--- library_name: peft base_model: unsloth/Hermes-3-Llama-3.1-8B tags: - axolotl - generated_from_trainer model-index: - name: ee84fe34-f20a-40f9-8bc4-745baa3fbebe results: [] --- [Built with Axolotl](https://github.com/axolotl-ai-cloud/axolotl)
See axolotl config axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/Hermes-3-Llama-3.1-8B bf16: auto chat_template: llama3 dataloader_num_workers: 8 dataset_prepared_path: null datasets: - data_files: - d7759a0049e38789_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 early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 1 gradient_checkpointing: true group_by_length: false hub_model_id: cimol/ee84fe34-f20a-40f9-8bc4-745baa3fbebe 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: 10 lora_alpha: 32 lora_dropout: 0.15 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 32 lora_target_linear: true loraplus_lr_embedding: 1.0e-06 loraplus_lr_ratio: 16 lr_scheduler: cosine max_grad_norm: 1 max_steps: 10 micro_batch_size: 8 mlflow_experiment_name: /tmp/d7759a0049e38789_train_data.json model_type: AutoModelForCausalLM num_epochs: 10 optim_args: adam_beta1: 0.9 adam_beta2: 0.999 adam_epsilon: 1e-8 optimizer: adamw_torch_fused output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 150 saves_per_epoch: 0 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: e4b465c7-a3bd-4378-9f28-7d1f30436e5d wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: e4b465c7-a3bd-4378-9f28-7d1f30436e5d warmup_steps: 15 weight_decay: 0.0 xformers_attention: null ```

# ee84fe34-f20a-40f9-8bc4-745baa3fbebe This model is a fine-tuned version of [unsloth/Hermes-3-Llama-3.1-8B](https://huggingface.co/unsloth/Hermes-3-Llama-3.1-8B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.3674 ## 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: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.999,adam_epsilon=1e-8 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 15 - training_steps: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0001 | 1 | 1.6627 | | No log | 0.0002 | 2 | 1.6460 | | No log | 0.0003 | 3 | 1.6023 | | No log | 0.0004 | 4 | 1.5439 | | No log | 0.0005 | 5 | 1.4872 | | No log | 0.0006 | 6 | 1.4477 | | No log | 0.0006 | 7 | 1.4170 | | No log | 0.0007 | 8 | 1.4044 | | No log | 0.0008 | 9 | 1.3885 | | 1.4684 | 0.0009 | 10 | 1.3674 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1