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bart-paraphrase-finetuned-xsum-v3
pranavk/bart-paraphrase-finetuned-xsum-v3
bart-paraphrase-finetuned-xsum-v3 is a machine learning model from pranavk. 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
- Jun 7, 2022
- Updated
- Jun 7, 2022
- SHA
- e73d747d
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-paraphrase-finetuned-xsum-v3
This model is a fine-tuned version of eugenesiow/bart-paraphrase on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1881
- Rouge1: 99.9251
- Rouge2: 99.9188
- Rougel: 99.9251
- Rougelsum: 99.9251
- Gen Len: 10.17
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: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 100 | 0.2702 | 99.9251 | 99.9188 | 99.9251 | 99.9251 | 10.38 |
| No log | 2.0 | 200 | 0.2773 | 99.9251 | 99.9188 | 99.9251 | 99.9251 | 11.45 |
| No log | 3.0 | 300 | 0.2178 | 99.8148 | 99.7051 | 99.8208 | 99.8148 | 11.19 |
| No log | 4.0 | 400 | 0.3649 | 99.9251 | 99.9188 | 99.9251 | 99.9251 | 12.32 |
| 0.1561 | 5.0 | 500 | 0.2532 | 99.8957 | 99.8875 | 99.8957 | 99.8918 | 10.375 |
| 0.1561 | 6.0 | 600 | 0.2050 | 99.9251 | 99.9188 | 99.9251 | 99.9251 | 11.15 |
| 0.1561 | 7.0 | 700 | 0.2364 | 99.8957 | 99.8875 | 99.8957 | 99.8918 | 10.18 |
| 0.1561 | 8.0 | 800 | 0.2006 | 99.9251 | 99.9188 | 99.9251 | 99.9251 | 10.17 |
| 0.1561 | 9.0 | 900 | 0.1628 | 99.9251 | 99.9188 | 99.9251 | 99.9251 | 10.23 |
| 0.1538 | 10.0 | 1000 | 0.1881 | 99.9251 | 99.9188 | 99.9251 | 99.9251 | 10.17 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
- Library
- transformers
- Type
- bart
- License
- apache-2.0
- Created
- Jun 7, 2022
- Updated
- Jun 7, 2022