--- library_name: peft license: apache-2.0 base_model: NousResearch/Hermes-2-Pro-Mistral-7B tags: - axolotl - generated_from_trainer model-index: - name: e98fba32-14f2-4ede-95d2-489fe2e260ed 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-Mistral-7B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - e7907239bd59ecf9_train_data.json ds_type: json format: custom path: /workspace/input_data/e7907239bd59ecf9_train_data.json type: field_input: inputs field_instruction: prompts field_output: paragraphs 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/e98fba32-14f2-4ede-95d2-489fe2e260ed 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/e7907239bd59ecf9_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: 4eb2235b-01b0-4839-96a6-ad0a92176a03 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 4eb2235b-01b0-4839-96a6-ad0a92176a03 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ```

# e98fba32-14f2-4ede-95d2-489fe2e260ed 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: 0.4591 ## 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 | 0.0012 | 1 | 0.7291 | | 2.8804 | 0.0119 | 10 | 0.5988 | | 1.9343 | 0.0237 | 20 | 0.5030 | | 1.9827 | 0.0356 | 30 | 0.4731 | | 1.5897 | 0.0474 | 40 | 0.4624 | | 1.7466 | 0.0593 | 50 | 0.4591 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1