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--- |
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base_model: defog/sqlcoder-7b-2 |
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library_name: peft |
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license: cc-by-sa-4.0 |
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tags: |
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- trl |
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- sft |
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- QLora |
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- peft |
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- SQL |
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- causal-lm |
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model-index: |
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- name: sqlcoder-7b-2_FineTuned_PEFT_QLORA_adapter |
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results: [] |
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language: |
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- en |
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--- |
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# sqlcoder-7b-2_FineTuned_QLORA_Adapter |
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This model is a fine-tuned version of [defog/sqlcoder-7b-2](https://huggingface.co/defog/sqlcoder-7b-2) on 260 SQL examples (Task, Schema and Answer triplets) related to financial/banking domain. |
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## Intended uses & limitations |
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MS SQL Server - SQL Query Generation |
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## Training |
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This model was trained using the QLoRA method with the following configurations: |
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- r = 64, |
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- lora_alpha = 32 |
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- lora_dropout = 0.05 |
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- bias='none' |
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- task_type='CAUSAL_LM' |
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Quantization parameters: |
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- load_in_4bit=True |
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- bnb_4bit_quant_type="nf4" |
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- bnb_4bit_compute_dtype=torch.bfloat16 |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0002 |
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- train_batch_size: 1 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 4 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 10 |
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- num_epochs: 5 |
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- mixed_precision_training: Native AMP |
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### Framework versions |
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- PEFT 0.13.2 |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.2 |
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- Tokenizers 0.19.1 |
