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--- |
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datasets: |
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- mhenrichsen/alpaca_2k_test |
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pipeline_tag: text2text-generation |
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--- |
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[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl) |
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Small qlora finetune using Axolotl. Locally tested using `wikitext` perplexity test and had a small improvement over the base Llama v2 7B base model. |
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Axolotl config used: |
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```yaml |
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base_model: NousResearch/Llama-2-7b-hf |
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base_model_config: NousResearch/Llama-2-7b-hf |
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model_type: LlamaForCausalLM |
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tokenizer_type: LlamaTokenizer |
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push_dataset_to_hub: |
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hub_model_id: |
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load_in_8bit: false |
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load_in_4bit: true |
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strict: false |
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datasets: |
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- path: mhenrichsen/alpaca_2k_test |
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type: alpaca |
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dataset_prepared_path: last_run_prepared |
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val_set_size: 0.01 |
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output_dir: ./checkpoints/llama-2-qlora |
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adapter: qlora |
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lora_model_dir: |
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sequence_len: 4096 |
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max_packed_sequence_len: 4096 |
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lora_r: 32 |
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lora_alpha: 16 |
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lora_dropout: 0.05 |
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lora_target_modules: |
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lora_target_linear: true |
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lora_fan_in_fan_out: |
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wandb_project: |
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wandb_watch: |
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wandb_run_id: |
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wandb_log_model: |
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gradient_accumulation_steps: 4 |
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micro_batch_size: 2 |
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num_epochs: 3 |
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optimizer: paged_adamw_32bit |
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lr_scheduler: cosine |
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learning_rate: 0.0002 |
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train_on_inputs: false |
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group_by_length: true |
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bf16: true |
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fp16: false |
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tf32: true |
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gradient_checkpointing: true |
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early_stopping_patience: |
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resume_from_checkpoint: |
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local_rank: |
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logging_steps: 1 |
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xformers_attention: true |
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flash_attention: |
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warmup_steps: 10 |
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eval_steps: 20 |
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save_steps: |
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debug: |
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deepspeed: |
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weight_decay: 0.0 |
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fsdp: |
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fsdp_config: |
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special_tokens: |
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bos_token: "<s>" |
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eos_token: "</s>" |
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unk_token: "<unk>" |
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``` |
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And then merged with Axolotl via: |
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``` |
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accelerate launch scripts/finetune.py configs/your_config.yml --merge_lora --lora_model_dir="./completed-model" --load_in_8bit=False --load_in_4bit=False |
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``` |
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