--- license: apache-2.0 library_name: peft tags: - axolotl - generated_from_trainer base_model: EleutherAI/pythia-410m-deduped model-index: - name: 2bc524d3-39c3-413f-86ea-7a7851e7528b results: [] --- [Built with Axolotl](https://github.com/OpenAccess-AI-Collective/axolotl)
See axolotl config axolotl version: `0.4.1` ```yaml adapter: lora base_model: EleutherAI/pythia-410m-deduped bf16: auto dataset_prepared_path: null datasets: - data_files: - adcc810a6ceb3267_train_data.json ds_type: json format: custom path: adcc810a6ceb3267_train_data.json type: field: null field_input: domain field_instruction: sentence field_output: triples field_system: null format: null no_input_format: null system_format: '{system}' system_prompt: '' early_stopping_patience: null evals_per_epoch: 2 gradient_accumulation_steps: 1 group_by_length: false hub_model_id: taopanda-1/2bc524d3-39c3-413f-86ea-7a7851e7528b learning_rate: 1.0e-05 load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: true lora_model_dir: null lora_r: 16 lora_target_linear: null lora_target_modules: - query_key_value micro_batch_size: 4 num_epochs: 1 output_dir: ./outputs/lora-alpaca-pythia/taopanda-1_6b76e44c-62d5-4a35-a480-c808b829ee0b resume_from_checkpoint: null seed: 96247 sequence_len: 512 special_tokens: pad_token: <|endoftext|> tf32: true train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: fatcat87-taopanda wandb_log_model: null wandb_mode: online wandb_name: taopanda-1_6b76e44c-62d5-4a35-a480-c808b829ee0b wandb_project: subnet56 wandb_runid: taopanda-1_6b76e44c-62d5-4a35-a480-c808b829ee0b wandb_watch: null weight_decay: 0.1 ```

[Visualize in Weights & Biases](https://wandb.ai/fatcat87-taopanda/subnet56/runs/qpp21cc7) # 2bc524d3-39c3-413f-86ea-7a7851e7528b This model is a fine-tuned version of [EleutherAI/pythia-410m-deduped](https://huggingface.co/EleutherAI/pythia-410m-deduped) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.4366 ## 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: 1e-05 - train_batch_size: 4 - eval_batch_size: 4 - seed: 96247 - distributed_type: multi-GPU - num_devices: 4 - total_train_batch_size: 16 - total_eval_batch_size: 16 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 23 - num_epochs: 1 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 3.7662 | 0.0013 | 1 | 3.5014 | | 1.521 | 0.5006 | 399 | 1.4366 | ### Framework versions - PEFT 0.11.1 - Transformers 4.42.3 - Pytorch 2.3.0+cu121 - Datasets 2.19.1 - Tokenizers 0.19.1