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@@ -76,6 +76,35 @@ scores = batch_scores[:, 1].exp().tolist()
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  print(scores) # [0.0020704232156276703, 0.9999990463256836] first document is not relevant, as expected
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  ```
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  # Citation
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  ```bibtex
 
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  print(scores) # [0.0020704232156276703, 0.9999990463256836] first document is not relevant, as expected
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  ```
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+ # Training
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+
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+ We used [LLaMA-Factory](https://github.com/hiyouga/LLaMA-Factory) to fine-tune Mistral to create FollowIR-7B, with the following training script:
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+ ```bash
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+ #!/bin/bash
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+ accelerate launch src/train_bash.py \
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+ --stage sft \
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+ --do_train \
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+ --model_name_or_path "mistralai/Mistral-7B-Instruct-v0.2" \
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+ --dataset followIR-train \
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+ --template mistral \
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+ --output_dir OUTPUT \
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+ --finetuning_type lora \
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+ --lora_target q_proj,v_proj,o_proj,k_proj \
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+ --overwrite_cache \
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+ --per_device_train_batch_size 32 \
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+ --gradient_accumulation_steps 1 \
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+ --lr_scheduler_type cosine \
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+ --logging_steps 2 \
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+ --save_steps 29 \
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+ --learning_rate 3e-5 \
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+ --num_train_epochs 8.0 \
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+ --plot_loss \
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+ --max_length 2048 \
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+ --lora_rank 8 \
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+ --lora_alpha 16 \
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+ --bf16
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+ ```
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+
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  # Citation
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  ```bibtex