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README.md
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---
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library_name: transformers
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license:
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base_model: llm-jp/llm-jp-3-3.7b-instruct
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tags:
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- llama-factory
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model-index:
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- name: sft
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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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- Pytorch 2.4.1+cu121
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- Datasets 3.1.0
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- Tokenizers 0.20.3
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---
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library_name: transformers
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license: apache-2.0
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base_model: llm-jp/llm-jp-3-3.7b-instruct
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tags:
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- llama-factory
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model-index:
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- name: sft
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results: []
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language:
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- ja
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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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- Pytorch 2.4.1+cu121
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- Datasets 3.1.0
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- Tokenizers 0.20.3
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### LLaMA-Factory yaml
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```
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### model
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model_name_or_path: llm-jp/llm-jp-3-3.7b-instruct
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### method
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stage: sft
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do_train: true
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finetuning_type: full
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deepspeed: examples/deepspeed/ds_z3_config.json
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### dataset
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dataset: cot_normal, cot_math
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template: alpaca_ja
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cutoff_len: 8192
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overwrite_cache: true
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preprocessing_num_workers: 16
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### output
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output_dir: saves/llm_jp/full/sft
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logging_steps: 10
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save_steps: 500
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plot_loss: true
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overwrite_output_dir: true
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### train
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per_device_train_batch_size: 8
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gradient_accumulation_steps: 4
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learning_rate: 1.0e-5
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num_train_epochs: 2.0
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lr_scheduler_type: cosine
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optim: adamw_bnb_8bit
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warmup_ratio: 0.1
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bf16: true
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ddp_timeout: 180000000
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### eval
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val_size: 0.01
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per_device_eval_batch_size: 1
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eval_strategy: steps
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eval_steps: 500
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### logging
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report_to: wandb
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```
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