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--- |
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base_model: mistralai/Mistral-7B-Instruct-v0.3 |
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datasets: |
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- generator |
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library_name: peft |
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license: apache-2.0 |
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tags: |
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- trl |
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- sft |
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- generated_from_trainer |
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model-index: |
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- name: Mistral-7B-text-to-sql-flash-attention-2-FAISS |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Mistral-7B-text-to-sql-flash-attention-2-FAISS |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4583 |
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## Model description |
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Article: https://medium.com/@frankmorales_91352/faiss-powered-semantic-search-meets-fine-tuned-mistral-a-novel-approach-to-text-to-sql-generation-fc633d9c1bc2 |
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## Training and evaluation data |
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Training: https://github.com/frank-morales2020/MLxDL/blob/main/FAISS_FINETUNING.ipynb |
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Evaluation: https://github.com/frank-morales2020/MLxDL/blob/main/FAISS_Evaluator_Mistral_7B_text_to_sql.ipynb |
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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: 3 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 24 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: constant |
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- lr_scheduler_warmup_ratio: 0.03 |
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- lr_scheduler_warmup_steps: 15 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 1.8409 | 0.4 | 10 | 0.6999 | |
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| 0.616 | 0.8 | 20 | 0.5322 | |
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| 0.4977 | 1.2 | 30 | 0.4910 | |
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| 0.4486 | 1.6 | 40 | 0.4661 | |
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| 0.4313 | 2.0 | 50 | 0.4529 | |
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| 0.36 | 2.4 | 60 | 0.4620 | |
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| 0.3534 | 2.8 | 70 | 0.4583 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.42.3 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
