--- library_name: peft license: apache-2.0 base_model: NousResearch/Hermes-2-Pro-Mistral-7B tags: - axolotl - generated_from_trainer model-index: - name: 2d39735f-f59b-4c9a-a973-518bd7cfbd0b results: [] --- [Built with Axolotl](https://github.com/axolotl-ai-cloud/axolotl)
See axolotl config axolotl version: `0.4.1` ```yaml absolute_data_files: false adapter: lora base_model: NousResearch/Hermes-2-Pro-Mistral-7B bf16: true chat_template: llama3 dataset_prepared_path: /workspace/axolotl datasets: - data_files: - 0e0c1e2936dded67_train_data.json ds_type: json format: custom path: /workspace/input_data/ type: field_instruction: instruct field_output: output format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null dpo: beta: 0.1 enabled: true group_by_length: false rank_loss: true reference_model: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 3 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: vertings6/2d39735f-f59b-4c9a-a973-518bd7cfbd0b hub_repo: null hub_strategy: end hub_token: null learning_rate: 2.0e-06 load_in_4bit: true load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 64 lora_dropout: 0.1 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 32 lora_target_linear: true lr_scheduler: cosine max_steps: 500 micro_batch_size: 6 mixed_precision: bf16 mlflow_experiment_name: /tmp/0e0c1e2936dded67_train_data.json model_type: AutoModelForCausalLM num_epochs: 2 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: 1 sequence_len: 1024 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: 6662be7b-4e98-40a7-bc9e-ed337f29e8d2 wandb_project: s56-7 wandb_run: your_name wandb_runid: 6662be7b-4e98-40a7-bc9e-ed337f29e8d2 warmup_steps: 50 weight_decay: 0.02 xformers_attention: true ```

# 2d39735f-f59b-4c9a-a973-518bd7cfbd0b This model is a fine-tuned version of [NousResearch/Hermes-2-Pro-Mistral-7B](https://huggingface.co/NousResearch/Hermes-2-Pro-Mistral-7B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.1349 ## 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: 2e-06 - train_batch_size: 6 - eval_batch_size: 6 - seed: 42 - gradient_accumulation_steps: 3 - total_train_batch_size: 18 - 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 | |:-------------:|:------:|:----:|:---------------:| | 3.6241 | 0.0000 | 1 | 1.6593 | | 3.4009 | 0.0058 | 250 | 1.1679 | | 2.6379 | 0.0116 | 500 | 1.1349 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1