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DistilBART_CNN_GNAD
Einmalumdiewelt/DistilBART_CNN_GNAD
DistilBART_CNN_GNAD is a machine learning model from Einmalumdiewelt. 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.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- Model type
- bart
- Access
- Public
- Created
- Aug 5, 2022
- Updated
- Aug 6, 2022
- SHA
- a90f0908
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. -->
DistilBART_CNN_GNAD
This model is a fine-tuned version of Einmalumdiewelt/DistilBART_CNN_GNAD on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.8723
- Rouge1: 27.4368
- Rouge2: 8.159
- Rougel: 18.1359
- Rougelsum: 23.1339
- Gen Len: 91.5847
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: 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: 10.0
Training results
Framework versions
- Transformers 4.22.0.dev0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
- Library
- transformers
- Type
- bart
- Languages
- de
- Created
- Aug 5, 2022
- Updated
- Aug 6, 2022