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bart-cnn-science
theojolliffe/bart-cnn-science
bart-cnn-science is a machine learning model from theojolliffe. 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 mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- mit
- Model type
- bart
- Access
- Public
- Created
- May 30, 2022
- Updated
- May 30, 2022
- SHA
- 2b5c0e68
Datasets
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-large-cnn-pubmed1o3-pubmed2o3-pubmed3o3-arxiv1o3-arxiv2o3-arxiv3o3
This model is a fine-tuned version of theojolliffe/bart-large-cnn-pubmed1o3-pubmed2o3-pubmed3o3-arxiv1o3-arxiv2o3 on the scientific_papers dataset. It achieves the following results on the evaluation set:
- Loss: 2.0646
- Rouge1: 42.5835
- Rouge2: 16.1887
- Rougel: 24.7972
- Rougelsum: 38.1846
- Gen Len: 129.9291
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: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 2.0865 | 1.0 | 33840 | 2.0646 | 42.5835 | 16.1887 | 24.7972 | 38.1846 | 129.9291 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
- Library
- transformers
- Type
- bart
- License
- mit
- Created
- May 30, 2022
- Updated
- May 30, 2022