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bart-pubmed-hierarchical
pendar02/bart-pubmed-hierarchical
bart-pubmed-hierarchical is a machine learning model from pendar02. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- bart
- Access
- Public
- Created
- Jan 13, 2025
- Updated
- Jan 13, 2025
- SHA
- 7679caa9
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
bart-pubmed-hierarchical
This model is a fine-tuned version of facebook/bart-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 4.4014
- Rouge1: 20.2
- Rouge2: 1.95
- Rougel: 13.15
- Rougelsum: 18.47
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: 5e-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
- training_steps: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 5.7363 | 0.5 | 5 | 4.6641 | 15.62 | 0.49 | 10.37 | 14.03 |
| 5.4938 | 1.0 | 10 | 4.5342 | 20.66 | 0.95 | 13.1 | 19.59 |
| 4.6575 | 1.5 | 15 | 4.4149 | 20.37 | 1.3 | 12.87 | 18.29 |
| 4.0167 | 2.0 | 20 | 4.4014 | 20.2 | 1.95 | 13.15 | 18.47 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1
- Library
- transformers
- Type
- bart
- License
- apache-2.0
- Created
- Jan 13, 2025
- Updated
- Jan 13, 2025