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--- |
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library_name: peft |
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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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- text-to-sql |
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- Spider |
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base_model: VictorDCh/Llama-3-8B-Instruct-MoE-2 |
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datasets: |
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- generator |
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- Hexamind/spider-clean-text-to-sql |
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model-index: |
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- name: Llama-3-8B-Instruct-MoE-2-spider |
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results: [] |
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language: |
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- en |
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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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# Llama-3-8B-Instruct-MoE-2-spider |
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This model is a fine-tuned version of [VictorDCh/Llama-3-8B-Instruct-MoE-2](https://huggingface.co/VictorDCh/Llama-3-8B-Instruct-MoE-2) on the generator dataset. |
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## Model description |
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This is a mixture of experts merged with mergekit from 4 experts (Llama 3 8B Instruct), fine-tuned on the Spider train dataset. |
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## Intended uses & limitations |
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This is part of a research project on using open-source models for text-to-SQL use cases. |
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Some pre-processing of the input data, and post-processing of the results may be necessary to obtain optimal results. |
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The input prompt uses the following system-user-assistant format: |
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- system message: """You are a text to SQL query translator. Users will ask you questions in English and you will generate a SQL query based on the provided SCHEMA. Only generate SQL. |
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SCHEMA: |
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{schema}""" |
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- user message: """Here is the user question in natural language: {question} """ |
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- assistant message (empty when testing): {SQL query} |
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## Training and evaluation data |
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The training and testing dataset can be found here: [Cleaned Spider dataset](https://huggingface.co/datasets/Hexamind/spider-clean-text-to-sql). |
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## Training procedure |
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One epoch of SFT on the train dataset as explained above. |
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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: 2 |
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- total_train_batch_size: 2 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.03 |
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- num_epochs: 1 |
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### Framework versions |
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- PEFT 0.7.2.dev0 |
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- Transformers 4.36.2 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.2 |
