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bart-cnn-samsum-peft-trained
HFS26/bart-cnn-samsum-peft-trained
bart-cnn-samsum-peft-trained is a machine learning model from HFS26. 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 peft. 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
- peft
- License
- mit
- Access
- Public
- Created
- Mar 19, 2026
- Updated
- Mar 19, 2026
- SHA
- aa3431d8
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. -->
bart-cnn-samsum-peft-trained
This model is a fine-tuned version of HFS26/bart-cnn-samsum-finetune-model on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1363
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.0971 | 1.0 | 19 | 0.1364 |
| 0.1004 | 2.0 | 38 | 0.1364 |
| 0.0919 | 3.0 | 57 | 0.1363 |
| 0.0938 | 4.0 | 76 | 0.1363 |
| 0.1085 | 5.0 | 95 | 0.1363 |
Framework versions
- PEFT 0.18.1
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.2
- Tokenizers 0.22.2
- Library
- peft
- License
- mit
- Created
- Mar 19, 2026
- Updated
- Mar 19, 2026