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bart-base-finetuned-xsum
AkashM/bart-base-finetuned-xsum
bart-base-finetuned-xsum is a machine learning model from AkashM. 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
- Nov 16, 2022
- Updated
- Nov 16, 2022
- SHA
- e90288da
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-base-finetuned-xsum
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: 1.0837
- Rouge1: 53.7269
- Rouge2: 42.5336
- Rougel: 52.0499
- Rougelsum: 52.6213
- Gen Len: 15.0789
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: 16
- eval_batch_size: 16
- 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 |
|---|---|---|---|---|---|---|---|---|
| 1.1829 | 1.0 | 4578 | 1.0837 | 53.7269 | 42.5336 | 52.0499 | 52.6213 | 15.0789 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.2
- Library
- transformers
- Type
- bart
- License
- apache-2.0
- Created
- Nov 16, 2022
- Updated
- Nov 16, 2022