--- library_name: peft base_model: peft-internal-testing/tiny-dummy-qwen2 tags: - axolotl - generated_from_trainer model-index: - name: 1f93fc32-979b-44e5-b16a-70ae030430e1 results: [] --- [Built with Axolotl](https://github.com/axolotl-ai-cloud/axolotl)
See axolotl config axolotl version: `0.4.1` ```yaml adapter: lora base_model: peft-internal-testing/tiny-dummy-qwen2 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 2565ffe651f90884_train_data.json ds_type: json format: custom path: /workspace/input_data/2565ffe651f90884_train_data.json type: field_instruction: problem field_output: solution 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: false fp16: true fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: false hub_model_id: sn56z1/1f93fc32-979b-44e5-b16a-70ae030430e1 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0001 load_in_4bit: false load_in_8bit: false local_rank: 0 logging_steps: 3 lora_alpha: 128 lora_dropout: 0.1 lora_fan_in_fan_out: true lora_model_dir: null lora_r: 64 lora_target_linear: true lr_scheduler: cosine max_steps: 500 micro_batch_size: 8 mlflow_experiment_name: /tmp/2565ffe651f90884_train_data.json model_type: AutoModelForCausalLM num_epochs: 3 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: false sample_packing: false saves_per_epoch: 4 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: null wandb_project: god wandb_run: ao3p wandb_runid: null warmup_steps: 10 weight_decay: 0.01 xformers_attention: null ```

# 1f93fc32-979b-44e5-b16a-70ae030430e1 This model is a fine-tuned version of [peft-internal-testing/tiny-dummy-qwen2](https://huggingface.co/peft-internal-testing/tiny-dummy-qwen2) on the None dataset. It achieves the following results on the evaluation set: - Loss: 11.9084 ## 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 - distributed_type: multi-GPU - num_devices: 4 - gradient_accumulation_steps: 4 - total_train_batch_size: 128 - total_eval_batch_size: 32 - 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: 263 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0114 | 1 | 11.9304 | | 11.9297 | 0.2507 | 22 | 11.9283 | | 11.924 | 0.5014 | 44 | 11.9210 | | 11.9189 | 0.7521 | 66 | 11.9175 | | 11.9155 | 1.0057 | 88 | 11.9148 | | 11.7453 | 1.2564 | 110 | 11.9126 | | 11.738 | 1.5071 | 132 | 11.9111 | | 11.5933 | 1.7578 | 154 | 11.9100 | | 12.0692 | 2.0114 | 176 | 11.9092 | | 11.9094 | 2.2621 | 198 | 11.9087 | | 11.9091 | 2.5128 | 220 | 11.9085 | | 11.9096 | 2.7635 | 242 | 11.9084 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1