--- library_name: peft base_model: katuni4ka/tiny-random-falcon-40b tags: - axolotl - generated_from_trainer model-index: - name: 357cf207-94c1-4727-83e8-a3df92021a25 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: katuni4ka/tiny-random-falcon-40b bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 106498e28a9833d4_train_data.json ds_type: json format: custom path: /workspace/input_data/106498e28a9833d4_train_data.json type: field_input: plan field_instruction: problem field_output: solution 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: true fp16: false fsdp: null fsdp_config: null gradient_accumulation_steps: 2 gradient_checkpointing: false group_by_length: true hub_model_id: lesso12/357cf207-94c1-4727-83e8-a3df92021a25 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.000212 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 10 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_grad_norm: 1.0 max_steps: 500 micro_batch_size: 4 mlflow_experiment_name: /tmp/106498e28a9833d4_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 seed: 120 sequence_len: 512 special_tokens: pad_token: <|endoftext|> 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: 0ad3d12c-5ef6-4109-a686-98f01ee6610b wandb_project: 12a wandb_run: your_name wandb_runid: 0ad3d12c-5ef6-4109-a686-98f01ee6610b warmup_steps: 50 weight_decay: 0.0 xformers_attention: null ```

# 357cf207-94c1-4727-83e8-a3df92021a25 This model is a fine-tuned version of [katuni4ka/tiny-random-falcon-40b](https://huggingface.co/katuni4ka/tiny-random-falcon-40b) on the None dataset. It achieves the following results on the evaluation set: - Loss: 10.4875 ## 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: 0.000212 - train_batch_size: 4 - eval_batch_size: 4 - seed: 120 - 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 | 0.0009 | 1 | 11.1210 | | 21.7714 | 0.0434 | 50 | 10.8178 | | 21.3436 | 0.0868 | 100 | 10.6548 | | 21.2468 | 0.1302 | 150 | 10.6071 | | 21.1852 | 0.1736 | 200 | 10.5626 | | 21.1424 | 0.2170 | 250 | 10.5307 | | 21.0647 | 0.2604 | 300 | 10.5109 | | 21.1159 | 0.3038 | 350 | 10.4972 | | 21.0575 | 0.3472 | 400 | 10.4896 | | 21.0216 | 0.3906 | 450 | 10.4908 | | 21.0878 | 0.4340 | 500 | 10.4875 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1