--- library_name: peft license: apache-2.0 base_model: unsloth/SmolLM-1.7B-Instruct tags: - axolotl - generated_from_trainer model-index: - name: fbb0a946-ad61-4cfc-8369-4a4276dac3bd 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/SmolLM-1.7B-Instruct bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 2e320ec8fcaae472_train_data.json ds_type: json format: custom path: /workspace/input_data/2e320ec8fcaae472_train_data.json type: field_instruction: Question field_output: Answer format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device_map: auto do_eval: true early_stopping_patience: null eval_batch_size: 2 eval_max_new_tokens: 128 eval_steps: null eval_table_size: null evals_per_epoch: 4 flash_attention: true fp16: false fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: true hub_model_id: sn56a1/fbb0a946-ad61-4cfc-8369-4a4276dac3bd 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_grad_norm: 1.0 max_memory: 0: 75GB max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/2e320ec8fcaae472_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: null saves_per_epoch: null 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: 37y5 wandb_runid: null warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ```

# fbb0a946-ad61-4cfc-8369-4a4276dac3bd This model is a fine-tuned version of [unsloth/SmolLM-1.7B-Instruct](https://huggingface.co/unsloth/SmolLM-1.7B-Instruct) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.3510 ## 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 - distributed_type: multi-GPU - num_devices: 4 - gradient_accumulation_steps: 4 - total_train_batch_size: 32 - total_eval_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: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0021 | 1 | 1.9243 | | 1.6573 | 0.1039 | 50 | 1.5584 | | 1.402 | 0.2078 | 100 | 1.3848 | | 1.4291 | 0.3117 | 150 | 1.3567 | | 1.3839 | 0.4156 | 200 | 1.3510 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1