frankmorales2020/Mistral-7B-text-to-sql-flash-attention-2-FAISS

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Mistral-7B-text-to-sql-flash-attention-2-FAISS

This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.3 on the generator dataset. It achieves the following results on the evaluation set:

• —Loss: 0.4583

Model description

Article: https://medium.com/@frankmorales_91352/faiss-powered-semantic-search-meets-fine-tuned-mistral-a-novel-approach-to-text-to-sql-generation-fc633d9c1bc2

Training and evaluation data

Training: https://github.com/frank-morales2020/MLxDL/blob/main/FAISS_FINETUNING.ipynb

Evaluation: https://github.com/frank-morales2020/MLxDL/blob/main/FAISSEvaluatorMistral7Btexttosql.ipynb

Training hyperparameters

The following hyperparameters were used during training:

• —learning_rate: 0.0002
• —trainbatchsize: 3
• —evalbatchsize: 8
• —seed: 42
• —gradientaccumulationsteps: 8
• —totaltrainbatch_size: 24
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: constant
• —lrschedulerwarmup_ratio: 0.03
• —lrschedulerwarmup_steps: 15
• —num_epochs: 3

Training results

Framework versions

• —PEFT 0.11.1
• —Transformers 4.42.3
• —Pytorch 2.3.0+cu121
• —Datasets 2.20.0
• —Tokenizers 0.19.1