Create README.md
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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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- habanoz/airoboros-3.1-no-mathjson-max-1k
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language:
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- en
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pipeline_tag: text-generation
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---
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Microsoft/phi-1.5 finetuned using airoboros-3.1-no-mathjson-max-1k dataset.
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Qlora is used. Adapter is merged.
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SFT code:
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https://github.com/habanoz/qlora.git
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Command used:
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```bash
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accelerate launch $BASE_DIR/qlora/train.py \
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--model_name_or_path $BASE_MODEL \
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--working_dir $BASE_DIR/$OUTPUT_NAME-checkpoints \
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--output_dir $BASE_DIR/$OUTPUT_NAME-peft \
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--merged_output_dir $BASE_DIR/$OUTPUT_NAME \
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--final_output_dir $BASE_DIR/$OUTPUT_NAME-final \
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--num_train_epochs 1 \
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--logging_steps 1 \
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--save_strategy steps \
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--save_steps 120 \
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--save_total_limit 2 \
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--data_seed 11422 \
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--evaluation_strategy steps \
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--per_device_eval_batch_size 4 \
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--eval_dataset_size 0.01 \
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--eval_steps 120 \
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--max_new_tokens 1024 \
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--dataloader_num_workers 3 \
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--logging_strategy steps \
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--do_train \
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--do_eval \
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--lora_r 64 \
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--lora_alpha 16 \
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--lora_modules all \
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--bits 4 \
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--double_quant \
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--quant_type nf4 \
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--lr_scheduler_type constant \
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--dataset habanoz/airoboros-3.1-no-mathjson-max-1k \
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--dataset_format airoboros_chat \
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--model_max_len 1024 \
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--per_device_train_batch_size 1 \
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--gradient_accumulation_steps 16 \
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--learning_rate 1e-5 \
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--adam_beta2 0.999 \
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--max_grad_norm 0.3 \
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--lora_dropout 0.0 \
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--weight_decay 0.0 \
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--seed 11422 \
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--gradient_checkpointing False \
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--use_flash_attention_2 \
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--ddp_find_unused_parameters False \
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--trust_remote_code True
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```
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