--- library_name: peft license: llama3 base_model: NousResearch/Hermes-2-Pro-Llama-3-8B tags: - axolotl - generated_from_trainer model-index: - name: 2349d5fb-7778-e934-bfb3-25da4637e04a 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: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 57a9c77b8cccbc26_train_data.json ds_type: json format: custom path: /workspace/input_data/57a9c77b8cccbc26_train_data.json type: field_input: parent_emotion field_instruction: parent_text field_output: reply_text 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: 5 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: duyphu/2349d5fb-7778-e934-bfb3-25da4637e04a hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0001 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 5 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 50 micro_batch_size: 2 mlflow_experiment_name: /tmp/57a9c77b8cccbc26_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 saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 2b7935c7-28db-4bcd-a075-490b9803b3cc wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 2b7935c7-28db-4bcd-a075-490b9803b3cc warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ```

# 2349d5fb-7778-e934-bfb3-25da4637e04a 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: 2.7958 ## 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: 0.0001 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - 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: 10 - training_steps: 50 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0006 | 1 | 3.3459 | | 3.119 | 0.0061 | 10 | 3.2056 | | 3.0813 | 0.0122 | 20 | 2.9366 | | 2.5708 | 0.0183 | 30 | 2.8241 | | 2.8239 | 0.0244 | 40 | 2.7999 | | 2.8232 | 0.0305 | 50 | 2.7958 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1