--- library_name: peft license: llama3 base_model: WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0 tags: - axolotl - generated_from_trainer model-index: - name: 7c60848a-6ba5-4df9-a1e7-e7c74860b0db results: [] --- [Built with Axolotl](https://github.com/axolotl-ai-cloud/axolotl)
See axolotl config axolotl version: `0.4.1` ```yaml adapter: lora base_model: WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 37f5e89eedf86c48_train_data.json ds_type: json format: custom path: /workspace/input_data/37f5e89eedf86c48_train_data.json type: field_input: paragraph field_instruction: question field_output: answer format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: max_steps: 50 weight_decay: 0.01 gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: sn56m1/7c60848a-6ba5-4df9-a1e7-e7c74860b0db hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 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_memory: 0: 70GiB max_steps: 30 micro_batch_size: 2 mlflow_experiment_name: /tmp/37f5e89eedf86c48_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 70 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: sn56-miner wandb_mode: disabled wandb_name: 7c60848a-6ba5-4df9-a1e7-e7c74860b0db wandb_project: god wandb_run: lsbl wandb_runid: 7c60848a-6ba5-4df9-a1e7-e7c74860b0db warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ```

# 7c60848a-6ba5-4df9-a1e7-e7c74860b0db This model is a fine-tuned version of [WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0](https://huggingface.co/WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.5682 ## 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: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_TORCH 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: 30 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0001 | 1 | 4.8353 | | 2.4236 | 0.0012 | 8 | 3.1081 | | 0.6153 | 0.0023 | 16 | 0.6795 | | 0.4216 | 0.0035 | 24 | 0.5682 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1