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README.md
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---
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license: apache-2.0
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datasets:
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- Intel/orca_dpo_pairs
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tags:
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- mistral
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- dpo
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- una
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- finetune
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- chatml
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- instruct
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---
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/6468ce47e134d050a58aa89c/-BlRd-74Hk4B153wl_ryD.png)
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# Neural-una-cybertron-7b
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Neural-una-cybertron-7b is an [fblgit/una-cybertron-7b-v2-bf16](https://huggingface.co/fblgit/una-cybertron-7b-v2-bf16) model that has been further fine-tuned with Direct Preference Optimization (DPO) using the [Intel/orca_dpo_pairs](https://huggingface.co/datasets/Intel/orca_dpo_pairs) dataset.
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This model was created after examining the procedure of [mlabonne/NeuralHermes-2.5-Mistral-7B](https://hf.co/mlabonne/NeuralHermes-2.5-Mistral-7B) model. Special thanks to [@mlabonne](https://hf.co/mlabonne).
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## Addionatal Information
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This model was fine-tuned on `Nvidia A100-SXM4-40GB` GPU.
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The total training time was 1 hour and 10 minutes.
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# Prompt Template(s)
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### ChatML
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```
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<|im_start|>system
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{system}<|im_end|>
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<|im_start|>user
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{user}<|im_end|>
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<|im_start|>assistant
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{asistant}<|im_end|>
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```
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## Training hyperparameters
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**LoRA**:
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* r=16
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* lora_alpha=16
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* lora_dropout=0.05
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* bias="none"
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* task_type="CAUSAL_LM"
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* target_modules=['k_proj', 'gate_proj', 'v_proj', 'up_proj', 'q_proj', 'o_proj', 'down_proj']
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**Training arguments**:
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* per_device_train_batch_size=4
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* gradient_accumulation_steps=4
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* gradient_checkpointing=True
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* learning_rate=5e-5
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* lr_scheduler_type="cosine"
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* max_steps=200
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* optim="paged_adamw_32bit"
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* warmup_steps=100
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**DPOTrainer**:
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* beta=0.1
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* max_prompt_length=1024
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* max_length=1536
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