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--- |
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license: apache-2.0 |
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base_model: Salesforce/codet5-small |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: sodabot-sql-sm |
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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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# sql-sodabot-v1.0 |
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This encoder-decoder model is a descendent of [Salesforce/codet5-small](https://huggingface.co/Salesforce/codet5-small), fine-tuned on a modified version of [b-mc2/sql-create-context](https://huggingface.co/datasets/b-mc2/sql-create-context) data. The original [CodeT5](https://github.com/salesforce/CodeT5) was published by Salesfoce Research as an "AI-powered coding assistant to boost the productivity of software developers". The goal of this project is to apply transfer learning in order to appropriate this model for text-to-SQL applications, specifically in the context of generating Socrata SQL ([SoQL](https://dev.socrata.com/docs/queries/)) queries that can be executed on the Socrata Open Data API (e.g., to analyze [NYC Open Data](https://opendata.cityofnewyork.us)). |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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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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- num_epochs: 25 |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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