--- library_name: peft license: llama3 base_model: NousResearch/Hermes-2-Pro-Llama-3-8B tags: - axolotl - generated_from_trainer model-index: - name: 26a4c4c9-3360-492e-8d72-1ea6942f4ab4 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/Hermes-2-Pro-Llama-3-8B bf16: true chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - d1ab44ecddf6a9db_train_data.json ds_type: json format: custom path: /workspace/input_data/d1ab44ecddf6a9db_train_data.json type: field_input: turn_1_kwargs field_instruction: turn_1_prompt field_output: turn_2_prompt format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: 2 eval_max_new_tokens: 128 eval_steps: 50 eval_table_size: null flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 16 gradient_checkpointing: true group_by_length: false hub_model_id: Romain-XV/26a4c4c9-3360-492e-8d72-1ea6942f4ab4 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_best_model_at_end: true 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: true lora_model_dir: null lora_r: 16 lora_target_linear: true lora_target_modules: - q_proj - k_proj - v_proj lr_scheduler: cosine max_steps: 155 micro_batch_size: 4 mlflow_experiment_name: /tmp/d1ab44ecddf6a9db_train_data.json model_type: AutoModelForCausalLM 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: 100 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: 30c5ef23-7003-47d4-9bff-9ea113ac23ab wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 30c5ef23-7003-47d4-9bff-9ea113ac23ab warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ```

# 26a4c4c9-3360-492e-8d72-1ea6942f4ab4 This model is a fine-tuned version of [NousResearch/Hermes-2-Pro-Llama-3-8B](https://huggingface.co/NousResearch/Hermes-2-Pro-Llama-3-8B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.3068 ## 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: 4 - eval_batch_size: 4 - seed: 42 - gradient_accumulation_steps: 16 - total_train_batch_size: 64 - 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: 64 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 1.6518 | 0.0157 | 1 | 1.7422 | | 0.1996 | 0.7828 | 50 | 0.3068 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1