--- library_name: peft base_model: peft-internal-testing/tiny-dummy-qwen2 tags: - axolotl - generated_from_trainer model-index: - name: adc9e498-4e5e-46a0-90a9-d8aad46447d9 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: - dc3686010ca1f501_train_data.json ds_type: json format: custom path: /workspace/input_data/dc3686010ca1f501_train_data.json type: field_input: raw_text field_instruction: tokenized field_output: lemmatized format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: 1 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: false hub_model_id: vmpsergio/adc9e498-4e5e-46a0-90a9-d8aad46447d9 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: 3 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_memory: 0: 78GiB max_steps: 30 micro_batch_size: 2 mlflow_experiment_name: /tmp/dc3686010ca1f501_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 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: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: d1e7b285-efbb-4369-bed7-57c1a3753b0b wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: d1e7b285-efbb-4369-bed7-57c1a3753b0b warmup_steps: 10 weight_decay: 0.01 xformers_attention: true ```

# adc9e498-4e5e-46a0-90a9-d8aad46447d9 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: 11.9463 ## 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_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: 30 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0005 | 1 | 11.9505 | | 11.9491 | 0.0023 | 5 | 11.9503 | | 11.9492 | 0.0045 | 10 | 11.9495 | | 11.9496 | 0.0068 | 15 | 11.9483 | | 11.9489 | 0.0090 | 20 | 11.9471 | | 11.9463 | 0.0113 | 25 | 11.9464 | | 11.9473 | 0.0136 | 30 | 11.9463 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1