--- library_name: peft license: mit base_model: fxmarty/tiny-dummy-qwen2 tags: - axolotl - generated_from_trainer model-index: - name: 5400612f-a4e9-4dda-bab1-630b639a7eb8 results: [] --- [Built with Axolotl](https://github.com/axolotl-ai-cloud/axolotl)
See axolotl config axolotl version: `0.4.1` ```yaml adapter: lora base_model: fxmarty/tiny-dummy-qwen2 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 444ad0ff4545664e_train_data.json ds_type: json field: text path: /workspace/input_data/444ad0ff4545664e_train_data.json type: completion 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: 8 gradient_checkpointing: true group_by_length: false hub_model_id: dimasik2987/5400612f-a4e9-4dda-bab1-630b639a7eb8 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 32 lora_dropout: 0.1 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 70GiB max_steps: 50 micro_batch_size: 2 mlflow_experiment_name: /tmp/444ad0ff4545664e_train_data.json model_type: AutoModelForCausalLM num_epochs: 3 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 25 save_strategy: steps sequence_len: 2028 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 5400612f-a4e9-4dda-bab1-630b639a7eb8 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 5400612f-a4e9-4dda-bab1-630b639a7eb8 warmup_steps: 10 weight_decay: 0.01 xformers_attention: null ```

# 5400612f-a4e9-4dda-bab1-630b639a7eb8 This model is a fine-tuned version of [fxmarty/tiny-dummy-qwen2](https://huggingface.co/fxmarty/tiny-dummy-qwen2) on the None dataset. It achieves the following results on the evaluation set: - Loss: 11.9266 ## 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: 8 - total_train_batch_size: 16 - optimizer: Use OptimizerNames.ADAMW_TORCH 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: 50 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 11.9301 | 0.0003 | 1 | 11.9295 | | 11.93 | 0.0015 | 5 | 11.9294 | | 11.9288 | 0.0029 | 10 | 11.9292 | | 11.9288 | 0.0044 | 15 | 11.9288 | | 11.9294 | 0.0059 | 20 | 11.9283 | | 11.9283 | 0.0073 | 25 | 11.9278 | | 11.9275 | 0.0088 | 30 | 11.9273 | | 11.9252 | 0.0103 | 35 | 11.9270 | | 11.9248 | 0.0117 | 40 | 11.9267 | | 11.9273 | 0.0132 | 45 | 11.9266 | | 11.9278 | 0.0147 | 50 | 11.9266 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1