--- library_name: peft license: llama3.2 base_model: unsloth/Llama-3.2-1B-Instruct tags: - axolotl - generated_from_trainer model-index: - name: adb6691b-5aa3-4e0a-9e9b-b517cdd966c5 results: [] --- [Built with Axolotl](https://github.com/axolotl-ai-cloud/axolotl)
See axolotl config axolotl version: `0.4.1` ```yaml adapter: lora auto_find_batch_size: true base_model: unsloth/Llama-3.2-1B-Instruct bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 13030f82a7571cf7_train_data.json ds_type: json format: custom path: /workspace/input_data/13030f82a7571cf7_train_data.json type: field_instruction: instruction field_output: output format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null do_eval: true early_stopping_patience: 3 eval_max_new_tokens: 128 eval_steps: 50 evals_per_epoch: null flash_attention: true fp16: false fsdp: null fsdp_config: null gradient_accumulation_steps: 2 gradient_checkpointing: false group_by_length: true hub_model_id: lesso18/adb6691b-5aa3-4e0a-9e9b-b517cdd966c5 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.000218 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 10 lora_alpha: 128 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 64 lora_target_linear: true lr_scheduler: cosine max_grad_norm: 1.0 max_steps: 500 micro_batch_size: 4 mlflow_experiment_name: /tmp/G.O.D/13030f82a7571cf7_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 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_steps: 50 saves_per_epoch: null sequence_len: 512 strict: false tf32: true tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 78f7460c-9707-40e5-94f3-dea53da5269b wandb_project: 18a wandb_run: your_name wandb_runid: 78f7460c-9707-40e5-94f3-dea53da5269b warmup_steps: 50 weight_decay: 0.0 xformers_attention: null ```

# adb6691b-5aa3-4e0a-9e9b-b517cdd966c5 This model is a fine-tuned version of [unsloth/Llama-3.2-1B-Instruct](https://huggingface.co/unsloth/Llama-3.2-1B-Instruct) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.2517 ## 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: 0.000218 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 50 - training_steps: 500 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0002 | 1 | 3.1149 | | 2.7042 | 0.0083 | 50 | 2.7513 | | 3.0109 | 0.0165 | 100 | 2.7991 | | 2.5636 | 0.0248 | 150 | 2.7374 | | 3.0321 | 0.0331 | 200 | 2.5573 | | 2.8198 | 0.0413 | 250 | 2.4827 | | 2.2206 | 0.0496 | 300 | 2.4009 | | 2.9364 | 0.0578 | 350 | 2.2891 | | 2.5913 | 0.0661 | 400 | 2.2623 | | 2.5269 | 0.0744 | 450 | 2.2431 | | 2.3284 | 0.0826 | 500 | 2.2517 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1