--- library_name: peft license: apache-2.0 base_model: unsloth/tinyllama tags: - axolotl - generated_from_trainer model-index: - name: cb7b7f17-09e9-4fe1-a403-8cfcd08f1c23 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/tinyllama bf16: true chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - e029f217fa002728_train_data.json ds_type: json format: custom path: /workspace/input_data/e029f217fa002728_train_data.json type: field_input: overview field_instruction: raw_text field_output: clean_text format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null device_map: ? '' : 0,1,2,3,4,5,6,7 early_stopping_patience: 2 eval_max_new_tokens: 128 eval_steps: 400 eval_table_size: null flash_attention: true gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: false hub_model_id: Alphatao/cb7b7f17-09e9-4fe1-a403-8cfcd08f1c23 hub_repo: null hub_strategy: null hub_token: null learning_rate: 0.0002 load_best_model_at_end: true load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lora_target_modules: - q_proj - k_proj - v_proj - o_proj - down_proj - up_proj lr_scheduler: cosine max_grad_norm: 1.0 max_steps: 8702 micro_batch_size: 2 mlflow_experiment_name: /tmp/e029f217fa002728_train_data.json model_type: AutoModelForCausalLM num_epochs: 2 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: 400 sequence_len: 2048 strict: false tf32: true tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.04 wandb_entity: null wandb_mode: online wandb_name: f214cfe8-8866-498c-ad88-a995718d9d2d wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: f214cfe8-8866-498c-ad88-a995718d9d2d warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ```

# cb7b7f17-09e9-4fe1-a403-8cfcd08f1c23 This model is a fine-tuned version of [unsloth/tinyllama](https://huggingface.co/unsloth/tinyllama) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.1239 ## 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_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: 8702 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 5.1078 | 0.0002 | 1 | 4.2512 | | 0.0377 | 0.0897 | 400 | 0.1555 | | 0.4174 | 0.1794 | 800 | 0.1444 | | 0.0484 | 0.2690 | 1200 | 0.1452 | | 0.0263 | 0.3587 | 1600 | 0.1334 | | 0.891 | 0.4484 | 2000 | 0.1317 | | 0.0199 | 0.5381 | 2400 | 0.1302 | | 0.0252 | 0.6277 | 2800 | 0.1290 | | 0.0114 | 0.7174 | 3200 | 0.1279 | | 0.0236 | 0.8071 | 3600 | 0.1275 | | 0.0526 | 0.8968 | 4000 | 0.1261 | | 0.379 | 0.9864 | 4400 | 0.1254 | | 0.014 | 1.0761 | 4800 | 0.1258 | | 0.0125 | 1.1658 | 5200 | 0.1252 | | 0.0377 | 1.2555 | 5600 | 0.1249 | | 0.2576 | 1.3451 | 6000 | 0.1247 | | 0.4384 | 1.4348 | 6400 | 0.1244 | | 0.4103 | 1.5245 | 6800 | 0.1242 | | 0.0122 | 1.6142 | 7200 | 0.1240 | | 0.3834 | 1.7038 | 7600 | 0.1239 | | 0.2488 | 1.7935 | 8000 | 0.1239 | | 0.7307 | 1.8832 | 8400 | 0.1239 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1