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mpasila/NordicAlpaca-Finnish-V1-7B-LoRA
NordicAlpaca-Finnish-V1-7B-LoRA is a machine learning model from mpasila. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as apache-2.0.
LoRA trained in 4-bit using HPLT/gpt-7b-nordic-prerelease as the base model for 1 epoch. Dataset used with the LoRA is pinzhenchen/alpaca-cleaned-fi.
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From the Hugging Face model README
LoRA trained in 4-bit using HPLT/gpt-7b-nordic-prerelease as the base model for 1 epoch. Dataset used with the LoRA is pinzhenchen/alpaca-cleaned-fi.
It uses Alpaca format but with a translated instruction at the start:
{
"instruction,output": "Alla on ohje, jossa kuvataan tehtävä. Kirjoita vastaus, joka täyttää pyynnön asianmukaisesti.\n\n### Instruction:\n%instruction%\n\n### Response:\n%output%",
"instruction,input,output": "Alla on ohje, jossa kuvataan tehtävä ja joka on yhdistetty kontekstia lisäävään syötteeseen. Kirjoita vastaus, joka täyttää pyynnön asianmukaisesti.\n\n### Instruction:\n%instruction%\n\n### Input:\n%input%\n\n### Response:\n%output%"
}
Using the following settings:
{
"lora_name": "Alpaca-Finnish-v1",
"always_override": false,
"q_proj_en": true,
"v_proj_en": true,
"k_proj_en": false,
"o_proj_en": false,
"gate_proj_en": false,
"down_proj_en": false,
"up_proj_en": false,
"save_steps": 250.0,
"micro_batch_size": 4,
"batch_size": 128,
"epochs": 3.0,
"learning_rate": "3e-4",
"lr_scheduler_type": "linear",
"lora_rank": 256,
"lora_alpha": 512,
"lora_dropout": 0.05,
"cutoff_len": 384,
"dataset": "alpaca_data_cleaned.fi",
"eval_dataset": "None",
"format": "alpaca-format-finnish",
"eval_steps": 100.0,
"raw_text_file": "None",
"overlap_len": 128,
"newline_favor_len": 128,
"higher_rank_limit": false,
"warmup_steps": 100.0,
"optimizer": "adamw_torch",
"hard_cut_string": "\\n\\n\\n",
"train_only_after": "",
"stop_at_loss": 0,
"add_eos_token": false,
"min_chars": 0.0,
"report_to": "None"
}