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t5-small-finetuned-wikisql
kaecilius/t5-small-finetuned-wikisql
t5-small-finetuned-wikisql is a machine learning model from kaecilius. 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
- Apr 25, 2025
- Updated
- Apr 25, 2025
- SHA
- e750014d
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. -->
t5-small-finetuned-wikisql
This model is a fine-tuned version of google-t5/t5-small on the wikisql dataset. It achieves the following results on the evaluation set:
- Loss: 0.1346
- Rougel Fmeasure: 85.655
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: 32
- eval_batch_size: 32
- 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: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rougel Fmeasure |
|---|---|---|---|---|
| 0.2154 | 1.0 | 2025 | 0.1703 | 84.069 |
| 0.1831 | 2.0 | 4050 | 0.1498 | 85.027 |
| 0.1649 | 3.0 | 6075 | 0.1405 | 85.392 |
| 0.1569 | 4.0 | 8100 | 0.1361 | 85.514 |
| 0.1549 | 5.0 | 10125 | 0.1346 | 85.655 |
Framework versions
- Transformers 4.51.1
- Pytorch 2.5.1+cu124
- Datasets 3.5.0
- Tokenizers 0.21.0
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Apr 25, 2025
- Updated
- Apr 25, 2025