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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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+
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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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+
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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: llama-2-qlora-alpaca2k
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+
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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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+
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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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+
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+ adapter: qlora
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+ lora_model_dir:
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+
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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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+
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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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+
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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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+
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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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+
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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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+
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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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+