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bart-finetuned-summarization-pubmed
This model is a fine-tuned version of facebook/bart-large-cnn on the pubmed-summarization dataset. It achieves the following results on the evaluation set:
- Loss: 1.7193
- Rouge1: 43.1219
- Rouge2: 18.7311
- Rougel: 28.1006
- Rougelsum: 38.0914
- Gen Len: 128.6263
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: 10
- eval_batch_size: 10
- seed: 42
- gradient_accumulation_steps: 5
- total_train_batch_size: 50
- 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 | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 1.8564 | 1.0 | 2398 | 1.7437 | 43.2294 | 18.867 | 28.2156 | 38.1868 | 128.4766 |
| 1.75 | 2.0 | 4796 | 1.7193 | 43.1219 | 18.7311 | 28.1006 | 38.0914 | 128.6263 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
