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  results: []
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  ---
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- <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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- should probably proofread and complete it, then remove this comment. -->
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-
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  # zephyr-7b-sft-qlora
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- This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the HuggingFaceH4/ultrachat_200k dataset.
 
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  It achieves the following results on the evaluation set:
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  - Loss: 0.9523
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  ## Model description
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- More information needed
 
 
 
 
 
 
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  ## Intended uses & limitations
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- More information needed
 
 
 
 
 
 
 
 
 
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  ## Training and evaluation data
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- More information needed
 
 
 
 
 
 
 
 
 
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  ## Training procedure
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  results: []
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  ---
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  # zephyr-7b-sft-qlora
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+ This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mist\
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+ ral-7B-v0.1) on the HuggingFaceH4/ultrachat_200k dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.9523
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  ## Model description
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+ QLoRA SFT via
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+ ```
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+ # Step 1 - SFT
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+ ACCELERATE_LOG_LEVEL=info accelerate launch --config_file recipes/accelerate_configs/multi_gpu.yaml --n\
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+ um_processes=1 scripts/run_sft.py recipes/zephyr-7b-beta/sft/config_qlora.yaml --load_in_4bit=true
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+ ```
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+ see https://github.com/huggingface/alignment-handbook/blob/main/recipes/zephyr-7b-beta/README.md
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  ## Intended uses & limitations
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+ ```
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+ chat_template: "{% for message in messages %}\n{% if message['role'] == 'user' %}\n{{ '<|user|>\n' + me\
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+ ssage['content'] + eos_token }}\n{% elif message['role'] == 'system' %}\n{{ '<|system|>\n' + message['c\
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+ ontent'] + eos_token }}\n{% elif message['role'] == 'assistant' %}\n{{ '<|assistant|>\n' + message['co\
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+ ntent'] + eos_token }}\n{% endif %}\n{% if loop.last and add_generation_prompt %}\n{{ '<|assistant|>' }\
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+ }\n{% endif %}\n{% endfor %}"
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+ ```
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+
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+ see https://github.com/huggingface/alignment-handbook/blob/main/recipes/zephyr-7b-beta/sft/config_qlora\
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+ .yaml
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  ## Training and evaluation data
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+ ```
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+ dataset_mixer:
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+ HuggingFaceH4/ultrachat_200k: 1.0
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+ dataset_splits:
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+ - train_sft
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+ - test_sft
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+ ```
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+
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+ see https://github.com/huggingface/alignment-handbook/blob/main/recipes/zephyr-7b-beta/sft/config_qlora\
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+ .yaml
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  ## Training procedure
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