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_qa_no_context-finetuned-xsum
javedonline/_qa_no_context-finetuned-xsum
_qa_no_context-finetuned-xsum is a machine learning model from javedonline. 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
- Mar 18, 2025
- Updated
- Mar 18, 2025
- SHA
- 6f9290c3
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. -->
_qa_no_context-finetuned-xsum
This model is a fine-tuned version of google/t5-v1_1-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: nan
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: 0.002
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 215 | nan |
| No log | 2.0 | 430 | nan |
| 0.0 | 3.0 | 645 | nan |
| 0.0 | 4.0 | 860 | nan |
| 0.0 | 5.0 | 1075 | nan |
| 0.0 | 6.0 | 1290 | nan |
| 0.0 | 7.0 | 1505 | nan |
| 0.0 | 8.0 | 1720 | nan |
| 0.0 | 9.0 | 1935 | nan |
| 0.0 | 10.0 | 2150 | nan |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu118
- Datasets 3.3.1
- Tokenizers 0.21.0
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Mar 18, 2025
- Updated
- Mar 18, 2025