--- library_name: peft license: other base_model: NousResearch/Meta-Llama-3-8B-Instruct tags: - axolotl - generated_from_trainer model-index: - name: 123e4567-e89b-12d3-a456-426614174000 results: [] --- [Built with Axolotl](https://github.com/axolotl-ai-cloud/axolotl)
See axolotl config axolotl version: `0.4.1` ```yaml adapter: lora base_model: NousResearch/Meta-Llama-3-8B-Instruct bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - format: custom path: mhenrichsen/alpaca_2k_test type: field_input: input field_instruction: instruction field_output: output format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: sylyas/123e4567-e89b-12d3-a456-426614174000 hub_repo: sylyas hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: true 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 lr_scheduler: cosine max_steps: 500 micro_batch_size: 1 mlflow_experiment_name: mhenrichsen/alpaca_2k_test 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 saves_per_epoch: 4 sequence_len: 512 special_tokens: pad_token: <|eot_id|> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: ilyas wandb_mode: online wandb_name: 123e4567-e89b-12d3-a456-426614174000 wandb_project: Public_TuningSN wandb_run: miner_id_24 wandb_runid: 123e4567-e89b-12d3-a456-426614174000 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ```

# 123e4567-e89b-12d3-a456-426614174000 This model is a fine-tuned version of [NousResearch/Meta-Llama-3-8B-Instruct](https://huggingface.co/NousResearch/Meta-Llama-3-8B-Instruct) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.9018 ## 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: 1 - eval_batch_size: 1 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 4 - 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: 475 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 1.3764 | 0.0021 | 1 | 1.6561 | | 0.9225 | 0.2505 | 119 | 0.9177 | | 1.0708 | 0.5011 | 238 | 0.9003 | | 1.066 | 0.7516 | 357 | 0.9018 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1