---
base_model: mistralai/Mistral-7B-Instruct-v0.3
datasets:
- generator
library_name: peft
license: apache-2.0
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: Mistral-7B-text-to-sql-flash-attention-2-FAISS
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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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](https://huggingface.co/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/FAISS_Evaluator_Mistral_7B_text_to_sql.ipynb


### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 3
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 24
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.03
- lr_scheduler_warmup_steps: 15
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.8409        | 0.4   | 10   | 0.6999          |
| 0.616         | 0.8   | 20   | 0.5322          |
| 0.4977        | 1.2   | 30   | 0.4910          |
| 0.4486        | 1.6   | 40   | 0.4661          |
| 0.4313        | 2.0   | 50   | 0.4529          |
| 0.36          | 2.4   | 60   | 0.4620          |
| 0.3534        | 2.8   | 70   | 0.4583          |


### Framework versions

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