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Model: corag/CoRAG-Llama3.1-8B-MultihopQA Source: Original Platform
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README.md
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---
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license: apache-2.0
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---
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# CoRAG-Llama3.1-8B-MultihopQA
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This is the CoRAG-8B model fine-tuned on [MultihopQA data](https://huggingface.co/datasets/corag/multihopqa) in the paper [Chain-of-Retrieval Augmented Generation](https://arxiv.org/abs/2501.14342).
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## Model Evaluation
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| **Model** | **2WikiQA EM** | **2WikiQA F1** | **HotpotQA EM** | **HotpotQA F1** | **Bamboogle EM** | **Bamboogle F1** | **MuSiQue EM** | **MuSiQue F1** |
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|----------------------------------------|----------------|----------------|------------------|------------------|------------------|------------------|----------------|----------------|
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| **3-shot Llama-3.1-8B-Inst.** | 30.7 | 39.9 | 34.1 | 46.6 | 28.0 | 37.3 | 7.7 | 15.4 |
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| **3-shot GPT-4o** | 49.0 | 56.2 | 45.8 | 59.4 | 53.6 | 63.8 | 15.7 | 25.8 |
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| **Fine-tuned Llama-8B w/ E5<sub>large</sub>** | 55.1 | 60.7 | 50.3 | 63.5 | 40.8 | 53.7 | 17.4 | 28.1 |
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| **CoRAG-8B (Ours)** | | | | | | | | |
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| > L=1, greedy | 56.5 | 62.3 | 50.1 | 63.2 | 37.6 | 51.4 | 18.6 | 29.3 |
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| > L=6, greedy | 70.6 | 75.5 | 54.4 | 67.5 | 48.0 | 63.5 | 27.7 | 38.5 |
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| > L=6, best-of-4 | 71.7 | 76.5 | 55.3 | 68.5 | 51.2 | 63.1 | 28.1 | 39.7 |
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| > L=6, tree search | 71.7 | 76.4 | 55.8 | 69.0 | 48.8 | 64.4 | 29.0 | 40.3 |
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| > L=10, best-of-8 | **72.5** | **77.3** | **56.3** | **69.8** | **54.4** | **68.3** | **30.9** | **42.4** |
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Please refer to [https://github.com/microsoft/LMOps/tree/main/corag](https://github.com/microsoft/LMOps/tree/main/corag) for evaluation instructions.
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Model predictions are available as the `predictions` field at https://huggingface.co/datasets/corag/multihopqa
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## Disclaimer
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This model has been specifically trained for the task of MultihopQA. It may not perform well on other tasks.
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## References
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```
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@article{wang2025chain,
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title={Chain-of-Retrieval Augmented Generation},
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author={Wang, Liang and Chen, Haonan and Yang, Nan and Huang, Xiaolong and Dou, Zhicheng and Wei, Furu},
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journal={arXiv preprint arXiv:2501.14342},
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year={2025}
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}
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```
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config.json
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{
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"_name_or_path": "corag-8b/",
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"architectures": [
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"LlamaForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"initializer_range": 0.02,
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"intermediate_size": 14336,
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"max_position_embeddings": 131072,
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"mlp_bias": false,
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"model_type": "llama",
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"num_attention_heads": 32,
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"num_hidden_layers": 32,
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"num_key_value_heads": 8,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_scaling": {
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"factor": 8.0,
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"high_freq_factor": 4.0,
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"low_freq_factor": 1.0,
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"original_max_position_embeddings": 8192,
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"rope_type": "llama3"
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},
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"rope_theta": 500000.0,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.49.0",
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"use_cache": false,
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"vocab_size": 128256
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}
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