--- library_name: peft base_model: NousResearch/Yarn-Llama-2-7b-64k tags: - axolotl - generated_from_trainer model-index: - name: be22adab-944b-44dd-b2f5-34176f365895 results: [] --- [Built with Axolotl](https://github.com/axolotl-ai-cloud/axolotl)
See axolotl config axolotl version: `0.4.1` ```yaml adapter: lora auto_find_batch_size: true base_model: NousResearch/Yarn-Llama-2-7b-64k bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 1dc9438022262def_train_data.json ds_type: json format: custom path: /workspace/input_data/1dc9438022262def_train_data.json type: field_input: Source field_instruction: Script field_output: Content format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null do_eval: true early_stopping_patience: 3 eval_max_new_tokens: 128 eval_steps: 50 evals_per_epoch: null flash_attention: false fp16: false fsdp: null fsdp_config: null gradient_accumulation_steps: 2 gradient_checkpointing: false group_by_length: true hub_model_id: lesso03/be22adab-944b-44dd-b2f5-34176f365895 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.000203 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 10 lora_alpha: 128 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 64 lora_target_linear: true lr_scheduler: cosine max_grad_norm: 1.0 max_steps: 500 micro_batch_size: 4 mlflow_experiment_name: /tmp/G.O.D/1dc9438022262def_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 save_steps: 50 saves_per_epoch: null sequence_len: 512 strict: false tf32: true tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 4a4ff803-1f36-452e-a6bd-d415e53ba94f wandb_project: 03a wandb_run: your_name wandb_runid: 4a4ff803-1f36-452e-a6bd-d415e53ba94f warmup_steps: 50 weight_decay: 0.0 xformers_attention: null ```

# be22adab-944b-44dd-b2f5-34176f365895 This model is a fine-tuned version of [NousResearch/Yarn-Llama-2-7b-64k](https://huggingface.co/NousResearch/Yarn-Llama-2-7b-64k) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.8033 ## 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: 0.000203 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - gradient_accumulation_steps: 2 - 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: 50 - training_steps: 500 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0004 | 1 | 2.2280 | | 2.597 | 0.0184 | 50 | 1.3078 | | 2.0506 | 0.0368 | 100 | 1.1180 | | 1.9292 | 0.0552 | 150 | 1.0144 | | 1.8005 | 0.0737 | 200 | 0.9691 | | 1.5755 | 0.0921 | 250 | 0.9145 | | 1.6099 | 0.1105 | 300 | 0.8698 | | 1.4342 | 0.1289 | 350 | 0.8378 | | 1.5467 | 0.1473 | 400 | 0.8157 | | 1.4868 | 0.1657 | 450 | 0.8051 | | 1.5057 | 0.1841 | 500 | 0.8033 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1