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Big-Bart-BBC
sss1465236/Big-Bart-BBC
Big-Bart-BBC is a machine learning model from sss1465236. 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
- Dec 29, 2023
- Updated
- Dec 29, 2023
- SHA
- b201478c
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. -->
Big-Bart-BBC
This model is a fine-tuned version of facebook/bart-large-cnn on the None dataset. It achieves the following results on the evaluation set:
- Loss: 4.1339
- Rouge1: 0.2638
- Rouge2: 0.1052
- Rougel: 0.2019
- Rougelsum: 0.202
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: 5.6e-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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 3.001 | 1.0 | 1652 | 2.8616 | 0.2179 | 0.0571 | 0.1565 | 0.1564 |
| 1.7636 | 2.0 | 3304 | 2.7371 | 0.2423 | 0.0772 | 0.1766 | 0.1767 |
| 0.9422 | 3.0 | 4956 | 3.1619 | 0.2463 | 0.0842 | 0.1832 | 0.1832 |
| 0.4259 | 4.0 | 6608 | 3.5730 | 0.2645 | 0.1009 | 0.2001 | 0.2002 |
| 0.1637 | 5.0 | 8260 | 4.1339 | 0.2638 | 0.1052 | 0.2019 | 0.202 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0
- Library
- transformers
- Type
- bart
- License
- mit
- Created
- Dec 29, 2023
- Updated
- Dec 29, 2023