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README.md
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Note: Our models are tuned based on Codellama, thus, licenses applicable to Codellama, such as [Llama license](https://ai.meta.com/resources/models-and-libraries/llama-downloads/), also hold on these models
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| | Top-1 | Voting@100 | Rerank@100 |
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| Codellama-7b-hf-SFT-warmup-GSM8k | 63.00 | - | - |
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| Codellama-7b-hf-SFT-GSM8k<br>(+Codellama-7b-hf-SFT-Rerank-GSM8k) | 63.68 | 68.0 | 77.0 |
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| Codellama-7b-hf-ReFT-GSM8k<br>(+Codellama-7b-hf-ReFT-Rerank-GSM8k) | 75.28 | 78.0 | 81.2 |
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## Training Data
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The model is trained on GSM8k data with Python SDP CoT format, which can be found [here](https://github.com/lqtrung1998/mwp_ReFT)
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## Evaluation Results
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See evaluations results of the models at table 4 of the research paper.
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## Usage
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You can use the models through Huggingface's Transformers library or follow scripts in our repo.
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Note: Our models are tuned based on Codellama, thus, licenses applicable to Codellama, such as [Llama license](https://ai.meta.com/resources/models-and-libraries/llama-downloads/), also hold on these models
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## Training Data
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The model is trained on GSM8k data with Python SDP CoT format, which can be found [here](https://github.com/lqtrung1998/mwp_ReFT)
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## Evaluation Results
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See evaluations results of the models at table 4 of the research paper.
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Updated results:
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| | Top-1 | Voting@100 | Rerank@100 |
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| Codellama-7b-hf-SFT-warmup-GSM8k | 63.00 | - | - |
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| Codellama-7b-hf-SFT-GSM8k<br>(+Codellama-7b-hf-SFT-Rerank-GSM8k) | 63.68 | 68.0 | 77.0 |
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| Codellama-7b-hf-ReFT-GSM8k<br>(+Codellama-7b-hf-ReFT-Rerank-GSM8k) | 75.28 | 78.0 | 81.2 |
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## Usage
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You can use the models through Huggingface's Transformers library or follow scripts in our repo.
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