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summarizer_MediQA
This model is a fine-tuned version of facebook/bart-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.9087
- Rouge1: 0.1757
- Rouge2: 0.0665
- Rougel: 0.1487
- Rougelsum: 0.1548
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: 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: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
---|---|---|---|---|---|---|---|
No log | 1.0 | 56 | 1.9335 | 0.1799 | 0.0713 | 0.1555 | 0.1613 |
No log | 2.0 | 112 | 1.9155 | 0.1727 | 0.0672 | 0.1489 | 0.1535 |
No log | 3.0 | 168 | 1.9087 | 0.1757 | 0.0665 | 0.1487 | 0.1548 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cpu
- Datasets 2.9.0
- Tokenizers 0.13.2