--- library_name: peft license: llama3.2 base_model: unsloth/Llama-3.2-3B-Instruct tags: - axolotl - generated_from_trainer model-index: - name: 2b60f15a-e2bc-4ba0-9628-ecf0b960e3ac results: [] --- [Built with Axolotl](https://github.com/axolotl-ai-cloud/axolotl)
See axolotl config axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/Llama-3.2-3B-Instruct bf16: true bnb_config_kwargs: bnb_4bit_quant_type: nf4 bnb_4bit_use_double_quant: true chat_template: llama3 cosine_min_lr_ratio: 0.1 data_processes: 16 dataset_prepared_path: null datasets: - data_files: - alpaca-cleaned_train_data.json ds_type: json path: /workspace/input_data/alpaca-cleaned_train_data.json type: field_input: input field_instruction: instruction field_output: output system_format: '{system}' system_prompt: '' debug: null deepspeed: null device_map: ? '' : cuda:0 do_eval: false early_stopping_patience: null eval_batch_size: 6 eval_sample_packing: false eval_steps: 0 evaluation_strategy: 'no' flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 10 gradient_checkpointing: true group_by_length: true hub_model_id: cwaud/2b60f15a-e2bc-4ba0-9628-ecf0b960e3ac hub_repo: cwaud hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lora_target_modules: - q_proj - v_proj lr_scheduler: cosine max_grad_norm: 1.0 max_memory: 0: 76GiB max_steps: 400 micro_batch_size: 6 mlflow_experiment_name: /tmp/alpaca-cleaned_train_data.json model_type: UnknownForCausalLM num_epochs: 3 optim_args: adam_beta1: 0.9 adam_beta2: 0.95 adam_epsilon: 1e-5 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_strategy: epoch sequence_len: 2048 strict: false tf32: false tokenizer_type: AutoTokenizer torch_compile: false train_on_inputs: false val_set_size: 50 wandb_entity: rayonlabs-rayon-labs wandb_mode: online wandb_project: Public_TuningSN wandb_run: miner_id_24 wandb_runid: 2b60f15a-e2bc-4ba0-9628-ecf0b960e3ac warmup_raio: 0.03 warmup_ratio: 0.03 weight_decay: 0.01 xformers_attention: null ```

# 2b60f15a-e2bc-4ba0-9628-ecf0b960e3ac This model is a fine-tuned version of [unsloth/Llama-3.2-3B-Instruct](https://huggingface.co/unsloth/Llama-3.2-3B-Instruct) on the None dataset. ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 6 - eval_batch_size: 6 - seed: 42 - distributed_type: multi-GPU - num_devices: 4 - gradient_accumulation_steps: 10 - total_train_batch_size: 240 - total_eval_batch_size: 24 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 12 - training_steps: 400 ### Training results ### Framework versions - PEFT 0.13.2 - Transformers 4.45.2 - Pytorch 2.4.1+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1