--- library_name: peft license: llama3.2 base_model: unsloth/Llama-3.2-3B tags: - axolotl - generated_from_trainer model-index: - name: 76fe64ac-a9e7-446d-9942-b8aaf7ec897b 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 bf16: true chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 1e7b9c404170ea58_train_data.json ds_type: json field: text path: /workspace/input_data/1e7b9c404170ea58_train_data.json type: completion debug: null deepspeed: null device_map: auto early_stopping_patience: 1 eval_max_new_tokens: 128 eval_steps: 25 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: false fsdp: null fsdp_config: null gradient_accumulation_steps: 8 gradient_checkpointing: true group_by_length: false hub_model_id: bbytxt/76fe64ac-a9e7-446d-9942-b8aaf7ec897b hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0004 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 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_memory: 0: 70GB max_steps: 50 micro_batch_size: 6 mlflow_experiment_name: /tmp/1e7b9c404170ea58_train_data.json model_type: AutoModelForCausalLM num_epochs: 3 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: 25 saves_per_epoch: null sequence_len: 2048 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: 76fe64ac-a9e7-446d-9942-b8aaf7ec897b wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 76fe64ac-a9e7-446d-9942-b8aaf7ec897b warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ```

# 76fe64ac-a9e7-446d-9942-b8aaf7ec897b This model is a fine-tuned version of [unsloth/Llama-3.2-3B](https://huggingface.co/unsloth/Llama-3.2-3B) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## 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: 0.0004 - train_batch_size: 6 - eval_batch_size: 6 - seed: 42 - gradient_accumulation_steps: 8 - total_train_batch_size: 48 - 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: 10 - training_steps: 50 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.0 | 0.0065 | 1 | nan | | 0.0 | 0.1626 | 25 | nan | | 0.0 | 0.3252 | 50 | nan | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1