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bart-large-cnn-xsum
ckandrew04/bart-large-cnn-xsum
bart-large-cnn-xsum is a machine learning model from ckandrew04. 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 9, 2024
- Updated
- Dec 9, 2024
- SHA
- 65a78150
Base models
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-xsum
This model is a fine-tuned version of facebook/bart-large-cnn on the xsum dataset. It achieves the following results on the evaluation set:
- Loss: 2.0314
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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.9458 | 0.3921 | 500 | 1.8663 |
| 1.7833 | 0.7842 | 1000 | 1.9308 |
| 1.3364 | 1.1762 | 1500 | 1.9378 |
| 1.3562 | 1.5683 | 2000 | 1.9538 |
| 1.3173 | 1.9604 | 2500 | 1.8672 |
| 0.9227 | 2.3525 | 3000 | 2.0590 |
| 0.8619 | 2.7446 | 3500 | 2.0314 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
- Library
- transformers
- Type
- bart
- License
- mit
- Created
- Dec 9, 2024
- Updated
- Dec 9, 2024