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TensorBoard
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t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use Lexie1212/t5-small-finetuned-question-to-sql with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Lexie1212/t5-small-finetuned-question-to-sql with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Lexie1212/t5-small-finetuned-question-to-sql") model = AutoModelForSeq2SeqLM.from_pretrained("Lexie1212/t5-small-finetuned-question-to-sql", device_map="auto") - Notebooks
- Google Colab
- Kaggle
t5-small-finetuned-question-to-sql
This model is a fine-tuned version of t5-small on the None dataset.
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use 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: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Translation Length |
|---|---|---|---|---|---|
| No log | 1.0 | 211 | 1.1596 | 0.3754 | 17.1585 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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Model tree for Lexie1212/t5-small-finetuned-question-to-sql
Base model
google-t5/t5-small