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README.md
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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/
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It achieves the following results on the evaluation set:
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- Loss: 0.9523
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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 --
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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' +
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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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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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- test_sft
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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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# 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 HuggingFaceH4ultrachat_200k dataset.
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It is the first step (Step 1 SFT, see below) of building Zephyr, i.e. before DPO.
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It achieves the following results on the evaluation set:
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- Loss: 0.9523
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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 --num_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' + message['content'] + eos_token }}\n{% elif message['role'] == 'system' %}\n{{ '<|system|>\n' + message['content'] + eos_token }}\n{% elif message['role'] == 'assistant' %}\n{{ '<|assistant|>\n' + message['content'] + eos_token }}\n{% endif %}\n{% if loop.last and add_generation_prompt %}\n{{ '<|assistant|>' }}\n{% endif %}\n{% endfor %}"
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```
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see https://github.com/huggingface/alignment-handbook/blob/main/recipes/zephyr-7b-beta/sft/config_qlora.yaml
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## Training and evaluation data
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- test_sft
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```
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see https://github.com/huggingface/alignment-handbook/blob/main/recipes/zephyr-7b-beta/sft/config_qlora.yaml
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## Training procedure
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