
This model is a fine-tuned version of google/pegasus-arxiv on the pub_med_summarization_dataset dataset. It achieves the following results on the evaluation set:
- Loss: 1.8118
- Rouge1: 44.286
- Rouge2: 19.0477
- Rougel: 27.1122
- Rougelsum: 40.2609
- Gen Len: 230.586
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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 2.65 | 1.0 | 1000 | 1.9848 | 40.6984 | 16.387 | 25.0097 | 36.4831 | 215.294 |
| 2.1317 | 2.0 | 2000 | 1.8524 | 43.6431 | 18.6794 | 26.7571 | 39.6642 | 224.646 |
| 2.0591 | 3.0 | 3000 | 1.8254 | 43.6707 | 18.5176 | 26.6015 | 39.6325 | 225.894 |
| 2.0109 | 4.0 | 4000 | 1.8138 | 44.1244 | 18.8866 | 26.8313 | 40.0913 | 229.656 |
| 1.9894 | 5.0 | 5000 | 1.8118 | 44.286 | 19.0477 | 27.1122 | 40.2609 | 230.586 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.9.1
- Datasets 1.18.4
- Tokenizers 0.11.6
