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qna-flan-t5
yinyinmayphoo/qna-flan-t5
qna-flan-t5 is a machine learning model from yinyinmayphoo. 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
- t5
- Access
- Public
- Created
- Sep 4, 2025
- Updated
- Sep 10, 2025
- SHA
- 2d3dca2e
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. -->
qna-flan-t5
This model is a fine-tuned version of google/flan-t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.4172
- Rouge1: 0.3723
- Rouge2: 0.0628
- Rougel: 0.2732
- Rougelsum: 0.2723
- Exact Match: 0.0
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: 4
- eval_batch_size: 4
- 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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Exact Match |
|---|---|---|---|---|---|---|---|---|
| 3.8463 | 1.0 | 10 | 3.4578 | 0.3619 | 0.0579 | 0.264 | 0.2628 | 0.0 |
| 3.7379 | 2.0 | 20 | 3.4268 | 0.3703 | 0.0628 | 0.2696 | 0.2694 | 0.0 |
| 3.6993 | 3.0 | 30 | 3.4172 | 0.3723 | 0.0628 | 0.2732 | 0.2723 | 0.0 |
Framework versions
- Transformers 4.56.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Sep 4, 2025
- Updated
- Sep 10, 2025