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--- |
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model-index: |
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- name: Junrulu/Reproduced-tulu2-dpo-13b |
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results: [] |
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datasets: |
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- HuggingFaceH4/ultrafeedback_binarized |
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- Junrulu/Reproduced-tulu2-test-sets |
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language: |
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- en |
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base_model: allenai/tulu-2-13b |
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--- |
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# Model Card for Reproduced Tulu2 DPO 13B |
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This repository provides a reproduction version of Tulu2-DPO-13B finetuned upon [Tulu2-13B](https://huggingface.co./allenai/tulu-2-13b) and [Ultrafeedback](https://huggingface.co./datasets/HuggingFaceH4/ultrafeedback_binarized). Therefore, we obey all licenses mentioned in Tulu2's work. Check our codes for more details: https://github.com/LuJunru/LLM_Finetune/tree/DPO, which is built with [TRL](https://github.com/huggingface/trl/tree/main). |
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## Performance |
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| Model | Size | Alignment | MT-Bench (score) | AlpacaEval 2.0 (win rate %) | |
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|-------------|-----|----|---------------|--------------| |
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| **Tulu-v2-13b** 🐪 | **13B** | **SFT** | **5.79** | **2.61** | |
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| **Tulu-v2-dpo-13b** 🐪 | **13B** | **DPO** | **6.06** | **6.96** | |
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| **Reproduced-tulu2-dpo-13b** | **13B** | **DPO** | **6.27** | **6.71** | |
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## Input Format |
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The model is trained to use the following format (note the newlines): |
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``` |
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<|user|> |
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Your message here! |
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<|assistant|> |
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``` |
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For best results, format all inputs in this manner. **Make sure to include a newline after `<|assistant|>`, this can affect generation quality quite a bit.** Note: if fine-tuning with this chat template, ensure to evaluate and test with the chat template. Otherwise, fine-tining without the template if you choose to not use template during testing. Any mismatch of the chatting template between training and testing phases can obviously dampen the final performance. |
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## Training hyperparameters |
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The following hyperparameters were used during DPO training: |
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- DPO beta: 0.1 |
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- learning_rate: 1e-6 * sqrt(Num of Nodes) |
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- total_train_batch_size: 128 * Num of Nodes |
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- optimizer: AdamW with beta1 0.9, beta2 0.999 and epsilon 1e-8 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- Weight Decay: 0.0 |
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- num_epochs: 3.0 |
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- Specifically add above input format over training samples |
