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exesql_postgres
Yanghl0526/exesql_postgres
exesql_postgres is a machine learning model from Yanghl0526. 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 other.
should probably proofread and complete it, then remove this comment. --
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13.8 GB on disk
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At a glance
- Library
- transformers
- License
- other
- Access
- Public
- Created
- Dec 21, 2025
- Updated
- Dec 21, 2025
- SHA
- fd5eb6f6
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. -->
epoch3_dpo_postgres
This model is a fine-tuned version of saves/deepseek-7B/epoch1_full_postgres on the dpo_postgres 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: 5e-06
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- total_eval_batch_size: 32
- 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: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0
Training results
Framework versions
- Transformers 4.46.1
- Pytorch 2.4.1
- Datasets 3.1.0
- Tokenizers 0.20.3
- Library
- transformers
- License
- other
- Created
- Dec 21, 2025
- Updated
- Dec 21, 2025